# kb

id: engineer-20260505-0
file: data/en.wikipedia.org/wiki/Engineer-0.md
category: reference
title: Engineer
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Engineer
date_saved: 2026-05-05T03:47:33.022400+00:00
instance: kb-cron
parent: engineer-20260505-0
summary:
An engineer is a practitioner of engineering. The word engineer (Latin ingeniator, Ir is the term and or title of an engineer in countries like Belgium, The Netherlands, and Indonesia) is derived from the Latin words ingeniare ("to contrive, devise") and ingenium ("cleverness"). The foundational qualifications of a licensed professional engineer typically include a four-year bachelor's degree in an engineering discipline, or in some jurisdictions, a master's degree in an engineering discipline plus four to six years of peer-reviewed professional practice (culminating in a project report or thesis) and passage of engineering board examinations. The work of engineers forms the link between scientific discoveries and their subsequent applications to human and business needs and quality of life. == Definition == In 1961, the Conference of Engineering Societies of Western Europe and the United States of America defined "professional engineer" as follows: A professional engineer is competent by virtue of his/her fundamental education and training to apply the scientific method and outlook to the analysis and solution of engineering problems. He/she is able to assume personal responsibility for the development and application of engineering science and knowledge, notably in research, design, construction, manufacturing, superintending, managing, and in the education of the


id: engineer-20260505-1
file: data/en.wikipedia.org/wiki/Engineer-1.md
category: reference
title: Engineer
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Engineer
date_saved: 2026-05-05T03:47:33.022400+00:00
instance: kb-cron
parent: engineer-20260505-0
summary:
There are many branches of engineering, each of which specializes in specific technologies and products. Typically, engineers will have deep knowledge in one area and basic knowledge in related areas. For example, mechanical engineering curricula typically include introductory courses in electrical engineering, computer science, materials science, metallurgy, mathematics, and software engineering. An engineer may either be hired for a firm that requires engineers on a continuous basis, or may belong to an engineering firm that provides engineering consulting services to other firms. When developing a product, engineers typically work in interdisciplinary teams. For example, when building robots an engineering team will typically have at least three types of engineers. A mechanical engineer would design the body and actuators. An electrical engineer would design the power systems, sensors, electronics, embedded software in electronics, and control circuitry. Finally, a software engineer would develop the software that makes the robot behave properly. Engineers that aspire to management engage in further study in business administration, project management and organizational or business psychology. Often engineers move up the management hierarchy from managing projects, functional departments, and divisions, and some eventually become CEOs of multi-national corporations. == Ethics == Engineers have obligations to the public, their


id: engineer-20260505-2
file: data/en.wikipedia.org/wiki/Engineer-2.md
category: reference
title: Engineer
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Engineer
date_saved: 2026-05-05T03:47:33.022400+00:00
instance: kb-cron
parent: engineer-20260505-0
summary:
In the United States, engineering is a regulated profession whose practice and practitioners are licensed and governed by law. Licensure is generally attainable through combination of education, pre-examination (Fundamentals of Engineering exam), examination (professional engineering exam), and engineering experience (typically in the area of 5+ years). Each state tests and licenses professional engineers. Currently, most states do not license by specific engineering discipline, but rather provide generalized licensure, and trust engineers to use professional judgment regarding their individual competencies; this is the favoured approach of the professional societies. Despite this, at least one of the examinations required by most states is actually focused on a particular discipline; candidates for licensure typically choose the category of examination which comes closest to their respective expertise. In the United States, an "industrial exemption" allows businesses to employ employees and call them an "engineer", as long as such individuals are under the direct supervision and control of the business entity and function internally related to manufacturing (manufactured parts) related to the business entity, or work internally within an exempt organization. Such person does not have the final authority to approve, or the ultimate responsibility for, engineering designs, plans, or specifications that are to be


id: engineer-20260505-3
file: data/en.wikipedia.org/wiki/Engineer-3.md
category: reference
title: Engineer
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Engineer
date_saved: 2026-05-05T03:47:33.022400+00:00
instance: kb-cron
parent: engineer-20260505-0
summary:
In France, the term ingénieur (engineer) is not a protected title and can be used by anyone who practices this profession. However, the title ingénieur diplomé (graduate engineer) is an official academic title that is protected by the government and is associated with the Diplôme d'Ingénieur, which is a renowned academic degree in France. Anyone misusing this title in France can be fined a large sum and jailed, as it is usually reserved for graduates of French engineering grandes écoles. Engineering schools which were created during the French revolution have a special reputation among the French people, as they helped to make the transition from a mostly agricultural country of late 18th century to the industrially developed France of the 19th century. A great part of 19th-century France's economic wealth and industrial prowess was created by engineers that have graduated from École Centrale Paris, École des Mines de Paris, École polytechnique or Télécom Paris. This was also the case after WWII when France had to be rebuilt. Before the "réforme René Haby" in the 1970s, it was very difficult to be admitted to such schools, and the French ingénieurs were commonly perceived as the nation's élite. However, after the Haby


id: engineering-technician-20260505-0
file: data/en.wikipedia.org/wiki/Engineering_technician-0.md
category: reference
title: Engineering technician
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Engineering_technician
date_saved: 2026-05-05T03:47:34.272828+00:00
instance: kb-cron
parent: engineering-technician-20260505-0
summary:
An engineering technician is a professional trained in skills and techniques related to a specific branch of technology, with a practical understanding of the relevant engineering concepts. Engineering technicians often assist in projects relating to research and development, or focus on post-development activities like implementation or operation. The Dublin Accord was signed in 2002 as an international agreement recognizing engineering technician qualifications. The Dublin Accord is analogous to the Washington Accord for engineers and the Sydney Accord for engineering technologists. == Nature of work == Engineering technicians help solve technical problems in many ways. They build or set up equipment, conduct experiments, collect data, and calculate results. They might also help to make a model of new equipment. Some technicians work in quality control, checking products, tests, and collecting data. In manufacturing, they help to design and develop products. They also find ways to produce things efficiently. There are multiple fields in this job such as; software design, repair, etc. They may also be people who produce technical drawings or engineering drawings. Engineering technicians are responsible for using the theories and principles of science, engineering, and mathematics to solve problems and come up with solutions in the research, design, development,


id: engineering-technologist-20260505-0
file: data/en.wikipedia.org/wiki/Engineering_technologist-0.md
category: reference
title: Engineering technologist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Engineering_technologist
date_saved: 2026-05-05T03:47:39.275195+00:00
instance: kb-cron
parent: engineering-technologist-20260505-0
summary:
An engineering technologist is a professional trained in certain aspects of development and implementation of a respective area of technology. An education in engineering technology concentrates more on application and less on theory than does an engineering education. Engineering technologists often assist engineers; but after years of experience, they can also become engineers. Like engineers, areas where engineering technologists can work include product design, fabrication, and testing. Engineering technologists sometimes rise to senior management positions in industry or become entrepreneurs. Engineering technologists are more likely than engineers to focus on post-development implementation, product manufacturing, or operation of technology. The American National Society of Professional Engineers (NSPE) makes the distinction that engineers are trained in conceptual skills, to "function as designers", while engineering technologists "apply others' designs". The mathematics and sciences, as well as other technical courses, in engineering technology programs, are taught with more application-based examples, whereas engineering coursework provides a more theoretical foundation in math and science. Moreover, engineering coursework tends to require higher-level mathematics including calculus and calculus-based theoretical science courses, as well as more extensive knowledge of the natural sciences, which serves to prepare students for research (whether in graduate studies or industrial R&D) as opposed to


id: engineering-technologist-20260505-1
file: data/en.wikipedia.org/wiki/Engineering_technologist-1.md
category: reference
title: Engineering technologist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Engineering_technologist
date_saved: 2026-05-05T03:47:39.275195+00:00
instance: kb-cron
parent: engineering-technologist-20260505-0
summary:
=== Canada === In Canada, the new occupational category of "technologist" was established in the 1960s, in conjunction with an emerging system of community colleges and technical institutes. It was designed to effectively bridge the gap between the increasingly theoretical nature of engineering degrees and the predominantly practical approach of technician and trades programs. Provincial associations may certify individuals as a professional technologist (P.Tech.), certified engineering technologist (C.E.T.), registered engineering technologist (R.E.T.), applied science technologist (AScT), or technologue professionel (T.P.). These provincial associations are constituent members of Technology Professionals Canada (TPC), which accredits technology programs across Canada, through its Technology Accreditation Canada (TAC). Nationally accredited engineering technology programs range from two to three years in length, depending on the province, and often require as many classroom hours as a 4-year degree program. === United States === In the United States, the U.S. Department of Education or the Council for Higher Education Accreditation (CHEA) are at the top of the educational accreditation hierarchy. The U.S. Department of Education acknowledges regional and national accreditation and CHEA recognizes specialty accreditation. One technology accreditation is currently recognized by CHEA: The Association of Technology, Management and Applied Engineering (ATMAE). CHEA recognizes ATMAE for accrediting associate,


id: engineering-technologist-20260505-2
file: data/en.wikipedia.org/wiki/Engineering_technologist-2.md
category: reference
title: Engineering technologist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Engineering_technologist
date_saved: 2026-05-05T03:47:39.275195+00:00
instance: kb-cron
parent: engineering-technologist-20260505-0
summary:
writing a technical report, based upon their experience and demonstrate their knowledge and understanding of engineering principles; earning the City and Guilds graduate diploma (bachelors level) and a postgraduate diploma (masters level) accredited by the Institution of Mechanical Engineers (IMechE), Institution of Engineering and Technology (IET) and Institution of Civil Engineers (ICE); following a work-based learning program; or taking an academic program specified by the institution to which they are applying. === Germany – European Union === ==== Engineering technologist / state-certified engineer ==== The engineering technologist (state-certified technician; German: Staatlich geprüfter Techniker) are vocational (non-academic) qualifications at the tertiary level in Germany. The degree is governed by the framework agreement of trade and technical schools (resolution of the Standing Conference of the Ministers of Education and Cultural Affairs of the states in the Federal Republic of Germany of 7 November 2002 in its respective applicable version) and is recognised by all states of the Federal Republic of Germany. It is awarded after passing state examinations at state or state-recognised technical school or academies (German: Fachschule/Fachakademie). Through the Vocational Training Modernisation Act (12.12.2019), state-certified engineers are also allowed to hold the title Bachelor Professional in Technik as of 1 January


id: geneticist-20260505-0
file: data/en.wikipedia.org/wiki/Geneticist-0.md
category: reference
title: Geneticist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Geneticist
date_saved: 2026-05-05T03:47:40.503712+00:00
instance: kb-cron
parent: geneticist-20260505-0
summary:
A geneticist is a biologist or physician who studies genetics, the science of genes, heredity, and variation of organisms. A geneticist can be employed as a scientist or a lecturer. Geneticists may perform general research on genetic processes or develop genetic technologies to aid in the pharmaceutical or and agriculture industries. Some geneticists perform experiments in model organisms such as Drosophila, C. elegans, zebrafish, rodents or humans and analyze data to interpret the inheritance of biological traits. A basic science geneticist is a scientist who usually has earned a PhD in genetics and undertakes research and/or lectures in the field. A medical geneticist is a physician who has been trained in medical genetics as a specialization and evaluates, diagnoses, and manages patients with hereditary conditions or congenital malformations; and provides genetic risk calculations and mutation analysis. == Education == Geneticists participate in courses from many areas, such as biology, chemistry, physics, microbiology, cell biology, bioinformatics, and mathematics. They also participate in more specifie genetics courses such as molecular genetics, transmission genetics, population genetics, quantitative genetics, ecological genetics, epigenetics, and genomics. == Careers == Geneticists can work in many different fields, doing a variety of jobs. There are many careers for


id: geographer-20260505-0
file: data/en.wikipedia.org/wiki/Geographer-0.md
category: reference
title: Geographer
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Geographer
date_saved: 2026-05-05T03:47:41.756735+00:00
instance: kb-cron
parent: geographer-20260505-0
summary:
A geographer is a physical scientist, social scientist or humanist whose area of study is geography, the study of Earth's natural environment and human society, including how society and nature interact. The Greek prefix "geo" means "earth" and the Greek suffix, "graphy", meaning "description", so a geographer is someone who studies the earth. The word "geography" is a Middle French word that is believed to have been first used in 1540. Although geographers are historically known as people who make maps, map making is actually the field of study of cartography, a subset of geography. Geographers do not study only the details of the natural environment or human society, but they also study the reciprocal relationship between these two. For example, they study how the natural environment contributes to human society and how human society affects the natural environment. In particular, physical geographers study the natural environment while human geographers study human society and culture. Some geographers are practitioners of GIS (geographic information system) and are often employed by local, state, and federal government agencies as well as in the private sector by environmental and engineering firms. The paintings by Johannes Vermeer titled The Geographer and The Astronomer are both


id: geologist-20260505-0
file: data/en.wikipedia.org/wiki/Geologist-0.md
category: reference
title: Geologist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Geologist
date_saved: 2026-05-05T03:47:43.021352+00:00
instance: kb-cron
parent: geologist-20260505-0
summary:
A geologist is a scientist who studies the structure, composition, and history of Earth. Geologists incorporate techniques from physics, chemistry, biology, mathematics, and geography to perform research in the field and the laboratory. Geologists work in the energy and mining sectors to exploit natural resources. They monitor environmental hazards such as earthquakes, volcanoes, tsunamis and landslides. Geologists are also important contributors to climate change discussions. == History == James Hutton is often viewed as the first modern geologist. In 1785 he showed a paper titled Theory of the Earth to the Royal Society of Edinburgh. In his paper, he explained his theory that the Earth must be much older than had previously been supposed to allow enough time for mountains to be eroded and for sediments to form new rocks at the bottom of the sea, which in turn were raised up to become dry land. Hutton published a two-volume version of his ideas in 1795 (Vol. 1, Vol. 2). Followers of Hutton were known as Plutonists because they believed that some rocks were formed by vulcanism, which is the deposition of lava from volcanoes, as opposed to the Neptunists, led by Abraham Werner, who believed that all rocks had


id: geologist-20260505-1
file: data/en.wikipedia.org/wiki/Geologist-1.md
category: reference
title: Geologist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Geologist
date_saved: 2026-05-05T03:47:43.021352+00:00
instance: kb-cron
parent: geologist-20260505-0
summary:
Economic geology: the study of ore genesis, and the mechanisms of ore creation, geostatistics. Engineering geology: application of the geologic sciences to engineering practice for the purpose of assuring that the geologic factors affecting the location, design, construction, operation and maintenance of engineering works are recognized and adequately provided for; Geophysics: the applied branch deals with the application of physical methods such as gravity, seismicity, electricity, magnetic properties to study the earth. Geochemistry: the applied branch deals with the study of the chemical makeup and behaviour of rocks, and the study of the behaviour of their minerals. Geochronology: the study of isotope geology specifically toward determining the date within the past of rock formation, metamorphism, mineralization and geological events (notably, meteorite impacts). Geomorphology: the study of landforms and the processes that create them. Hydrogeology: the study of the origin, occurrence and movement of groundwater water in a subsurface geological system. Igneous petrology: the study of igneous processes such as igneous differentiation, fractional crystallization, intrusive and volcanological phenomena. Isotope geology: the case of the isotopic composition of rocks to determine the processes of rock and planetary formation. Metamorphic petrology: the study of the effects of metamorphism on minerals and rocks. Marine


id: geoprofessions-20260505-0
file: data/en.wikipedia.org/wiki/Geoprofessions-0.md
category: reference
title: Geoprofessions
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Geoprofessions
date_saved: 2026-05-05T03:47:44.331397+00:00
instance: kb-cron
parent: geoprofessions-20260505-0
summary:
"Geoprofessions" is a term coined by the Geoprofessional Business Association to connote various technical disciplines that involve engineering, earth and environmental services applied to below-ground ("subsurface"), ground-surface, and ground-surface-connected conditions, structures, or formations. The principal disciplines include, as major categories: geomatics engineering geotechnical engineering; geology and engineering geology; geological engineering; geophysics; geophysical engineering; environmental science and environmental engineering; construction-materials engineering and testing; and other geoprofessional services. Each discipline involves specialties, many of which are recognized through professional designations that governments and societies or associations confer based upon a person's education, training, experience, and educational accomplishments. In the United States, engineers must be licensed in the state or territory where they practice engineering. Most states license geologists and several license environmental "site professionals." Several states license engineering geologists and recognize geotechnical engineering through a geotechnical-engineering titling act. == Geotechnical-engineering specialties == Although geotechnical engineering is applied for a variety of purposes, it is essential to foundation design. As such, geotechnical engineering is applicable to every existing or new structure on the planet; every building and every highway, bridge, tunnel, harbor, airport, water line, reservoir, or other public work. Commonly, the geotechnical-engineering service comprises a study of subsurface conditions using various sampling,


id: geoprofessions-20260505-1
file: data/en.wikipedia.org/wiki/Geoprofessions-1.md
category: reference
title: Geoprofessions
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Geoprofessions
date_saved: 2026-05-05T03:47:44.331397+00:00
instance: kb-cron
parent: geoprofessions-20260505-0
summary:
Engineering geologist. (a) Elements of the engineering geologist specialty. The practice of engineering geology involves the interpretation, evaluation, analysis, and application of geological information and data to civil works. Geotechnical soil and rock units are designated, characterized, and classified, using standard engineering soil and rock classification systems. Relationships are interpreted between landform development, current and past geologic processes, ground and surface water, and the strength characteristics of soil and rock. Processes evaluated include both surficial processes (for example, slope, fluvial, and coastal processes), and deep-seated processes (for example, volcanic activity and seismicity). Geotechnical zones or domains are designated based on soil and rocked geological strength characteristics, common landforms, related geologic processes, or other pertinent factors. Proposed developmental modifications are evaluated and, where appropriate, analyzed to predict potential or likely changes in types and rates of surficial geologic processes. Proposed modifications may include such things as vegetation removal, using various types of earth materials in construction, applying loads to shallow or deep foundations, constructing cut or fill slopes and other grading, and modifying ground and surface water flow. The effects of surficial and deep-seated geologic processes are evaluated and analyzed to predict their potential effect on public health, public safety, land


id: geoprofessions-20260505-2
file: data/en.wikipedia.org/wiki/Geoprofessions-2.md
category: reference
title: Geoprofessions
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Geoprofessions
date_saved: 2026-05-05T03:47:44.331397+00:00
instance: kb-cron
parent: geoprofessions-20260505-0
summary:
Environmental science and environmental engineering are the geoprofessions commonly associated with the identification, remediation, and prevention of environmental contamination. These services range from phase-one and phase-two environmental site-assessments – research designed to assess the likelihood that a property is contaminated and subsurface exploration conducted to identify the nature and extent of contamination, respectively – up through the design of processes and systems to remediate contaminated sites for the protection of human health and the environment. Environmental geology is one of the principal geoprofessions engaged in assessing and remediating contaminated sites. Environmental geologists help identify the subsurface stratigraphy in which contaminants are located and through which they migrate. Environmental chemistry is the geoprofession that encompasses the study of chemical compounds in the soil. These compounds are categorized as pollutants or contaminants when introduced into the environment by human factors (e.g., waste, mining processes, radioactive release) and are not of natural origin. Environmental chemistry assesses interactions or these compounds with soil, rock, and water to determine their fate and transport, the techniques to measure the levels of contaminants in the environment, and technologies to destroy or reduce the toxicity of contaminants in wastes or compounds that have been released to the environment.


id: geoprofessions-20260505-3
file: data/en.wikipedia.org/wiki/Geoprofessions-3.md
category: reference
title: Geoprofessions
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Geoprofessions
date_saved: 2026-05-05T03:47:44.331397+00:00
instance: kb-cron
parent: geoprofessions-20260505-0
summary:
== Construction-materials engineering and testing (CoMET) == Construction-materials engineering and testing (CoMET) comprises an array of licensed-engineer-directed professional services applied principally for purposes of construction quality assurance and quality control. CoMET services commonly are provided as a separate discipline by firms that also practice geotechnical engineering, possibly among other geoprofessional disciplines. The geoprofessional-service industry has evolved in this manner because geotechnical engineering employs the observational method. Karl von Terzaghi and Ralph B. Peck – the creators of modern geotechnical engineering – used the observational method and multiple working hypotheses to expedite and economize the subsurface-exploration process, by using sampling and testing to form a judgment about subsurface conditions, and then observing excavated conditions and materials to confirm or modify those judgments and related recommendations, and then finalize them. To economize still further, geoprofessionals educated and trained paraprofessionals to represent them on site (hence the term "field representative"), especially to apply their judgment (much as a geotechnical engineer would) in comparing observed conditions with those the geotechnical engineer believed would exist. Over time, geotechnical engineers expanded their CoMET services by providing the additional education and training their field representatives needed to evaluate constructors' attainment of conditions commonly specified by geoprofessionals; e.g.,


id: geoprofessions-20260505-4
file: data/en.wikipedia.org/wiki/Geoprofessions-4.md
category: reference
title: Geoprofessions
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Geoprofessions
date_saved: 2026-05-05T03:47:44.331397+00:00
instance: kb-cron
parent: geoprofessions-20260505-0
summary:
Many of the CoMET services performed for construction projects are performed for environmental projects as well, but requirements tend to be less rigid because they involve fewer licensing and related requirements. For example, individuals may perform federally mandated all-appropriate inquiries – typically a phase-one environmental site assessment – without a license of any kind.


id: geoprofessions-20260505-5
file: data/en.wikipedia.org/wiki/Geoprofessions-5.md
category: reference
title: Geoprofessions
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Geoprofessions
date_saved: 2026-05-05T03:47:44.331397+00:00
instance: kb-cron
parent: geoprofessions-20260505-0
summary:
== Other geoprofessional services == To the extent that archeology and paleontology require systematic subsurface excavation to recover artifacts, they, too, are considered geoprofessions. Many geoprofessional-services firms offer these services to those of their clients that need to satisfy federal and/or state regulations that require paleontological and/or archeological inquiry before site development or redevelopment activities can proceed. == See also == List of geology journals List of mining journals == References == Bates and Jackson. (1980) Glossary of Geology. 2nd ed., American Geological Institute. ISBN 0-913312-15-0. Bowles, J. (1988) Foundation Analysis and Design. McGraw-Hill Publishing Company. ISBN 0-07-006776-7. Burger, H. Robert, Sheehan, Anne F., and Jones, Craig H. (2006) Introduction to Applied Geophysics : Exploring the Shallow Subsurface. New York: W.W. Norton. ISBN 0-393-92637-0. Cedergren, Harry R. (1977) Seepage, Drainage, and Flow Nets. Wiley. ISBN 0-471-14179-8. Chen, W-F and Scawthorn, C. (2003) Earthquake Engineering Handbook. CRC Press, ISBN 0-8493-0068-1 Das, Braja M. (2006) Principles of Geotechnical Engineering. England: THOMSON LEARNING (KY). ISBN 0-534-55144-0. Fang, H.-Y. and Daniels, J. (2005) Introductory Geotechnical Engineering: an Environmental Perspective. Taylor & Francis. ISBN 0-415-30402-4. Faure, Gunter. (1998) Principles and Applications of Geochemistry: a Comprehensive Textbook for Geology Students. Upper Saddle River, NJ: Prentice-Hall. ISBN


id: government-scientist-20260505-0
file: data/en.wikipedia.org/wiki/Government_scientist-0.md
category: reference
title: Government scientist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Government_scientist
date_saved: 2026-05-05T03:47:45.547413+00:00
instance: kb-cron
parent: government-scientist-20260505-0
summary:
A government scientist is a scientist employed by a country's government, either in a research-driven job (for example J. Robert Oppenheimer on the Manhattan Project), or for another role that requires scientific training and methods. In some countries other terms, such as Technical officers, is also used for scientists. == Australia == In Australia, most government scientists are employed by the Commonwealth Scientific and Industrial Research Organisation. A Chief Scientist is appointed to advise the government through the Office of the Chief Scientist. == Singapore == In Singapore, government scientists are classified according to the Departmental Titles (Alteration) (Amendment) Act 1996, which amended the Departmental Titles (Alteration) Ordinance of 1950. == United Kingdom == In the United Kingdom, government scientists are part of the Scientific Civil Service. However, that was not always the case. Before the Second World War, government scientists were recruited and employed by the Civil Service on an ad hoc basis, with grades, job titles, and organizations that varied between departments. In 1930, the Carpenter Committee was appointed to investigate the organization of civil service scientific and technical staff, and its report proposed a reorganization that covered the entire Service. This report was endorsed by the Tomlin


id: healthcare-scientist-20260505-0
file: data/en.wikipedia.org/wiki/Healthcare_scientist-0.md
category: reference
title: Healthcare scientist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Healthcare_scientist
date_saved: 2026-05-05T03:47:46.825606+00:00
instance: kb-cron
parent: healthcare-scientist-20260505-0
summary:
A healthcare scientist (HCS), or medical scientist, is a scientist working in any of a number of health related disciplines. Healthcare scientists may work directly for health service providers, or in academia or industry. Healthcare scientists typically refers to those contributing directly to clinical services, and not scientists working solely in health related research and development. == Disciplines == Boundaries between healthcare science and other related fields are not strictly defined. There are more than 50 different specialisms. Healthcare scientists work in clinical bioinformatics, life sciences, physical sciences and physiological sciences. A non-exhaustive list of healthcare science roles is below. Medical physicist Biomedical scientist Audiologist Clinical cytogeneticist Clinical embryologist Neurophysiological scientist Vascular scientist Cardiac scientist == Organization == Regulation and organization of healthcare scientists varies significantly from country to country, and from discipline to discipline. === Europe === ==== United Kingdom ==== There are over 50,000 healthcare scientists working in the NHS. Biomedical Scientist and Clinical scientist are a protected title in the United Kingdom, requiring state registration. The Health and Care Professions Council holds the register and regulates the profession. The main routes to registration and training are through courses run by the Institute of Biomedical Science or the


id: laboratory-manager-20260505-0
file: data/en.wikipedia.org/wiki/Laboratory_manager-0.md
category: reference
title: Laboratory manager
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Laboratory_manager
date_saved: 2026-05-05T03:47:49.254811+00:00
instance: kb-cron
parent: laboratory-manager-20260505-0
summary:
A laboratory manager (alternatively laboratory supervisor) is an individual who supervises personnel and operations in a laboratory environment; the position is senior to that of a laboratory technician or laboratory technologist, and is considered a middle-management occupation. == Nature of work == While the duties of laboratory managers depend on their particular field or industry, they generally direct or coordinate scientific research and related activities such as quality control, along with ensuring laboratories have the necessary equipment and materials to sustain operations. Depending on the size of the company or academic institution, the scope of a manager's responsibilities also varies. At a senior level, a laboratory manager may be an administrator primarily responsible for budgets, hiring and supervising scientific and technical personnel, and working with senior management to develop goals and strategies for the organization. Laboratory managers or supervisors at this level may be responsible for managing large teams. Some laboratory managers are current or former scientists who are sometimes called "working managers," and who participate in conducting research in addition to administrative duties, mentoring students, and assisting other researchers. Managers in this category are commonly known as staff scientists. Chemistry laboratory managers may also be chemical hygiene officers responsible


id: laboratory-technician-20260505-0
file: data/en.wikipedia.org/wiki/Laboratory_technician-0.md
category: reference
title: Laboratory technician
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Laboratory_technician
date_saved: 2026-05-05T03:47:50.565122+00:00
instance: kb-cron
parent: laboratory-technician-20260505-0
summary:
A laboratory technician or (informally) lab tech is a person who works in a laboratory performing analytical or experimental procedures, maintaining laboratory equipment. According to the Oxford English Dictionary, the first use of the term laboratory technician was in 1896:It [sc. a therapeutic property] is now totally abandoned by the advanced laboratory technicians.The term is now widely accepted. Laboratory technicians are found in a wide range of scientific fields, including forensic science, pathology, chemistry, biomedical science and physics. Laboratory technicians may hold a range of formal academic qualifications, such as associate degrees, often obtained through vocational education. They are usually supervised by laboratory managers. == References ==


id: medical-laboratory-scientist-20260505-0
file: data/en.wikipedia.org/wiki/Medical_laboratory_scientist-0.md
category: reference
title: Medical laboratory scientist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Medical_laboratory_scientist
date_saved: 2026-05-05T03:47:55.874604+00:00
instance: kb-cron
parent: medical-laboratory-scientist-20260505-0
summary:
A medical laboratory scientist (MLS), clinical laboratory scientist (CLS), or medical technologist (MT) is a licensed healthcare professional who performs diagnostic testing of body fluids, examples: blood, urine, sputum and other body tissue. The medical technologist is tasked with releasing the patient's results to aid in further treatment. The scope of a medical laboratory scientist's work begins with the receipt of patient or client specimens, and finishes with the delivery of test results to physicians and other healthcare providers. The utility of clinical diagnostic testing relies squarely on the validity of test methodology. To this end, much of the work done by medical laboratory scientists involves ensuring specimen quality, interpreting test results, data-logging, testing control products, performing calibration, maintenance, validation, and troubleshooting of instrumentation as well as performing statistical analyses to verify the accuracy and repeatability of testing. Medical laboratory scientists may also assist healthcare providers with test selection and specimen collection and are responsible for prompt verbal delivery of critical lab results. Medical laboratory scientists in healthcare settings also play an important role in clinical diagnosis; some estimates suggest that up to 70% of medical decisions are based on laboratory test results and MLS contributions affect 95% of a


id: medical-laboratory-scientist-20260505-1
file: data/en.wikipedia.org/wiki/Medical_laboratory_scientist-1.md
category: reference
title: Medical laboratory scientist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Medical_laboratory_scientist
date_saved: 2026-05-05T03:47:55.874604+00:00
instance: kb-cron
parent: medical-laboratory-scientist-20260505-0
summary:
== Specialty areas == Many medical laboratory scientists are generalists, skilled in most areas of the clinical laboratory. However, some are specialists, qualified by unique undergraduate education or additional training to perform more complex analyses than usual within a specific field. Specialties include clinical biochemistry, hematology, coagulation, microbiology, bacteriology, toxicology, virology, parasitology, mycology, immunology, immunohematology (blood bank), histopathology, histocompatibility, cytopathology, genetics, cytogenetics, electron microscopy, and IVF labs. Medical technologists specialty may use additional credentials, such as "SBB" (specialist in blood banking), "SM" (Ssecialist in microbiology), "SC" (specialist in chemistry), or "SH" (specialist in hematology) from the American Society for Clinical Pathology (ASCP). These additional notations may be appended to the base credential, for example, "MLS (ASCP), SBB (ASCP)". Additional information can be found in the ASCP Procedures for Examination & Certification. Andrology laboratory scientist, embryology laboratory scientist, and molecular diagnostics technologist certifications are provided by the American Association of Bioanalysts; those with the certifications are classified as ALS (AAB), ELS (AAB), and MDxT (AAB), respectively. Certified histocompatibility associate, certified histocompatibility technologist, certified histocompatibility specialist, and diplomate of the ABHI are titles granted by the American Board of Hisocompatibility and Immunogenetics after meeting education and experience requirements and passing the required


id: medical-laboratory-scientist-20260505-2
file: data/en.wikipedia.org/wiki/Medical_laboratory_scientist-2.md
category: reference
title: Medical laboratory scientist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Medical_laboratory_scientist
date_saved: 2026-05-05T03:47:55.874604+00:00
instance: kb-cron
parent: medical-laboratory-scientist-20260505-0
summary:
=== Pakistan === In Pakistan, the National Institute of Health (NIH) in Islamabad is the pioneer in laboratory sciences. The College of Medical Lab Technology (CMLT) of the NIH offers a two-year F.Sc degree in Medical Lab Technology (MLT). The previous two-year B.Sc. in MLT was discontinued and replaced by the four-year Bachelor Program in Medical Lab Sciences (MLS). The University of Health Sciences in Lahore also offers a four-year Bachelor program in MLS through approved colleges. The University of Lahore, University of Faisalabad, University of Sargodha, and Superior University in Lahore all offer a five-year Doctor of Medical Lab Sciences (DMLS) Program. Eligibility criteria for the four-year B.Sc. in MLS and the five-year Doctor of Medical Lab Sciences (DMLS) is the F.Sc. Pre-Medical. === United States === In the United States, a medical laboratory scientist (MLS), medical technologist (MT), or a clinical laboratory scientist (CLS) typically earns a bachelor's degree in medical laboratory science, clinical laboratory science, or medical technology. Other routes include attaining a degree in biomedical science or in a life / biological science (biology, biochemistry, microbiology, etc.). Both routes typically requires the MLS/MT/CLS to obtain certification from a national certifying board (AAB, AMT, or ASCP) as


id: medical-laboratory-scientist-20260505-3
file: data/en.wikipedia.org/wiki/Medical_laboratory_scientist-3.md
category: reference
title: Medical laboratory scientist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Medical_laboratory_scientist
date_saved: 2026-05-05T03:47:55.874604+00:00
instance: kb-cron
parent: medical-laboratory-scientist-20260505-0
summary:
=== United Kingdom === In the United Kingdom (UK) there are two varieties of registered healthcare scientist in hospitals - Clinical Scientists and Biomedical Scientists (BMS). There is a strict and formal post graduate training programme for both careers followed by statutory registration for each with the Health & Care Professions Council UK (HCPC), for the safety and assurance of the customers - the patients. They are two similar but distinct careers with parallel but different training paths and different entry requirements. The role of Clinical Scientists is to improve the health and well-being of patients and the public by practising alongside doctors, nurses, and other health and social care professionals in the delivery of healthcare. Their aim is to provide expert scientific and clinical advice to clinician colleagues, to aid in the diagnosis, treatment and management of patient care. Examples of the type of work they undertake include: Advising, diagnosing, interpreting, and treating patients Advising health and social care professionals in the diagnosis and treatment of patients Researching the science, technology, and practise used in healthcare to innovate and improve services Designing, building, and operating technology for diagnosing and treating patients Ensuring the safety and reliability of tests and


id: medical-laboratory-scientist-20260505-4
file: data/en.wikipedia.org/wiki/Medical_laboratory_scientist-4.md
category: reference
title: Medical laboratory scientist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Medical_laboratory_scientist
date_saved: 2026-05-05T03:47:55.874604+00:00
instance: kb-cron
parent: medical-laboratory-scientist-20260505-0
summary:
=== United States === There are currently three major certification agencies in the United States of America for clinical laboratory scientists. They are the American Association of Bioanalysts (AAB), the American Medical Technologists (AMT), and the American Society for Clinical Pathology (ASCP). Clinical Laboratory Science programs have the option to be accredited by the National Accrediting Agency for Clinical Laboratory Science (NAACLS). NAACLS accreditation allows students to sit for their certification at the completion of their program in addition to being a stamp of program quality. All the three national accrediting agencies will certify scientists in the clinical laboratory as generalist (chemistry, hematology, immunology, immunohematology/blood bank, and microbiology). The American Association of Bioanalysts and the American Medical Technologists certifications continue to use the traditional designation medical technologist (MT), while the American Society for Clinical Pathology has adopted the designation of medical laboratory scientist (MLS). Regardless of terminology, these highly qualified individuals serve as scientists in the clinical laboratory. Two other organizations have previously provided proficiency examinations to clinical laboratory scientists: the US Department of Health and Human Services, and the National Credentialing Agency for Laboratory Personnel (NCA). The NCA was absorbed by the American Society for Clinical Pathology in 2009


id: medical-laboratory-scientist-20260505-5
file: data/en.wikipedia.org/wiki/Medical_laboratory_scientist-5.md
category: reference
title: Medical laboratory scientist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Medical_laboratory_scientist
date_saved: 2026-05-05T03:47:55.874604+00:00
instance: kb-cron
parent: medical-laboratory-scientist-20260505-0
summary:
Master of Science, Master of Business Administration, Master of Health Administration, Doctor of medical laboratory science for specialization, education and management roles. Doctor of Philosophy for management and directorship roles in the clinical laboratory as well as for academic research and professorship. Doctors of Philosophy holding a degree in a biological science, and who are board certified by a CLIA-approved entity, are qualified as a medical laboratory director. Doctor of Medicine or Doctor of clinical laboratory Science - this is the position that qualifies an individual to oversee or direct almost all types of clinical laboratories. Under U.S. CLIA laws, a requirement of at least year of clinical laboratory experience (any MD) or pathology residency must be met. In the United Kingdom the Modernising Scientific Careers (MSC) programme sets out for the first time a comprehensive training and career framework for the whole healthcare science workforce inclusive of the more than 50 different scientific professional specialisms. In its conception it aimed to provide a coherent framework that was accessible, affordable and designed specifically to both capture scientific and technological advances and to provide improved outcomes for patients, the service and professionals. A key aspect of the framework from the start


id: medical-laboratory-scientist-20260505-6
file: data/en.wikipedia.org/wiki/Medical_laboratory_scientist-6.md
category: reference
title: Medical laboratory scientist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Medical_laboratory_scientist
date_saved: 2026-05-05T03:47:55.874604+00:00
instance: kb-cron
parent: medical-laboratory-scientist-20260505-0
summary:
== Labor shortage == Medical facilities throughout the United States have gradually been experiencing a shortage in medical laboratory science professionals. The current projectory of medical laboratory personnel through 2030 is insufficient to serve medical services effectively. Reasons for the shortage include current professionals retiring, a modern increase in medical laboratory scientist and technician demand, changes in the practice caused by new technological advances (which need training to learn to use), and vacancy and retirement rates being greater than the number of graduates from medical laboratory programs. Lack of funding, low salaries, lack of a developed career ladder, and a lack of clear job requirements has made recruitment and the hiring process difficult. Newer recruiting attempts have increased the number of graduated professionals in the last five years, but not enough to meet the growing demand. Some clinical organizations suggest that professional-development programs for the allied health fields should be improved to cultivate interest in younger professionals and students. The Institute of Medicine is actively working on re-viewing policy reforms and new plans and recommendations to increase medical professional turnout among younger people. The COVID-19 pandemic highlighted the medical laboratory shortage in the medical field. Organizations such as the American


id: meteorologist-20260505-0
file: data/en.wikipedia.org/wiki/Meteorologist-0.md
category: reference
title: Meteorologist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Meteorologist
date_saved: 2026-05-05T03:47:57.188632+00:00
instance: kb-cron
parent: meteorologist-20260505-0
summary:
A meteorologist is a scientist who studies and works in the field of meteorology aiming to understand or predict Earth's atmospheric phenomena including the weather. Those who study meteorological phenomena are meteorologists in research, while those using mathematical models and knowledge to prepare daily weather forecasts are called weather forecasters or operational meteorologists. Meteorologists work in government agencies, private consulting and research services, industrial enterprises, utilities, radio and television stations, and in education. They are not to be confused with weather presenters, who present the weather forecast in the media and range in training from journalists having just minimal training in meteorology to full-fledged meteorologists. == Description == Meteorologists study the Earth's atmosphere and its interactions with the Earth's surface, the oceans and the biosphere. Their knowledge of applied mathematics and physics allows them to understand the full range of atmospheric phenomena, from snowflake formation to the Earth's general climate. Research meteorologists are specialized in areas like: Climatology to estimate the various components of the climate and their variability to determine, for example, the wind potential of a given region or global warming. Air quality where they are interested in the phenomena of transport, transformation and dispersion of atmospheric pollutants


id: microbiologist-20260505-0
file: data/en.wikipedia.org/wiki/Microbiologist-0.md
category: reference
title: Microbiologist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Microbiologist
date_saved: 2026-05-05T03:47:58.380196+00:00
instance: kb-cron
parent: microbiologist-20260505-0
summary:
A microbiologist (from Greek μῑκρος) is a scientist who studies microscopic life forms and processes. This includes study of the growth, interactions and characteristics of microscopic organisms such as bacteria, algae, fungi, and some types of parasites and their vectors. Most microbiologists work in offices and/or research facilities, both in private biotechnology companies and in academia. Most microbiologists specialize in a given topic within microbiology such as bacteriology, parasitology, virology, or immunology. == Duties == Microbiologists generally work in some way to increase scientific knowledge or to utilise that knowledge in a way that improves outcomes in medicine or some industry. For many microbiologists, this work includes planning and conducting experimental research projects in some kind of laboratory setting. Others may have a more administrative role, supervising scientists and evaluating their results. Microbiologists working in the medical field, such as clinical microbiologists, may see patients or patient samples and do various tests to detect disease-causing organisms. For microbiologists working in academia, duties include performing research in an academic laboratory, writing grant proposals to fund research, as well as some amount of teaching and designing courses. Microbiologists in industry roles may have similar duties except research is performed in industrial labs


id: neuroscientist-20260505-0
file: data/en.wikipedia.org/wiki/Neuroscientist-0.md
category: reference
title: Neuroscientist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Neuroscientist
date_saved: 2026-05-05T03:47:59.569810+00:00
instance: kb-cron
parent: neuroscientist-20260505-0
summary:
A neuroscientist (or neurobiologist) is a scientist specializing in neuroscience that deals with the anatomy and function of neurons, neural circuits, and glia, and their behavioral, biological, and psychological roles in health and disease. Neuroscientists generally work as researchers within a college, university, government agency, or private industry setting. In research-oriented careers, neuroscientists design and conduct scientific experiments on the nervous system and its functions. They can engage in basic or applied research. Basic research seeks to expand current understanding of the nervous system, whereas applied research seeks to address a specific problem, such as developing a treatment for a neurological disorder. Neuroscientists have numerous career opportunities outside of academic research, including careers in industry, science writing, government program management, science advocacy, and education. A neuroscientist commonly holds a doctorate in a medical science. == Job overview == === Job description === Neuroscientists focus primarily on the study and research of the nervous system. The nervous system is composed of the brain, spinal cord and nerve cells. Studies of the nervous system may focus on the cellular level, as in studies of the ion channels, or instead may focus on a systemic level as in behavioural or cognitive studies. A


id: neuroscientist-20260505-1
file: data/en.wikipedia.org/wiki/Neuroscientist-1.md
category: reference
title: Neuroscientist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Neuroscientist
date_saved: 2026-05-05T03:47:59.569810+00:00
instance: kb-cron
parent: neuroscientist-20260505-0
summary:
=== Medieval European beliefs and Andreas Vesalius === Medieval beliefs generally held true the proposals of Galen, including the attribution of mental processes to specific ventricles in the brain. Functions of regions of the brain were defined based on their texture and composition: memory function was attributed to the posterior ventricle, a harder region of the brain and thus a good place for memory storage. Andreas Vesalius redirected the study of neuroscience away from the anatomical focus; he considered the attribution of functions based on location to be crude. Pushing away from the superficial proposals made by Galen and medieval beliefs, Vesalius did not believe that studying anatomy would lead to any significant advances in the understanding of thinking and the brain. == Current and developing research topics == Research in neuroscience is expanding and becoming increasingly interdisciplinary. Many current research projects involve the integration of computer programs in mapping the human nervous system. The National Institutes of Health (NIH) sponsored Human Connectome Project, launched in 2009, hopes to establish a highly detailed map of the human nervous system and its millions of connections. Detailed neural mapping could lead the way for advances in the diagnosis and treatment of neurological


id: neuroscientist-20260505-2
file: data/en.wikipedia.org/wiki/Neuroscientist-2.md
category: reference
title: Neuroscientist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Neuroscientist
date_saved: 2026-05-05T03:47:59.569810+00:00
instance: kb-cron
parent: neuroscientist-20260505-0
summary:
Camillo Golgi and Santiago Ramón y Cajal (1906) for the development of the silver staining method, revealing what would later be determined as individual neurons. Cajal's interpretations of the images produced by Golgi's staining technique led to the adoption of the neuron doctrine. Charles Sherrington and Edgar Adrian (1932) for their discoveries of the general function of neurons, including excitatory and inhibitory signals, and the all-or-nothing response of nerve fibers. Sir Henry Dale and Otto Loewi (1936) for the discovery of neurotransmitters and identification of acetylcholine. Joseph Erlanger and Herbert Gasser (1944) for discoveries illustrating the varied timing exhibited by single nerve fibers. Walter Rudolf Hess and António Caetano Egas Moniz (1949) for discovery of the functional organization of the midbrain and for the controversial therapeutic value of leucotomy respectively. Alan Hodgkin, Andrew Huxley, and Sir John Eccles (1963) for discovering the ionic basis of the action potential and macroscopic currents through their use of the squid giant axon. Sir Bernard Katz, Ulf von Euler and Julius Axelrod (1970) for the discovery of the mechanisms responsible for neurotransmitter storage, release, and inactivation. Their work included the discovery of the synaptic vesicle and quantal neurotransmitter release. Roger Guillemin and Andrew V.


id: petroleum-geologist-20260505-0
file: data/en.wikipedia.org/wiki/Petroleum_geologist-0.md
category: reference
title: Petroleum geologist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Petroleum_geologist
date_saved: 2026-05-05T03:48:02.134611+00:00
instance: kb-cron
parent: petroleum-geologist-20260505-0
summary:
A petroleum geologist is an earth scientist who works in the field of petroleum geology, which involves all aspects of the discovery and production of oil and gas. Petroleum geologists are usually linked to the actual discovery of oil and gas and the identification of possible new oil deposits or gas fields. It can be a very labor-intensive task involving several different fields of science and elaborate equipment. Petroleum geologists look at the structural and sedimentary aspects of the stratum/strata to identify possible oil traps or tight shale plays. == Profile == Petroleum geologists make the decision of where to drill for petroleum. This is done by locating prospects within a sedimentary basin. Petroleum geologists determine a prospect's viability looking at seven main aspects in conventional petroleum geology: Source: the presence of an organic-rich source rock capable of generating hydrocarbons during deep burial. Reservoir: the usually porous rock and permeable unit that collects the hydrocarbons expelled from the source rock and holds them inside a trap. Seal: the rock unit that inhibits the oil or gas from escaping from a hydrocarbon-bearing reservoir rock. Trap: structural or stratigraphic feature that captures migrating hydrocarbons into an economically producible accumulation. Timing: geologic events


id: physician-scientist-20260505-0
file: data/en.wikipedia.org/wiki/Physician-scientist-0.md
category: reference
title: Physician-scientist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Physician-scientist
date_saved: 2026-05-05T03:48:03.416125+00:00
instance: kb-cron
parent: physician-scientist-20260505-0
summary:
A physician-scientist (in North American English) or clinician-scientist (in British English and Australian English) is a physician who divides their professional time between direct clinical practice with patients and scientific research. Physician-scientists traditionally hold both a medical degree and a Doctor of Philosophy, also known as an MD-PhD or DO-PhD. Compared to other clinicians, physician-scientists invest significant time and professional effort in scientific research, with ratios of research to clinical time ranging from 50/50 to 80/20. Physician-scientists are often employed by academic or research institutions where they drive innovation across a wide range of medical specialties and may also use their extensive training to focus their clinical practices on specialized patient populations, such as those with rare genetic diseases or cancers. Although they are a minority of both practicing physicians and active research scientists, physician-scientists are often cited as playing a critical role in translational medicine and clinical research by adapting biomedical research findings to health care applications. Over time, the term physician scientist has expanded to holders of other clinical degrees—such as nurses, dentists, and veterinarians—who are also included by the United States National Institutes of Health (NIH) in its studies of the physician-scientist workforce (PSW). == History ==


id: physicist-20260505-0
file: data/en.wikipedia.org/wiki/Physicist-0.md
category: reference
title: Physicist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Physicist
date_saved: 2026-05-05T03:48:04.654230+00:00
instance: kb-cron
parent: physicist-20260505-0
summary:
A physicist is a scientist who specializes in the field of physics, which encompasses the interactions of matter and energy at all length and time scales in the physical universe. Physicists generally are interested in the root or ultimate causes of phenomena, and usually frame their understanding in mathematical terms. They work across a wide range of research fields, spanning all length scales: from sub-atomic and particle physics, through biological physics, to cosmological length scales encompassing the universe as a whole. The field generally includes two types of physicists: experimental physicists who specialize in the observation of natural phenomena and the development and analysis of experiments, and theoretical physicists who specialize in mathematical modeling of physical systems to rationalize, explain and predict natural phenomena. Physicists can apply their knowledge towards solving practical problems or to developing new technologies (also known as applied physics or engineering physics). == History == The study and practice of physics is based on an intellectual ladder of discoveries and insights from ancient times to the present. Many mathematical and physical ideas used today found their earliest expression in the work of ancient civilizations, such as the Babylonian astronomers and Egyptian engineers, the Greek philosophers of


id: physicist-20260505-1
file: data/en.wikipedia.org/wiki/Physicist-1.md
category: reference
title: Physicist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Physicist
date_saved: 2026-05-05T03:48:04.654230+00:00
instance: kb-cron
parent: physicist-20260505-0
summary:
=== United Kingdom === Chartered Physicist (CPhys) is a chartered status and a professional qualification awarded by the Institute of Physics. It is denoted by the postnominals "CPhys". Achieving chartered status in any profession denotes to the wider community a high level of specialised subject knowledge and professional competence. According to the Institute of Physics, holders of the award of the Chartered Physicist (CPhys) demonstrate the "highest standards of professionalism, up-to-date expertise, quality and safety" along with "the capacity to undertake independent practice and exercise leadership" as well as "commitment to keep pace with advancing knowledge and with the increasing expectations and requirements for which any profession must take responsibility". Chartered Physicist is considered to be equal in status to Chartered Engineer, which the IoP also awards as a member of the Engineering Council UK, and other chartered statuses in the UK. It is also considered a "regulated profession" under the European professional qualification directives. === Canada === The Canadian Association of Physicists can appoint an official designation called Professional Physicist (P. Phys.), similar to the designation of Professional Engineer (P. Eng.). This designation was unveiled at the CAP congress in 1999 and already more than 200 people carry this


id: principal-investigator-20260505-0
file: data/en.wikipedia.org/wiki/Principal_investigator-0.md
category: reference
title: Principal investigator
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Principal_investigator
date_saved: 2026-05-05T03:48:08.216521+00:00
instance: kb-cron
parent: principal-investigator-20260505-0
summary:
In many countries, the term principal investigator (PI) refers to the holder of an independent grant and the lead researcher for the grant project, usually in the sciences, such as a laboratory study or a clinical trial. The phrase is also often used as a synonym for "head of the laboratory" or "research group leader". While the expression is common in the sciences, it is used widely for the person or persons who make final decisions and supervise funding and expenditures on a given research project. A co-investigator (Co-I) assists the principal investigator in the management and leadership of the research project. There may be a number of co-investigators supporting a PI. == Federal funding == In the context of United States federal funding from agencies such as the National Institutes of Health (NIH) or the National Science Foundation (NSF), the PI is the person who takes direct responsibility for completion of a funded project, directing the research and reporting directly to the funding agency. For small projects (which might involve 1–5 people) the PI is typically the person who conceived the investigation, but for larger projects the PI may be selected by a team to obtain the best strategic


id: school-science-technician-20260505-0
file: data/en.wikipedia.org/wiki/School_science_technician-0.md
category: reference
title: School science technician
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/School_science_technician
date_saved: 2026-05-05T03:48:09.474032+00:00
instance: kb-cron
parent: school-science-technician-20260505-0
summary:
In schools, the science technician is the person who prepares the practical equipment and makes up the solutions used in school science labs. The role also includes instructing and assisting teachers with practical skills, including class demonstrations, for advanced techniques across all disciplines. Many are very well qualified and have degrees, such as a Bachelor's degree (B.A. or B.Sc), Master's degree (M.Sc.) or even a Doctorate (Dr) and/or other professional qualifications such as the HNC, HND and NVQ. Their main duties include: Care of living organisms Making up solutions School science experiments and demonstrations Inventory Budget and Accounts Repairing and constructing laboratory equipment In December 2002 CLEAPSS commissioned a survey into the Specific Job roles of Science Technicians. The pdf Document G228 - Technicians and their jobs which can be freely downloaded was released and later updated in 2009. The guide was written to help promote a professional technician service in schools and colleges. == See also == Science education == References == == External links == CLEAPSS - The School Science Advisory Service providing practical advice & help on safety in Science ASE - Professional Organisation for Teachers and Technicians


id: science-attach-20260505-0
file: data/en.wikipedia.org/wiki/Science_attaché-0.md
category: reference
title: Science attaché
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Science_attaché
date_saved: 2026-05-05T03:48:14.539947+00:00
instance: kb-cron
parent: science-attach-20260505-0
summary:
A science attaché (also known as a scientific attaché or a technical attaché) is a member of a diplomatic mission, usually an embassy. A science attaché traditionally had three primary functions: advise the ambassador on scientific and technical matters, report on scientific and technological events, and represent their country in scientific and technical matters to foreign scientific and technical academies; to industry; to intergovernmental organizations and agencies; and to international non-governmental organizations. In 1998, the National Academy of Sciences called for the appointment of more science-savvy diplomats to the State Department to improve the quality of the scientific advice available to foreign policymakers. The panel also emphasized the need to encourage general foreign service staff to acquire scientific skills. Science attachés could help scientists understand the host nation's science culture and practices. Formerly, being appointed science attaché was viewed as the "kiss of death" for advancement within the foreign service. Though the perception may change from scientific issues such as global warming, global infectious diseases, and bioterrorism to foreign policymaking and diplomacy. == Historical functions == The role of science attachés of the United States was first outlined in 1950 in a report entitled Science and Foreign Relations, issued by


id: science-technician-20260505-0
file: data/en.wikipedia.org/wiki/Science_technician-0.md
category: reference
title: Science technician
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Science_technician
date_saved: 2026-05-05T03:48:15.716321+00:00
instance: kb-cron
parent: science-technician-20260505-0
summary:
Science technician is a profession involving working as a member of support staff in any science disciplines. The Science Council defines a technician as “a person who is skilled in the use of particular techniques and procedures to solve practical problems, often in ways that require considerable ingenuity and creativity. Technicians typically work with complex instruments and equipment, and require specialised training, as well as considerable practical experience, in order to do their job effectively”. Science technicians are frequently based in laboratories, but they also perform roles in workshops, studios, the field, or in any location where scientific work is being carried out. As a group, science technicians have been referred to as "Invisible"; members of the scientific workforce whose role in the process for forming new scientific knowledge has been poorly acknowledged and insufficiently studied. However, more recently their role has been studied in some detail. == Profession == Professional training for science technicians varies between countries. In Germany, where science technicians are a subset of the "technical assistant" class of professions, state-certified technician training is a vocational training that lasts between two and three years. It allows specializations in, for instance, physics, chemistry, pharmacy, medicine and computer science,


id: scientific-glassblowing-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_glassblowing-0.md
category: reference
title: Scientific glassblowing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_glassblowing
date_saved: 2026-05-05T03:48:16.954825+00:00
instance: kb-cron
parent: scientific-glassblowing-20260505-0
summary:
Scientific glassblowing is a specialty field of lampworking used in industry, science, art and design used in research and production. Scientific glassblowing has been used in chemical, pharmaceutical, electronic and physics research including Galileo's thermometer, Thomas Edison's light bulb, and vacuum tubes used in early radio, TV and computers. More recently, the field has helped advance fiber optics, lasers, atomic and subatomic particle research, advanced communications development and semiconductors. The field combined hand skills using lathes and torches with modern computer assisted furnaces, diamond grinding and lapping machines, lasers and ultra-sonic mills. == Scientific glassblowing schools == === Degree programs === Salem Community College in Carney's Point, New Jersey offers the only degree program in the United States, an Associate in Applied Science, with a focus on the construction of scientific glass apparatus. Students come from throughout the United States and from around the world to develop this specialized skill at Salem Community College. Alfred University offers a masters program in glass science and a PhD with a blend of theoretical and applied studies similar to degree programs in materials science and engineering. === Universities offering courses === The following is the list of recognized universities that provide courses in


id: technician-20260505-0
file: data/en.wikipedia.org/wiki/Technician-0.md
category: reference
title: Technician
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Technician
date_saved: 2026-05-05T03:48:18.281630+00:00
instance: kb-cron
parent: technician-20260505-0
summary:
A technician is a worker in a field of technology who is proficient in the relevant skill and technique, with a relatively practical understanding of the theoretical principles. == Specialisation == The term technician covers many different specialisations. These include: Work safety technician Systems technician Sciences technician Data systems technician Data processing technician Information systems technician Cryptologic technician Sonar technician Engineering technician Laboratory technician Digital imaging technician Machinery Technician Machines technician Electricity technician Electronics technician Computer repair technician Automation technician Pharmacy technician Nail technician Theatrical technician Emergency Medical Technician == Campaigns == In the UK, a shortage of skilled technicians in the science, engineering and technology sectors has led to various campaigns to encourage more people to become technicians and to promote the role of technician. == See also == Career and Technical Education History of technology Technical education Grey-collar worker == References == == External links == Media related to Technicians at Wikimedia Commons


id: volcanologist-20260505-0
file: data/en.wikipedia.org/wiki/Volcanologist-0.md
category: reference
title: Volcanologist
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Volcanologist
date_saved: 2026-05-05T03:48:19.502138+00:00
instance: kb-cron
parent: volcanologist-20260505-0
summary:
A volcanologist, or volcano scientist, is a geologist who focuses on understanding the formation and eruptive activity of volcanoes. Volcanologists frequently visit volcanoes, sometimes active ones, to observe and monitor volcanic eruptions, collect eruptive products including tephra (such as ash or pumice), rock and lava samples. One major focus of inquiry in recent times is the prediction of eruptions to alleviate the impact on surrounding populations and monitor natural hazards associated with volcanic activity. Geologists who research volcanic materials that make up the solid Earth are referred to as igneous petrologists. == Etymology == The word volcanologist (or vulcanologist) is derived from the English volcanology (volcano + -logy), which was derived from the French volcanologie (or vulcanologie), which was further derived from the French word volcan (volcano), which was even further derived from Vulcanus, the Latin name of the Roman god of fire and metalworking. The Latin word is of Etruscan origin, but unknown meaning. == Job overview == === Job Description === Volcanologists research many aspects of volcanic processes to better understand planetary formation or to monitor current and future volcanic eruptions in order to protect citizens living in volcanic hazard zones. Volcanologists work at universities, museums or other


id: open-science-20260505-0
file: data/en.wikipedia.org/wiki/Open_science-0.md
category: reference
title: Open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science
date_saved: 2026-05-05T03:48:21.258734+00:00
instance: kb-cron
parent: open-science-20260505-0
summary:
Open science (also known as open research) is the movement to make scientific research, including publications, data, physical samples, software, and models, transparent and accessible to all levels of society through collaborative networks. This encompasses practices such as publishing open research, campaigning for open access, encouraging scientists to practice open-notebook science (such as openly sharing data and code), broader dissemination and public engagement in science, and generally making it easier to publish, access, and communicate scientific knowledge. Usage of the term varies substantially across disciplines, with a notable prevalence in the STEM disciplines. The term 'open research' has gained currency as a broader alternative to 'open science,' encompassing the humanities and arts alongside traditional scientific disciplines. The primary focus connecting all disciplines is the widespread uptake of new technologies and tools, and the underlying ecology of the production, dissemination and reception of knowledge from a research-based point-of-view. The term 'open scholarship' has also been proposed to include research from the arts and humanities as well as the different roles and practices that researchers perform as educators and communicators. Open science can be seen as continuing, rather than revolutionizing, practices that began in the 17th century with the academic journal, which


id: open-science-20260505-1
file: data/en.wikipedia.org/wiki/Open_science-1.md
category: reference
title: Open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science
date_saved: 2026-05-05T03:48:21.258734+00:00
instance: kb-cron
parent: open-science-20260505-0
summary:
Peer review is widely acknowledged as time-consuming. Citation impact, attributed to the authors, correlates more closely with journal circulation than with article quality. Open Science–aligned publishing formats rarely conform to traditional journal structures that calculate impact factors. Hence, this school argues that there are faster impact measurement technologies that can account for a range of publication types as well as social media web coverage of a scientific contribution to arrive at a complete evaluation of how impactful the science contribution was. The gist of the argument for this school is that hidden uses like reading, bookmarking, sharing, discussing and rating are traceable activities, and these traces can and should be used to develop a newer measure of scientific impact. The umbrella jargon for this new type of impact measurements is called altmetrics, coined in a 2011 article by Priem et al., (2011). Markedly, the authors discuss evidence that altmetrics differ from traditional webometrics which are slow and unstructured. Altmetrics are proposed to rely upon a greater set of measures that account for tweets, blogs, discussions, and bookmarks. Scholars propose that altmetrics should capture the entire research lifecycle, including collaboration patterns, to produce comprehensive impact measures. However, the authors are explicit


id: open-science-20260505-2
file: data/en.wikipedia.org/wiki/Open_science-2.md
category: reference
title: Open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science
date_saved: 2026-05-05T03:48:21.258734+00:00
instance: kb-cron
parent: open-science-20260505-0
summary:
=== Before journals === Before the advent of scientific journals, scientists had little to gain and much to lose by publicizing scientific discoveries. Many scientists, including Galileo, Kepler, Isaac Newton, Christiaan Huygens, and Robert Hooke, made claim to their discoveries by describing them in papers coded in anagrams or cyphers and then distributing the coded text. Their intent was to develop their discovery into something off which they could profit, then reveal their discovery to prove ownership when they were prepared to make a claim on it. The system of not publicizing discoveries caused problems because discoveries were not shared quickly and because it sometimes was difficult for the discoverer to prove priority. Newton and Gottfried Leibniz both claimed priority in discovering calculus. Newton said that he wrote about calculus in the 1660s and 1670s, but did not publish until 1693. Leibniz published "Nova Methodus pro Maximis et Minimis", a treatise on calculus, in 1684. Debates over priority are inherent in systems where science is not published openly, and this was problematic for scientists who wanted to benefit from priority. Under aristocratic patronage, scientists received funding to develop useful innovations or provide entertainment, creating pressure to satisfy patrons' desires and


id: open-science-20260505-3
file: data/en.wikipedia.org/wiki/Open_science-3.md
category: reference
title: Open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science
date_saved: 2026-05-05T03:48:21.258734+00:00
instance: kb-cron
parent: open-science-20260505-0
summary:
=== Internet and the free access to scientific documents === The open science movement, as presented in activist and institutional discourses at the beginning of the 21st century, refers to different ways of opening up science, especially in the Internet age. Its first pillar is free access to scientific publications. This issue entered the political landscape when the Budapest Open Access Initiative was released February 14, 2002, following a conference organized by the Open Society Institute (now Open Society Foundations) on December 1–2, 2001. The resulting declaration calls for the use of digital tools such as open archives and open access journals, free of charge for the reader. The idea of open access to scientific publications quickly became inseparable from the question of free licenses to guarantee the right to disseminate and possibly modify shared documents, such as the Creative Commons licenses, created in 2002. In 2011, a new text from the Budapest Open Initiative explicitly refers to the relevance of the CC-BY license to guarantee free dissemination and not only free access to a scientific document. Beyond publications, the open access principle has expanded to include research data — the empirical foundation of scientific studies across disciplines, as mentioned


id: open-science-20260505-4
file: data/en.wikipedia.org/wiki/Open_science-4.md
category: reference
title: Open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science
date_saved: 2026-05-05T03:48:21.258734+00:00
instance: kb-cron
parent: open-science-20260505-0
summary:
== Open Science and Research Assessment == A central aspect of the Open Science movement is the reform of research assessment. Initiatives such as the Coalition for Advancing Research Assessment (CoARA) (launched in 2022) and the San Francisco Declaration on Research Assessment (DORA) advocate moving away from traditional quantitative metrics like the Journal Impact Factor (JIF) and the h-Index, as these often exhibit biases and neglect qualitative aspects. Instead, alternative metrics and indicators, such as altmetrics and Open Science indicators, are to be given greater consideration. Open Science indicators include metrics such as the number of open access publications, data management plans, preprints, FAIR-licensed data, and open peer review reports. These approaches aim to promote the transparency and reusability of scientific outcomes, thereby enabling a fairer and more comprehensive evaluation of scientific achievements.While Open Science aims to enhance transparency, accessibility, and collaboration, the introduction of numerous new metrics to measure openness has led to unintended consequences. These metrics often rely on quantitative indicators, which conflict with the holistic and qualitative approaches advocated by initiatives such as CoARA and DORA. The core issue is that these metrics are designed not only to measure but also to influence researchers' behavior. This can


id: open-science-20260505-5
file: data/en.wikipedia.org/wiki/Open_science-5.md
category: reference
title: Open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science
date_saved: 2026-05-05T03:48:21.258734+00:00
instance: kb-cron
parent: open-science-20260505-0
summary:
=== Disadvantages === Arguments against open science tend to focus on the advantages of data ownership and concerns about the misuse of data, but see. Other concerns around data misuse involve privacy and safety risks that arise from ecological data on protected animal populations or sensitive data on human specimens that could potentially be re-identified and lead to hard and stigma for certain populations. Potential misuse Allowing open access can bring documented cases of misuse, and such misuse can take various forms from accidental errors to intentional forms of misuse like misrepresenting data in order to manipulate or deceive. In 2011, Dutch researchers announced their intention to publish a research paper in the journal Science describing the creation of a strain of H5N1 influenza which can be easily passed between ferrets, the mammals which most closely mimic the human response to the flu. The announcement triggered a controversy in both political and scientific circles about the ethical implications of publishing scientific data which could be used to create biological weapons. These events are examples of how science data could potentially be misused. It has been argued that constraining the dissemination of dual-use knowledge can in certain cases be justified because,


id: open-science-20260505-6
file: data/en.wikipedia.org/wiki/Open_science-6.md
category: reference
title: Open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science
date_saved: 2026-05-05T03:48:21.258734+00:00
instance: kb-cron
parent: open-science-20260505-0
summary:
=== Open-science projects === Different projects conduct, advocate, develop tools for, or fund open science. The Allen Institute for Brain Science conducts numerous open science projects while the Center for Open Science has projects to conduct, advocate, and create tools for open science. Other workgroups have been created in different fields, such as the Decision Analysis in R for Technologies in Health (DARTH) workgroup], which is a multi-institutional, multi-university collaborative effort by researchers who have a common goal to develop transparent and open-source solutions to decision analysis in health. Organizations have extremely diverse sizes and structures. The Open Knowledge Foundation (OKF) is a global organization sharing large data catalogs, running face to face conferences, and supporting open source software projects. In contrast, Blue Obelisk is an informal group of chemists and associated cheminformatics projects. The tableau of organizations is dynamic with some organizations becoming defunct, e.g., Science Commons, and new organizations trying to grow, e.g., the Self-Journal of Science. Common organizing forces include the knowledge domain, type of service provided, and even geography, e.g., OCSDNet's concentration on the developing world. The Allen Brain Atlas maps gene expression in human and mouse brains; the Encyclopedia of Life documents all the terrestrial


id: open-science-20260505-7
file: data/en.wikipedia.org/wiki/Open_science-7.md
category: reference
title: Open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science
date_saved: 2026-05-05T03:48:21.258734+00:00
instance: kb-cron
parent: open-science-20260505-0
summary:
F1000Research provides open publishing and open peer review for the life sciences. The Open Library of Humanities is a non-profit open access publisher for the humanities and social sciences. The Journals Library of the National Institute for Health and Care Research (NIHR) publishes all relevant documents and data from the onset of research projects, updating them alongside the progress of the study. Journal support for open-science does not conflict with preprint servers: figshare archives and shares images, readings, and other data; and Open Science Framework preprints, arXiv, and HAL Archives Ouvertes provide electronic preprints across many fields. === Software === A variety of computer resources support open science. These include software like the Open Science Framework from the Center for Open Science to manage project information, data archiving and team coordination; distributed computing services like Ibercivis to use unused CPU time for computationally intensive tasks; and services like Experiment.com to provide crowdsourced funding for research projects. Blockchain platforms for open science have been proposed. The first such platform is the Open Science Organization, which aims to solve urgent problems with fragmentation of the scientific ecosystem and difficulties of producing validated, quality science. Among the initiatives of Open Science Organization include


id: academic-spring-20260505-0
file: data/en.wikipedia.org/wiki/Academic_Spring-0.md
category: reference
title: Academic Spring
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Academic_Spring
date_saved: 2026-05-05T03:48:22.386993+00:00
instance: kb-cron
parent: academic-spring-20260505-0
summary:
The Academic Spring was the designation, inspired by the Arab Spring, used for a short time in 2012 to indicate movements by academics, researchers, and scholars opposing the restrictive copyright and circulation of traditional academic journals and promoting free access online instead. == History == There have been previous attempts to increase the availability of free and up-to-date scientific research. In 2004, there were reports in British media of a "revolution in academic publishing" which would make research freely available online but many scientists continued to publish their work in the traditional big name journals like Nature. The barriers to free access for recent scientific research became a hot topic in 2012, after a blog post by mathematician Timothy Gowers went viral in January. According to the Financial Times, the movement was named by Dennis Johnson of Melville House Publishing, though scientist Mike Taylor has suggested the name came from The Economist. === Research Works Act === In December 2011 the Research Works Act was proposed in the US Congress to restrict open access to research funded by the US federal government. This followed other similar proposed measures such as the Fair Copyright in Research Works Act. These attempts to


id: academic-torrents-20260505-0
file: data/en.wikipedia.org/wiki/Academic_Torrents-0.md
category: reference
title: Academic Torrents
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Academic_Torrents
date_saved: 2026-05-05T03:48:23.601107+00:00
instance: kb-cron
parent: academic-torrents-20260505-0
summary:
Academic Torrents is a website which enables the sharing of research data using the BitTorrent protocol. The site was founded in November 2013, and is a project of the Institute for Reproducible Research (a 501(c)3 U.S. non-profit corporation). The project is said to be similar to LOCKSS but with a focus on "offering researchers the opportunity to distribute the hosting of their papers and datasets to authors and readers, providing easy access to scholarly works and simultaneously backing them up on computers around the world." == Notable datasets == === Developing Human Connectome Project === The developing Human Connectome Project related to the Human Connectome Project uses the platform. "Researchers from three leading British institutions are using BitTorrent to share over 150 GB of unique high-resolution brain scans of unborn babies with colleagues worldwide... The researchers opted to go for the Academic Torrents tracker, which specializes in sharing research data" === CrossRef metadata === The site hosts public metadata releases from Crossref which contain over 120+ million metadata records for scholarly work, each with a DOI. This was done so to allow the community to work with the entire database programmatically instead of using their API. "The sheer number of


id: africarxiv-20260505-0
file: data/en.wikipedia.org/wiki/AfricArXiv-0.md
category: reference
title: AfricArXiv
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/AfricArXiv
date_saved: 2026-05-05T03:48:24.880840+00:00
instance: kb-cron
parent: africarxiv-20260505-0
summary:
AfricArXiv is an open-access repository for preprints of academic publications which are either about Africa or by African scientists. The platform was established in 2018. It was established to make preprint servers more available in various fields and regions. Its establishment happen during trends to provide more digital services to support science in Africa. From its founding the platform welcomed publications in any African language. In July 2020 the platform began hosting audio and video files. The Center for Open Science hosts the platform. The cost of operating the servers is significant and that organization takes a fee to cover its costs. Preprints can be submitted to AfricArXiv via ScienceOpen. Users need to have a verified ORCID digital identifier and should include in their manuscripts a short summary translation in a traditional African language. After a member of the AfricArXiv team has checked the submission for formal criteria and approved the manuscript, it will be posted with a Crossref DOI and CC BY 4.0 attribution license. == See also == List of preprint repositories == References == == Further consideration == Ahinon, Justin Sègbédji; Arafat, Hisham; Ahmad, Umar; Achampong, Joyce; Aldirdiri, Osman; Ayodele, Obasegun Tekena; Okelo, Luke; Bezuidenhout, Louise; Cary,


id: allen-brain-atlas-20260505-0
file: data/en.wikipedia.org/wiki/Allen_Brain_Atlas-0.md
category: reference
title: Allen Brain Atlas
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Allen_Brain_Atlas
date_saved: 2026-05-05T03:48:26.197389+00:00
instance: kb-cron
parent: allen-brain-atlas-20260505-0
summary:
The Allen Mouse and Human Brain Atlases are projects within the Allen Institute for Brain Science which seek to combine genomics with neuroanatomy by creating gene expression maps for the mouse and human brain. They were initiated in September 2003 with a $100 million donation from Paul G. Allen and the first atlas went public in September 2006. As of May 2012, seven brain atlases have been published: Mouse Brain Atlas, Human Brain Atlas, Developing Mouse Brain Atlas, Developing Human Brain Atlas, Mouse Connectivity Atlas, Non-Human Primate Atlas, and Mouse Spinal Cord Atlas. There are also three related projects with data banks: Glioblastoma, Mouse Diversity, and Sleep. It is the hope of the Allen Institute that their findings will help advance various fields of science, especially those surrounding the understanding of neurobiological diseases. The atlases are free and available for public use online. == History == In 2001, Paul Allen gathered a group of scientists, including James Watson and Steven Pinker, to discuss the future of neuroscience and what could be done to enhance neuroscience research (Jones 2009). During these meetings David Anderson from the California Institute of Technology proposed the idea that a three-dimensional atlas of gene expression in


id: allen-brain-atlas-20260505-1
file: data/en.wikipedia.org/wiki/Allen_Brain_Atlas-1.md
category: reference
title: Allen Brain Atlas
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Allen_Brain_Atlas
date_saved: 2026-05-05T03:48:26.197389+00:00
instance: kb-cron
parent: allen-brain-atlas-20260505-0
summary:
== Brain explorer == The Allen Brain Atlas website contains a downloadable 3-D interactive Brain explorer. The explorer is essentially a search engine for locations of gene expression; this is particularly useful in finding regions that express similar genes. Users can delineate networks and pathways using this application by connecting regions that co-express a certain gene. The explorer uses a multicolor scale and contains multiple planes of the brain that let viewers see differences in density and expression level. The images are a composite of many averaged samples so it is useful when comparing to individuals with abnormally low gene expression. == Atlases == === Mouse Brain === The Allen Mouse Brain Atlas is a comprehensive genome-wide map of the adult mouse brain that reveals where each gene is expressed. The mouse brain atlas was the original project of the Allen Brain Atlas and was finished in 2006. The purpose of the atlas is to aid in the development of neuroscience research. The hope of the project is that it will allow scientists to gain a better understanding of brain diseases and disorders such as autism and depression. === Human Brain === The Allen Human Brain Atlas was made public


id: allen-institute-for-brain-science-20260505-0
file: data/en.wikipedia.org/wiki/Allen_Institute_for_Brain_Science-0.md
category: reference
title: Allen Institute for Brain Science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Allen_Institute_for_Brain_Science
date_saved: 2026-05-05T03:48:31.360974+00:00
instance: kb-cron
parent: allen-institute-for-brain-science-20260505-0
summary:
The Allen Institute for Brain Science is a division of the Allen Institute, based in Seattle, Washington, that focuses on bioscience research. Founded in 2003, it is dedicated to accelerating the understanding of how the human brain works. With the intent of catalyzing brain research in different areas, the Allen Institute provides free data and tools to scientists. Started with $100 million in seed money from Microsoft co-founder and philanthropist Paul Allen in 2003, the institute tackles projects at the leading edge of science—far-reaching projects at the intersection of biology and technology. The resulting data create free, publicly available resources that fuel discovery for countless researchers. Hongkui Zeng is the current director of the institute. == History and funding == The Allen Institute for Brain Science is a scientific division of the Allen Institute, a nonprofit research organization that also includes the Allen Institute for Cell Science, launched in 2014. The Paul G. Allen Frontiers Group was launched in 2016 while the Allen Institute for Immunology was launched in 2018. All four divisions of the Allen Institute are housed in the same building in Seattle's South Lake Union neighborhood. The institute employs a business model that combines the operational agility


id: allen-institute-for-brain-science-20260505-1
file: data/en.wikipedia.org/wiki/Allen_Institute_for_Brain_Science-1.md
category: reference
title: Allen Institute for Brain Science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Allen_Institute_for_Brain_Science
date_saved: 2026-05-05T03:48:31.360974+00:00
instance: kb-cron
parent: allen-institute-for-brain-science-20260505-0
summary:
=== Allen Brain Observatory === The Allen Brain Observatory was launched in 2016 to capture cellular-level activity of neurons in the mouse visual cortex. Experiments through the observatory use visual or electrical readouts of neural activity as animals see visual stimuli, ranging from natural images to black and white grid lines to a clip from the Orson Welles film noir, Touch of Evil. In 2018, the institute opened the observatory for research projects proposed by scientists from the broader community through a program called OpenScope, which was modeled after large-scale shared physics observatories such as the Hubble Space Telescope. === Other online resources === In addition to the atlas resources, the Allen Institute has generated several other online research tools, including: The Ivy Glioblastoma Atlas Project (Ivy GAP), a platform for exploring the anatomic and genetic basis of glioblastoma at the cellular and molecular levels. The BrainSpan Atlas of the Developing Human Brain, a resource for studying human brain development developed by a consortium of scientific partners and funded by awards from the National Institutes of Health. == Awards == Forbes – 30 Under 30 Rising Stars Transforming Science and Health to Allen Institute scientist Adrian Cheng (2012) Cajal Club


id: amsterdam-call-for-action-on-open-science-20260505-0
file: data/en.wikipedia.org/wiki/Amsterdam_Call_for_Action_on_Open_Science-0.md
category: reference
title: Amsterdam Call for Action on Open Science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Amsterdam_Call_for_Action_on_Open_Science
date_saved: 2026-05-05T03:48:33.684910+00:00
instance: kb-cron
parent: amsterdam-call-for-action-on-open-science-20260505-0
summary:
The Amsterdam Call for Action on Open Science is a document that advocates for "full open access for all scientific publications", and endorses an environment where "data sharing and stewardship is the default approach for all publicly funded research". == History == The Amsterdam Call for Action on Open Science was first produced as a draft at an Open Science meeting that was organized by the Dutch Presidency of the Council of the European Union on April 4 and 5, 2016, in Amsterdam. The draft presented to meeting participants in the morning of the 5th had twelve actions. These were commented on by participants, split up in various parallel sessions, and refined during the afternoon. The edits were not completed during the meeting and unlike the meeting schedule suggested, the Call text was not released on the 5th. Nevertheless, the draft was symbolically presented to Sander Dekker and the Dutch Presidency. On April 6, the updated version was released for public commenting on a wiki. In a mail which participants received it was stated that comments could be placed until 14 April. The finalised Call for Action was input to the Competitiveness Council on 27 May, led by the Dutch


id: arxiv-20260505-0
file: data/en.wikipedia.org/wiki/ArXiv-0.md
category: reference
title: ArXiv
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/ArXiv
date_saved: 2026-05-05T03:48:34.832856+00:00
instance: kb-cron
parent: arxiv-20260505-0
summary:
arXiv (pronounced as "archive"—the X represents the Greek letter chi ⟨χ⟩) is an open-access repository of electronic preprints and postprints (known as e-prints) approved for posting after moderation, but not peer reviewed. It consists of scientific papers in the fields of mathematics, physics, astronomy, electrical engineering, computer science, quantitative biology, statistics, mathematical finance, and economics, which can be accessed online. In many fields of mathematics and physics, almost all scientific papers are self-archived on the arXiv repository before publication in a peer-reviewed journal. Some publishers also grant permission for authors to archive the peer-reviewed postprint. Begun on August 14, 1991, arxiv.org passed the half-million-article milestone on October 3, 2008. By the end of 2014, it had surpassed one million articles, and it reached two million by the end of 2021. As of November 2024, the submission rate is about 24,000 articles per month. == History == arXiv was made possible by the compact TeX file format, which allowed scientific papers to be easily transmitted over the Internet and rendered client-side. Around 1990, Joanne Cohn began emailing physics preprints to colleagues as TeX files, but the number of papers being sent soon filled mailboxes to capacity. Paul Ginsparg recognized the need


id: arxiv-20260505-1
file: data/en.wikipedia.org/wiki/ArXiv-1.md
category: reference
title: ArXiv
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/ArXiv
date_saved: 2026-05-05T03:48:34.832856+00:00
instance: kb-cron
parent: arxiv-20260505-0
summary:
== Moderation process and endorsement == Although arXiv is not peer reviewed, a collection of moderators for each area review the submissions; they may recategorize any that are deemed off-topic, or reject submissions that are not scientific papers, or sometimes for undisclosed reasons. The lists of moderators for many sections of arXiv are publicly available, but moderators for most of the physics sections remain unlisted. In addition to human moderators, all submissions are checked via an automated quality control process, ensuring a baseline standard of professionalism. Additionally, an "endorsement" system was introduced in 2004 as part of an effort to ensure content is relevant and of interest to current research in the specified disciplines. Under the system, for categories that use it, an author must be endorsed by an established arXiv author before being allowed to submit papers to those categories. Endorsers are not asked to review the paper for errors but to check whether the paper is appropriate for the intended subject area. New authors from recognized academic institutions generally receive automatic endorsement, which in practice means that they do not need to deal with the endorsement system at all. However, the endorsement system has attracted criticism for allegedly


id: berkeley-initiative-for-transparency-in-the-social-sciences-20260505-0
file: data/en.wikipedia.org/wiki/Berkeley_Initiative_for_Transparency_in_the_Social_Sciences-0.md
category: reference
title: Berkeley Initiative for Transparency in the Social Sciences
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Berkeley_Initiative_for_Transparency_in_the_Social_Sciences
date_saved: 2026-05-05T03:48:35.991923+00:00
instance: kb-cron
parent: berkeley-initiative-for-transparency-in-the-social-sciences-20260505-0
summary:
The Berkeley Initiative for Transparency in the Social Sciences, abbreviated BITSS, is an academic initiative dedicated to advancing transparency, reproducibility, and openness in social science research. It was established in 2012 by the University of California, Berkeley's Center for Effective Global Action. It has worked with the Center for Open Science to define and promote a set of best practices for social scientists to maximize transparency in their research. BITSS has also worked to promote registered reports, supporting journals like the Journal of Development Economics in taking up the review track. In 2015, BITSS began awarding the annual Leamer-Rosenthal Prizes for Open Social Science to honor outstanding achievements and emerging leaders in promoting transparency in social science. Through its Catalyst program, the initiative also supports and empowers over 150 graduate students, faculty, librarians, and early career researchers to advance open science all over the world. Their annual Research Transparency and Reproducibility Training (RT2) provides an overview of and hands-on practice with tools and practices for transparent and reproducible social science research. Their Massive Open Online Course "Transparent and Open Social Science Research,” based on a UC Berkeley course taught by Edward Miguel, is available on the FutureLearn platform. In 2019,


id: bgee-20260505-0
file: data/en.wikipedia.org/wiki/Bgee-0.md
category: reference
title: Bgee
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Bgee
date_saved: 2026-05-05T03:48:37.217309+00:00
instance: kb-cron
parent: bgee-20260505-0
summary:
Bgee is a database maintained by the SIB Swiss Institute of Bioinformatics and the University of Lausanne for retrieval and comparison of gene expression patterns from RNA-Seq, scRNA-Seq, Microarray, In situ hybridization and EST studies, across multiple animal species. Bgee provides an intuitive answer to the question where is a gene expressed? and supports research in cancer and agriculture, as well as evolutionary biology. Bgee is based exclusively on curated, healthy wild-type, expression data (i.e., no gene knock-out, no treatment, no disease), to provide a comparable reference of healthy wild-type gene expression. Bgee produces calls of presence/absence of expression, and of differential over-/under-expression, integrated along with information of gene orthology, and of homology between organs. This allows comparisons of expression patterns between species. Bgee allows searches by gene, organ / tissue / cell type and developmental stage. Bgee is a part of Global Core Biodata Resources (GCBRs) and ELIXIR Core Data Resources representing "critical components for ensuring the reproducibility and integrity of life sciences research." Bgee is also an ELIXIR Recommended Interoperability Resources that facilitate the FAIR-supporting activities in scientific research. == References == == Further reading == == External links == "Bgee is a new ELIXIR Recommended Interoperability Resources".


id: binder-project-20260505-0
file: data/en.wikipedia.org/wiki/Binder_Project-0.md
category: reference
title: Binder Project
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Binder_Project
date_saved: 2026-05-05T03:48:38.365166+00:00
instance: kb-cron
parent: binder-project-20260505-0
summary:
The Binder Project is a software project to package and share interactive, reproducible environments. A Binder or "Binder-ready repository" is a code repository that contains both code and content to run, and configuration files for the environment needed to run it. Since 2017, when the Binder Project was merged into the JupyterHub project, the development communities share many people in common. A common use of Binder is for sharing a Jupyter notebook in a way that the recipient can immediately execute in a browser. The Binder project maintains core libraries and documentation for running Binder services, which make those projects available, as well as BinderHub, a tool for deploying such services via common cloud computing environments. A public BinderHub portal is hosted by the community at mybinder.org. == BinderHub == A BinderHub lets you launch a publicly executable version of a Binder repository. Given a URL to a repository, it generates a new URL that anyone can visit in a browser to interact with a running version of the code in that repository. The public BinderHub, mybinder.org, load-balances Binder instances across a federation of contributing institutions, each of which is running its own BinderHub instance. == See also == Project


id: bioinformatics-research-network-20260505-0
file: data/en.wikipedia.org/wiki/Bioinformatics_Research_Network-0.md
category: reference
title: Bioinformatics Research Network
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Bioinformatics_Research_Network
date_saved: 2026-05-05T03:48:39.667934+00:00
instance: kb-cron
parent: bioinformatics-research-network-20260505-0
summary:
Bioinformatics Research Network (BRN) is a non-profit open-science research-based organization aiming to provide volunteer opportunities and bioinformatics research training that is free and open to everyone. It is a community-driven 501(c)(3) non-profit organization that aims to establish a worldwide network that is open to anyone interested in bioinformatics irrespective of academic background and to provide bioinformatics training, mentorship and the opportunity to collaborate on exciting research projects. == Training and projects == BRN provides free training workshops through its partner group Bioinformatics Interest Group. BIG is a student club of The University of Texas Health Science Center at San Antonio established to promote the development of student bioinformaticians and encourage the growth of bioinformatics skills in the community. BRN is open to academic labs to host projects for open collaboration. These projects are then available for everyone to contribute. To work on a project, a volunteer has to complete the required skill assessments for the specific project and apply to the respected team. The decision to allow the volunteer to work depends on the team of the respective project. == Publication == BRN has published its projects in BioRxiv and in peer-reviewed journals. == References == == External links ==


id: blue-obelisk-20260505-0
file: data/en.wikipedia.org/wiki/Blue_Obelisk-0.md
category: reference
title: Blue Obelisk
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Blue_Obelisk
date_saved: 2026-05-05T03:48:40.823971+00:00
instance: kb-cron
parent: blue-obelisk-20260505-0
summary:
Blue Obelisk is an informal group of chemists who promote open data, open source, and open standards; it was initiated by Peter Murray-Rust and others in 2005. Multiple open source cheminformatics projects associate themselves with the Blue Obelisk, among which, in alphabetical order, Avogadro, Bioclipse, cclib, Chemistry Development Kit, GaussSum, JChemPaint, JOELib, Kalzium, Openbabel, OpenSMILES, and UsefulChem. The project has handed out personal awards for achievements in promoting Open Data, Open Source and Open Standards. Among those who received a Blue Obelisk Award are: Christoph Steinbeck (2006) Geoff Hutchinson (2006) Bob Hanson (2006), Egon Willighagen (2007) Jean-Claude Bradley (2007) Ola Spjuth (2007) Noel O'Boyle (2010) Rajarshi Guha (2010) Cameron Neylon (2010) Alex Wade (2010) Nina Jeliazkova (2010) Henry Rzepa (2011) Dan Zaharevitz (2011) Sam Adams (2011) Jens Thomas (2011) Marcus Hanwell (2011) Roger Sayle (2011) the Environmental Molecular Sciences Laboratory (2012) Saulius Gražulis (2014) Antony Williams (2014) Daniel Lowe (2014) Andrew Lang (2014) Matthew H. Todd (2014) Greg Landrum (2016) Mark Forster (2016) John Mayfield (2017) == See also == Cheminformatics == References == == External links == Official website Twitter account


id: jean-claude-bradley-20260505-0
file: data/en.wikipedia.org/wiki/Jean-Claude_Bradley-0.md
category: reference
title: Jean-Claude Bradley
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Jean-Claude_Bradley
date_saved: 2026-05-05T03:48:42.050146+00:00
instance: kb-cron
parent: jean-claude-bradley-20260505-0
summary:
Jean-Claude Bradley was a chemist who actively promoted Open Science in chemistry, including at the White House, for which he was awarded the Blue Obelisk award in 2007. He coined the term "Open Notebook science". He died in May 2014. A memorial symposium was held July 14, 2014 at Cambridge University, UK. One outcome of his Open Notebook work is the collection of physicochemical properties of organic compounds he was studying. All of this data he made available as Open data under the CCZero license. For example, in 2009 Bradley et al. published their work on making solubility data of organic compounds available as Open data. Later, the melting point data set he collaborated on with Andrew Lang and Antony Williams was published with Figshare. Both data sets were also made available as books via the Lulu.com self-publishing platform. He blogged extensively and contributed to at least 25 individual blogs. In an interview in 2008 with Bora Zivkovic titled "Doing Science Publicly", he spoke of his work and online presence. In 2010, he gave an extensive interview about the impact of Open Notebook science with Richard Poynder. == References == == External links == Jean-Claude Bradley's Google Scholar Citations Page


id: center-for-open-science-20260505-0
file: data/en.wikipedia.org/wiki/Center_for_Open_Science-0.md
category: reference
title: Center for Open Science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Center_for_Open_Science
date_saved: 2026-05-05T03:48:47.375901+00:00
instance: kb-cron
parent: center-for-open-science-20260505-0
summary:
The Center for Open Science is a non-profit technology organization based in Charlottesville, Virginia with a mission to "increase the openness, integrity, and reproducibility of scientific research." Brian Nosek and Jeffrey Spies founded the organization in January 2013, funded mainly by the Laura and John Arnold Foundation and others. The organization began with work in reproducibility of psychology research, with the large-scale initiative Reproducibility Project: Psychology. A second reproducibility project for cancer biology research has also been started through a partnership with Science Exchange. In March 2017, the Center published a detailed strategic plan. Brian Nosek posted a letter outlining the history of the Center and future directions. In 2020, the Center received a grant from Fast Grants to promote the publication of COVID-19 research on the platform. In 2021, the Center for Open Science was honored with the Einstein Foundation Award for Promoting Quality in Research in the institutional category for their contribution to fostering research integrity and to improving transparency and accessibility. == Open Science Framework == === Reproducibility project === The Open Science Framework (OSF) is an open source software project that facilitates open collaboration in science research. The framework was initially used to work on a


id: consortia-advancing-standards-in-research-administration-information-20260505-0
category: reference
title: Consortia Advancing Standards in Research Administration Information
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Consortia_Advancing_Standards_in_Research_Administration_Information
date_saved: 2026-05-05T03:48:50.096933+00:00
instance: kb-cron
parent: consortia-advancing-standards-in-research-administration-information-20260505-0
file:
data/en.wikipedia.org/wiki/Consortia_Advancing_Standards_in_Research_Administration_Information-0.md

summary:
The Consortia Advancing Standards in Research Administration Information (CASRAI), also known as CASRAI, is an active international non-profit organization that focuses on reducing administrative burdens and improving reporting outcomes in research through standardization of information management. The organization is currently operated by a committee of The Health Initiative, a 501(c)(3) organization, with administrative operations coordinated through Hospital.org.uk and Pango.Network. Its members include universities, colleges, teaching hospitals, and other research institutions worldwide. While maintaining its presence in Fairfax, Virginia, United States, the organization has expanded its operations internationally with partial sponsorship from the University of Oxford and University of Edinburgh. == Overview == CASRAI develops and maintains standard information agreements, which define the necessary data elements for key business processes in the research lifecycle and provide definitions for related terms. These standardized infrastructures developed by CASRAI can be integrated into local software systems and processes to facilitate consistent and comparable sharing of research information across the lifecycle. The standards are available in an online dictionary, facilitating the exchange of information in consistent formats, such as CERIF-XML. As of 2025, CASRAI hosts over 200 million DOIs and provides researchers with the capability to claim their contributions using the Credit taxonomy system. These


id: the-cost-of-knowledge-20260505-0
file: data/en.wikipedia.org/wiki/The_Cost_of_Knowledge-0.md
category: reference
title: The Cost of Knowledge
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/The_Cost_of_Knowledge
date_saved: 2026-05-05T03:48:51.315386+00:00
instance: kb-cron
parent: the-cost-of-knowledge-20260505-0
summary:
The Cost of Knowledge is a protest by academics against the business practices of academic journal publisher Elsevier. Among the reasons for the protests were a call for lower prices for journals and to promote increased open access to information. The main work of the project was to ask researchers to sign a statement committing not to support Elsevier journals by publishing, performing peer review, or providing editorial services for these journals. == History == Before the advent of the Internet, it was difficult for scholars to distribute articles giving their research results. Historically, publishers performed services including proofreading, typesetting, copyediting, printing, and worldwide distribution. In more recent times, all researchers became expected to give the publishers digital copies of their work which needed no further processing – in other words, the modern academic is expected to do, often for free, duties traditionally assigned to the publisher, and for which, traditionally, the publisher is paid in exchange. For digital distribution, printing is unnecessary, copying is (almost) free, and worldwide distribution happens online instantly. Internet technology, and with it the aforementioned significant decrease in overhead costs, enabled the four major scientific publishers – Elsevier, Springer, Wiley, and Informa – to cut


id: the-cost-of-knowledge-20260505-1
file: data/en.wikipedia.org/wiki/The_Cost_of_Knowledge-1.md
category: reference
title: The Cost of Knowledge
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/The_Cost_of_Knowledge
date_saved: 2026-05-05T03:48:51.315386+00:00
instance: kb-cron
parent: the-cost-of-knowledge-20260505-0
summary:
=== Impact and reception === In February 2012, analysts of the Exane Paribas bank reported a financial impact on Elsevier with the company's stock prices falling due to the boycott. Dennis Snower criticised the monopoly of scientific publishers, but said at the same time that he did not support the boycott even though he himself is the editor-in-chief of an open-access journal on economics. He thinks that more competition among the various journals should instead be encouraged. The Senate of the University of Kansas has been reported to consider joining the boycott of Elsevier. In allusion to the revolutions of the Arab Spring, the German Frankfurter Allgemeine Zeitung daily newspaper called the movement the "Academic Spring" (German: Akademischer Frühling). When the British Wellcome Trust made a commitment to open up science, The Guardian similarly called this the "Academic Spring". After the Wellcome Trust announcement, The Cost of Knowledge campaign was recognized by that newspaper as the start of something new. A 2016 study evaluating the boycott stated that in the past four years 38% of signatories had abandoned their "won't publish in an Elsevier outlet" commitment and that only around 5000 researchers were still clearly boycotting Elsevier by publishing elsewhere.


id: covid-moonshot-20260505-0
file: data/en.wikipedia.org/wiki/COVID_Moonshot-0.md
category: reference
title: COVID Moonshot
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/COVID_Moonshot
date_saved: 2026-05-05T03:48:52.653806+00:00
instance: kb-cron
parent: covid-moonshot-20260505-0
summary:
The COVID Moonshot is a collaborative open-science project started in March 2020 with the goal of developing an un-patented oral antiviral drug to treat SARS-CoV-2, the virus causing COVID-19. COVID Moonshot researchers are targeting the proteins needed to form functioning new viral proteins. They are particularly interested in proteases such as 3C-like protease (Mpro), a coronavirus nonstructural protein that mediates the breaking and replication of proteins. COVID Moonshot may be the first open-science community effort for the development of an antiviral drug. Hundreds of scientists around the world, from academic and industrial organizations, have shared their expertise, resources, data, and results to more rapidly identify, screen, and test candidate compounds for the treatment of COVID-19. == Project history == Development of antiviral drugs is a complicated and time-consuming multistage process. The public sharing of information in the early stages of genome identification and protein structure identification has accelerated the process of searching for COVID-19 treatments and established a basis for the COVID Moonshot initiative. === Genome identification === On January 3, 2020, Chinese virologist Yong-Zhen Zhang of Fudan University and the Shanghai Public Health Clinical Center received a test sample from Wuhan, China, where patients had a pneumonia-like illness. By


id: covid-moonshot-20260505-1
file: data/en.wikipedia.org/wiki/COVID_Moonshot-1.md
category: reference
title: COVID Moonshot
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/COVID_Moonshot
date_saved: 2026-05-05T03:48:52.653806+00:00
instance: kb-cron
parent: covid-moonshot-20260505-0
summary:
The design submissions were stored in Collaborative Drug Discovery's CDD Vault, a database used for large-scale management of chemical structures, experimental protocols and experimental results. Alpha Lee and Matt Robinson brought computational expertise from PostEra to the project. PostEra used techniques from artificial intelligence and machine learning to develop analysis tools for computational drug discovery, chemical synthesis and biochemical assays. When COVID Moonshot's appeal resulted in not hundreds but thousands of responses, they built a platform capable of triaging large numbers of compounds and designing routes for their synthetic formation. Supercomputer access was provided through the COVID-19 High Performance Computing (HPC) Consortium, accelerating the speed at which designs could be examined and compared. The distributed supercomputing initiative Folding@home has carried out multiple sprints to model novel protein structures and target desirable structures as a part of COVID Moonshot. Many of the criteria for selecting drug candidates were determined by the group's goals. An ideal drug candidate would be effective in treating COVID-19. It also would be easily and cheaply made, so that as many countries and companies as possible could produce and distribute it. The ingredients to make it should be easy to obtain, and the processes involved should be


id: creative-commons-20260505-0
file: data/en.wikipedia.org/wiki/Creative_Commons-0.md
category: reference
title: Creative Commons
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Creative_Commons
date_saved: 2026-05-05T03:48:53.809037+00:00
instance: kb-cron
parent: creative-commons-20260505-0
summary:
Creative Commons (CC) is an American nonprofit organization and international network devoted to educational access and expanding the range of creative works available for others to build upon legally and to share. The organization has released several copyright licenses, known as Creative Commons licenses, free of charge to the public, to allow authors of creative works to communicate which rights they reserve and which rights they waive for the benefit of recipients or other creators. Content owners still maintain their copyright, but Creative Commons licenses give standard releases that replace the individual negotiations for specific rights between copyright owner (licensor) and licensee, that are necessary under an "all rights reserved" copyright management. As of 2019, there were "nearly 2 billion" works licensed under the various Creative Commons licenses. Wikipedia and its sister projects use one of these licenses. According to a 2017 report, Flickr alone hosted over 415 million cc-licensed photos, along with around 49 million works in YouTube, 40 million works in DeviantArt and 37 million works in Wikimedia Commons. The licenses are also used by Stack Exchange, MDN, Internet Archive, Khan Academy, LibreTexts, OpenStax, MIT OpenCourseWare, WikiHow, TED, OpenStreetMap, GeoGebra, Doubtnut, Fandom, Arduino, ccmixter.org, and Ninjam, among others,


id: creative-commons-20260505-1
file: data/en.wikipedia.org/wiki/Creative_Commons-1.md
category: reference
title: Creative Commons
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Creative_Commons
date_saved: 2026-05-05T03:48:53.809037+00:00
instance: kb-cron
parent: creative-commons-20260505-0
summary:
=== Bassel Khartabil === Bassel Khartabil was a Palestinian Syrian open source software developer who served as a project lead and public affiliate for Creative Commons Syria. On March 15, 2012, he was detained by the Syrian government in Damascus at Adra Prison for no crime. On October 17, 2015, the Creative Commons Board of Directors passed a resolution calling for Bassel Khartabil's release. In 2017, Bassel's wife received confirmation that Bassel had been killed shortly after she lost contact with him in 2015. == Evolution of CC licenses == All current CC licenses (except the CC0 Public Domain Dedication tool) require attribution (attributing the authors of the original creative works), which can be inconvenient for works based on multiple other works. Critics feared that Creative Commons could erode the copyright system over time, or allow "some of our most precious resources – the creativity of individuals – to be simply tossed into the commons to be exploited by whomever has spare time and a magic marker." Critics also worried that the lack of rewards for content producers would dissuade artists from publishing their work, and questioned whether Creative Commons would enable the commons that it aimed to create. Creative


id: creative-commons-20260505-2
file: data/en.wikipedia.org/wiki/Creative_Commons-2.md
category: reference
title: Creative Commons
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Creative_Commons
date_saved: 2026-05-05T03:48:53.809037+00:00
instance: kb-cron
parent: creative-commons-20260505-0
summary:
Various commentators have reported confusion in understanding what "noncommercial" use means. Creative Commons issued a report in 2009, "Defining noncommercial", which presented research and various perspectives. The report claimed that noncommercial to many people means "no exchange of money or any commerce". Beyond that simple statement, many people disagree on whether noncommercial use permits publishing on websites supported with advertising, sharing noncommercial media through nonprofit publishing for a fee, and many other practices in contemporary media distribution. Creative Commons has not sought to resolve the confusion, in part because of high consumer demand for the noncommercial license as is with its ambiguity. === Personality rights === In 2007, Virgin Mobile Australia launched a bus stop advertising campaign which promoted its mobile phone text messaging service using the work of amateur photographers who uploaded their work to the photo-sharing site Flickr using a Creative Commons by Attribution license. Users licensing their images this way freed their work for use by any other entity, as long as the original creator was attributed credit, without any other compensation being required. Virgin upheld this single restriction by printing a URL, leading to the photographer's Flickr page, on each of their ads. However, one picture


id: creative-commons-india-20260505-0
file: data/en.wikipedia.org/wiki/Creative_Commons_India-0.md
category: reference
title: Creative Commons India
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Creative_Commons_India
date_saved: 2026-05-05T03:48:55.071847+00:00
instance: kb-cron
parent: creative-commons-india-20260505-0
summary:
Creative Commons India Chapter is the country-level Chapter of Creative Commons in India. It organises online and offline events on various aspects related to open content, Open Educational Resources, Creative Commons licensed publishing and the use of Open Access textbooks in schools. == History == CC India Chapter was set up under its current team on September 1, 2018. Its Chapter Lead is Savithri Singh. Subhashish Panigrahi is representative to the Global Network Council. Earlier, the India Chapter was relaunched in 2013. It was originally launched in India in 2007, and by 2013, the Creative Commons had been tailor-made for India law. Wikimedia India, the Acharya Narendra Dev College, and the Centre for Internet and Society (India) were the key organisations were the key part of the Chapter with a focus respectively on outreach, open educational research, and legal support. The CC India network was initially housed at IIT Bombay. Its goals have included "raising awareness on licenses and open education resources, connecting with photography communities, content donation and participating in affiliate network." == Initiatives == Among the initiatives taken up in India on the Creative Commons front are: In 2019, the Indian State of Odisha (earlier Orissa), announced that


id: data-collaboratives-20260505-0
file: data/en.wikipedia.org/wiki/Data_collaboratives-0.md
category: reference
title: Data collaboratives
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Data_collaboratives
date_saved: 2026-05-05T03:48:56.315156+00:00
instance: kb-cron
parent: data-collaboratives-20260505-0
summary:
Data collaboratives (sometimes called "corporate data philanthropy") are a form of collaboration in which participants from different sectors—including private companies, research institutions, and government agencies—can exchange data and data expertise to help solve public problems. == Types == Data collaboratives can take many forms. They can be organized as: Public Interfaces: Private firms publish select data assets to be public for use by external parties. Firms typically present this information as Application Programming Interfaces (APIs) or data platforms. Trusted Intermediary: Private sector firms share data with partners from public, civil society actors, and academia. Data can be brokered by third parties, who provide valuable data under fixed terms and time limits to non-private organizations. It can also be run through third-party analytics, which shares data with data stewards to run analysis and share those findings with external actors, providing the outcomes of the data without exposing the sensitive information. Data Pooling: Multi-sectoral stakeholders join "data pools" to share data resources. Public data pools allow partners to openly access and independently use the data, while private data pools limit access and contribution to the information. Research and Analysis Partnership: Organizations share data and "proprietary data assets" with public and academic institutions


id: data-collaboratives-20260505-1
file: data/en.wikipedia.org/wiki/Data_collaboratives-1.md
category: reference
title: Data collaboratives
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Data_collaboratives
date_saved: 2026-05-05T03:48:56.315156+00:00
instance: kb-cron
parent: data-collaboratives-20260505-0
summary:
AI4BetterHearts: A global data cooperative established by the Novartis Foundation and Microsoft to improve cardiovascular health with the aim of using AI and data analytics to tackle heart disease. The Chicago Data Collaborative: An effort by newsrooms, academics, and non-profit organizations to source data from public agencies, organize and document the data, and link it for a better and comprehensive understanding of the criminal justice system. The Counter Trafficking Data Collaborative: A data collaborative working to curb human trafficking through data contributed by various countries and is maintained by the International Organization for Migration (IOM) and Polaris. CubeIQ: An offline intelligence and measurement company helping marketers understand the true impact of their cross-channel advertising in the offline world. Their "Data For Good" program provides access to anonymous, privacy-compliant location data for academic research and humanitarian initiatives related to human mobility. Data Collaborative for Justice: A project at the John Jay College that leverages community data to research the operations of the criminal justice system and create informed and transparent frameworks for criminal justice reform. The Health Data Collaborative: A multi-agency, multilateral effort active in five African countries that provides a collaborative platform to leverage technical and financial resources at all


id: data-publishing-20260505-0
file: data/en.wikipedia.org/wiki/Data_publishing-0.md
category: reference
title: Data publishing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Data_publishing
date_saved: 2026-05-05T03:48:57.716301+00:00
instance: kb-cron
parent: data-publishing-20260505-0
summary:
Data publishing (also data publication) is the act of releasing research data in published form for use by others. It is a practice consisting in preparing certain data or data set(s) for public use thus to make them available to everyone to use as they wish. This practice is an integral part of the open science movement. There is a large and multidisciplinary consensus on the benefits resulting from this practice. The main goal is to elevate data to be first class research outputs. There are a number of initiatives underway as well as points of consensus and issues still in contention. There are several distinct ways to make research data available, including: publishing data as supplemental material associated with a research article, typically with the data files hosted by the publisher of the article hosting data on a publicly available website, with files available for download hosting data in a repository that has been developed to support data publication, e.g. figshare, Dryad, Dataverse, Zenodo. A large number of general and specialty (such as by research topic) data repositories exist. For example, the UK Data Service enables users to deposit data collections and re-share these for research purposes. publishing a


id: dataverse-20260505-0
file: data/en.wikipedia.org/wiki/Dataverse-0.md
category: reference
title: Dataverse
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Dataverse
date_saved: 2026-05-05T03:49:03.930930+00:00
instance: kb-cron
parent: dataverse-20260505-0
summary:
The Dataverse is an open source web application to share, preserve, cite, explore and analyze research data. Researchers, data authors, publishers, data distributors, and affiliated institutions all receive appropriate credit via a data citation with a persistent identifier (e.g., DOI, or handle). A Dataverse repository hosts multiple dataverses. Each dataverse contains dataset(s) or other dataverses, and each dataset contains descriptive metadata and data files (including documentation and code that accompany the data). In 2019, Dataverse won the Duke's Choice Award for university and higher education. == Background == The Dataverse Project is housed and developed by the Dataverse Team at the Institute for Quantitative Social Science (IQSS) at Harvard University. Coding of the Dataverse (previously known as Dataverse Network) software began in 2006 under the leadership of Mercè Crosas and Gary King. The earlier Virtual Data Center (VDC) project, which spanned 1999-2006, was organized by Micah Altman, Gary King, and Sidney Verba as a collaboration between the Harvard-MIT Data Center (now part of IQSS) and the Harvard University Library. Precursors to the VDC date to 1987, comprising such entities as a stand-alone software guide to local data, preweb software, and tools to transfer cataloging information by FTP to other sites


id: economics-of-open-science-20260505-0
file: data/en.wikipedia.org/wiki/Economics_of_open_science-0.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T03:49:05.253185+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
The economics of open science describe the economic aspects of making a wide range of scientific outputs (e.g., publications, data, software) to all levels of society. Open science involves a plurality of economic models and goods. Historically, academic journals and other academic institutions, such as learned societies, have favored a knowledge club or a toll access model: publications are managed as a community service for the selected benefit of academic readers and authors. During the second half of the 20th century, the "big 5" largest publishers (Elsevier, Springer, Wiley, Taylor & Francis, and the American Chemical Society) have partly absorbed or outcompeted non-profits structure and applied an industrial approach to scholarly publishing. The development of the web shifted the focus of scholarly communication from publication to a large variety of outputs (data, software, metrics). It also challenged the values and the organization of existing actors with the development of an international initiatives in favor of open access and open science. While initially distanced by new competitors, the main commercial publishers have started to flip to author-pay models after 2000, funded through article processing charges and the negotiation of transformative deals. Actors like Elsevier or Wiley have diversified their activities from


id: economics-of-open-science-20260505-1
file: data/en.wikipedia.org/wiki/Economics_of_open_science-1.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T03:49:05.253185+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
=== Open science club === The economic theory of club goods was originally developed in the 1965 by James Buchanan to complement the distinction between private and public goods. While clubs are private organizations they also manage the allocation of the resources between the individual members, in a similar manner to a public service. Membership criteria are a fundamental feature of clubs and affect their efficiency: "The central question in a theory of clubs is that of determining the membership margin, so to speak, the size of the most desirable cost and consumption sharing arrangement." ==== Definitions of knowledge club ==== Before the Second World War, academic publishing was mostly characterized by a wide range of community-driven scholarly structures with little concerns for profitability. They relied on informal community norms rather than commercial regulations. Theses structures have been described as knowledge clubs: "until the second part of the twentieth century, most journals could be assimilated to a club model". While managed by a community and publicly available, knowledge club are demic and mostly used to the benefit of their members. As a defining feature of the club model, scientific authors are not paid for their publications: "ever since the first


id: economics-of-open-science-20260505-2
file: data/en.wikipedia.org/wiki/Economics_of_open_science-2.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T03:49:05.253185+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
==== Knowledge club and open science ==== The OA Diamond Study states that non-commercial journals in open access "maintain a secular tradition of "club" journals, set up for the uses and interests of a specific closed community of knowledge." While access to read is no longer a material condition for membership, non-commercial journals are still largely managed for the benefits of a community. They are "still strongly embedded in institutional environments (from a legal and governance perspective)." Club journals have gained a new relevance with the development of electronic publishing and played a fundamental role in the early development of online open science in the early 1990s. Pioneers of open access electronic publishings were non-commercial and community-driven initiatives that built up on a trend of grassroot publishing innovation in the social sciences and the humanities: "In the late '80s and early '90s, a host of new journal titles launched on listservs and (later) the Web. Journals such as Postmodern Cultures, Surfaces, the Bryn Mawr Classical Review and the Public-Access Computer Systems Review were all managed by scholars and library workers rather than publishing professionals." The development of the web and free editing tools for scientific publications like Open Journal System


id: economics-of-open-science-20260505-3
file: data/en.wikipedia.org/wiki/Economics_of_open_science-3.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T03:49:05.253185+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
The small society presses, struggling to cope with growing scale, were supported and then largely supplanted by the 'Big 5' commercial presses: Elsevier (which acquired Pergamon in 1991), Wiley, Springer, Taylor & Francis and Sage. These newly-empowered players brought an industrial approach to the publication and dissemination process, for the first time realising the benefits that these specialised capital and skills could provide by operating at a scale that was unprecedented to that date. As it became a private good, the scientific journal was also transformed into an industrial product, with an increased standardization of publishing norms, peer-review process or copyrights. In contrast smaller scientific publishers participate to a more typical publishing market, with a persistent competition. Four out of the five most costly journals "are published by big five publishers". With the conversion to electronic journals, scientific publishing became a hybrid market: along with individual subscriptions, leading publishers introduced big deals or pluri-annual licenses to large bundle of journal titles. Big deals were typically negotiated with national networks of research libraries and academic institutions. Big deals proved advantageous to publishers as well as they limited the "administrative costs" of managing a large number of contracts between journals and buyers.


id: economics-of-open-science-20260505-4
file: data/en.wikipedia.org/wiki/Economics_of_open_science-4.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T03:49:05.253185+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
==== From readers to authors: hybrid and full open access ==== The early developments of Open science and the open sharing of scientific publication on the web was at first a challenge for leading commercial publishers: the executive board of Elsevier "had failed to grasp the significance of electronic publishing altogether, and therefore the deadly danger that it posed—the danger, namely, that scientists would be able to manage without the journal". Initial experiments of scientific journals were mostly led by non-commercial initiatives. Commercially viable open access journals have appeared in the late 1990s, under the leadership of new competitors such as the Public Library of Science (PLOS), MDPI or Hindawi. They relies generally on the author-pay model: the journal provides an editorial service to the author of a publication and charge an article-processing charge to cover the editing costs. This practice is anterior to open access, as subscription-based journals held by scientific societies occasionally charged for additional services (such as photographies in color). For Peter Suber, this economic model is similar to broadcast television: "If advertisers can pay all the costs of production, then a TV studio can broadcast a show without charging viewers. In the case of scholarly research


id: economics-of-open-science-20260505-5
file: data/en.wikipedia.org/wiki/Economics_of_open_science-5.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T03:49:05.253185+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
the largest supplier of academic journals is also in charge of evaluating and validating research quality and impact (e.g., Pure, Plum Analytics, Sci Val), identifying academic experts for potential employers (e.g., Expert Lookup5), managing the research networking platforms through which to collaborate (e.g., SSRN, Hivebench, Mendeley), managing the tools through which to find funding (e.g., Plum X, Mendeley, Sci Val), and controlling the platforms through which to analyze and store researchers' data (e.g., Hivebench, Mendeley). Since it has expanded beyond publishing, the vertical integration of privately owned infrastructures has become extensively integrated to daily research activities: "the privatised control of scholarly infrastructures is especially noticeable in the context of 'vertical integration' that publishers such as Elsevier and SpringerNature are seeking by controlling all aspects of the research lifecycle, from submission to publication and beyond". In contrast with publication, which was an outsourced business separated from institutional and community activities, the new services developed by large publishers are embedded in the infrastructure of universities and create potentially stronger dependency links: "Pure embeds Elsevier within the university workflow process through its abilities to manage research at the university level, including the provision of a dashboard to facilitate decision making by university research


id: economics-of-open-science-20260505-6
file: data/en.wikipedia.org/wiki/Economics_of_open_science-6.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T03:49:05.253185+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
==== The emergence of digital knowledge commons ==== Until the 1990s open knowledge was not considered as a commons in economic theory but as a "classic example of a pure public good, a good available to all and where one person's use does not subtract from another's use". For Elinor Ostrom and Charlotte Hess, this framework is no longer viable as the principle of non-excludability has been significantly weakened: "new technologies can enable the capture of what were once free and open public goods (...) Knowledge, which can seem so ubiquitous in digital form, is, in reality, more vulnerable than ever before" In a scientific context, examples of new enclosures of public goods may include all the surveillance data systems put in place by Elsevier, Springer or Academic social networks that capturate activities such as social interactions, reference collections. The uncontrolled development of the early web highlighted the need for common management of knowledge resources: "People started to notice behaviors and conditions on the web — congestion, free riding, conflict, overuse, and pollution — that had long been identified with other types of commons." The open access of the 1990s and early 2000s movement aimed to ensure that science will


id: economics-of-open-science-20260505-7
file: data/en.wikipedia.org/wiki/Economics_of_open_science-7.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T03:49:05.253185+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
==== Consolidation of the common ecosystem (2015-) ==== Since 2015, open science infrastructures, platforms and journals have converged to the creation of digital academic commons. While they were initially conceived either as a public good (a "grid" that ensure the distribution of a non-excludable resource) or a club good (with a limited range beyond a specific communities), open science infrastructures have been increasingly structured around a shared ecosystem of services and standards has emerged through the network of dependencies from one infrastructure to another. Open science infrastructures face similar issues met by other open institutions such as open data repositories or large scale collaborative project such as Wikipedia: "When we study contemporary knowledge infrastructures we find values of openness often embedded there, but translating the values of openness into the design of infrastructures and the practices of infrastructuring is a complex and contingent process". The conceptual definition of open science infrastructures has been largely influenced by the analysis of Elinor Ostrom on the commons and more specifically on the knowledge commons. In accordance with Ostrom, Cameron Neylon understates that open infrastructures are not only a public good characterized by the management of a pool of common resources but also by


id: economics-of-open-science-20260505-8
file: data/en.wikipedia.org/wiki/Economics_of_open_science-8.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T03:49:05.253185+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
=== Editorial work and evaluation === Editorial work and the management of peer review remain the core activity of academic journals and their most identified contribution and service rendered to scientific communities. It is the main expenses of the non-commercial journals surveyed by the OA Diamond Study: "the five main expenses/payables of the journal are editing (531), copy-editing (463), technical and software support (393), typesetting (384), and design (336)". Translation is a frequently quoted added cost, that may have been incentivicized by open science as the potential audience of local non-academic readers create incentives to maintain a multilingual website. Even before their conversion to electronic publishing, non-for-profits journals have maintained an affordable price, due to a nearly exclusive focus on editorial services: "in 2013, the mean price per article in for-profit journals was 3.2 times higher than in non-for-profit journals, and that the corresponding ratio for the median price per article was even 4.33:1". With Internet publication, costs can be significantly lower, due to additional cuts in transaction and labor costs, use of share platforms and infrastructure or reliance on voluntary work: "over 60% of journals reported annual costs in the previous year under $/€10,000, including in-kind contributions." In contrast


id: economics-of-open-science-20260505-9
file: data/en.wikipedia.org/wiki/Economics_of_open_science-9.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T03:49:05.253185+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
=== Commercial services and prestige === The overall price per article of commercial publishers is consistently higher than in the non-commercial sectors. This discrepancy has been partly accounted by the maintenance of several services necessary to run a business activity (pricing, transaction management, marketing...), that non-commercial structure can drop entirely with little impact. Leading commercial journals claim to be more selective in regard to article submissions, which has the effect of creating a more complex and time-consuming acceptation workflow: "The more effort a publisher invests in each paper, and the more articles a journal rejects after peer review, the more costly is each accepted article to publish [although] the key question is whether the extra effort adds useful value". Besides, "costs vary widely in this sector". Without any transformation of the editorial workflow or efficiency gain a standard well-established subscription journal could "charge about $3,700 per paper to cover costs". Yet, in a publisher like Nature, the costs would be "at £20,000–30,000 ($30,000–40,000) per paper". In the higher end of the commercial spectrum, cost per articles are more likely to embed services that are not directly related to publishing : "One possible reason for such variation between journals and publishers


id: economics-of-open-science-20260505-10
file: data/en.wikipedia.org/wiki/Economics_of_open_science-10.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T03:49:05.253185+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
=== Transaction costs === In a market economy, the diffusion of private goods is usually assorted with transactions costs. Theses costs cover all the services required to manage the commoditization of a product, both from the side of the producer as from the side of a consumer. In a wider sense, it encompasses all the work and time allocated all the stakeholders of the transactions to perform it, such as benchmarks, negotiations or contractualizations. Savings on transaction costs are frequently quoted as a significant advantage of non-excludable resource system (common good, public good) over private markets. Since access to the resource is weakly restrained and conditioned by unformal rules, its allocation is less costly overall: "a community could (...) produce better quality outcomes at lower economic costs, because of lower transaction costs, than alternative institutional systems involving private property" According to a 2017 OECD report, market allocation of open knowledge outputs is not sufficiently efficient: as the price of a public good converges to zero, any attempt at setting up a price will result in excessive exclusion and reduced collective benefits. The market may not be the best mechanism for the allocation of a public good, as any price above


id: economics-of-open-science-20260505-11
file: data/en.wikipedia.org/wiki/Economics_of_open_science-11.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T03:49:05.253185+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
=== Access costs === Access to pre-existent research outputs such as publications, datasets or code is a major condition of research. The subscription model used to rely on the assumptions that researchers only need to access a few specialized publications. In practice, research is more unpredictible and frequently rely crossing methods and observations from different fields or even different disciplines. In 2011, a survey of JISC showed that 68% of UK researchers felt they did have a sufficiently wide access to journal and conference papers. Non-academic professional audiences experience difficulties in accessing directly relevant research: "a quarter of those in industry/commerce described their current level of access as fairly/very difficult" as "the main barrier was unwillingness to pay". A survey of business use of research in Denmark highlighted a large range of strategies to avoid the high cost of pay-per-view, especially through collaboration with academics that have institutional access. The impact of open access is amplified by the high degree of internationalization of research: "83% of the economic return on cancer research is drawn from research from non-UK sources" which are less likely to be accessible in a subscription-based model. Beyond the extended coverage, Open science can enhance the efficiency


id: economics-of-open-science-20260505-12
file: data/en.wikipedia.org/wiki/Economics_of_open_science-12.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T03:49:05.253185+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
=== Research efficiency === Impacts of open science on research efficiency stem from the benefits of enhanced access to previous work. Due to the complexity of bibliography search, closed subscription system "can lead to high levels of duplication—that is, where separate teams work on the same thing unbeknownst to each other." The issue is not limited to academic research, but affect industrial R&D as well: "an analysis of pharmaceutical patents by 18 large companies showed that 86% of target compounds were investigated by two or more companies" Non-publication of data or intermediary results can also have cascading effects on the overall quality of research. Meta-analysis rely on the reproductibility of pre-existent observations and experiments to identify the scientific consensus on a specific topic or field of research. They can be affected by statistical errors and bias, as well as the pre-selection of statistically significant results. Extensive opening of final and intermediary data sources makes it easier to spot potential mistakes. Text and data mining projects have more recently become a major focus of studies on potential gain of research efficiency. In contrast with the standard procedures of state of the art, text mining projects process very large corpus and are


id: economics-of-open-science-20260505-13
file: data/en.wikipedia.org/wiki/Economics_of_open_science-13.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T03:49:05.253185+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
=== Economic and social development === The potential economic impact for open science research outputs is significant. Innovation commons are a major, although overlooked, source of economic growth: "The innovation commons is the true origin of innovation. It is the source from which the subsequent markers of innovation emerge — the entrepreneurial actors, the innovating firms, the new markets, and so on." Recent developments like the growth of data analytics services across a large variety of economic sectors have created further needs for research data: "There are many other values (...) that are promoted through the longterm stewardship and open availability of research data. The rapidly expanding area of artificial intelligence (AI) relies to a great extent on saved data." In 2019, the combined data market of the 27 countries of the European Union and the United Kingdom was estimated at 400 billion euros and had a sustained growth of 7.6% per year. although no estimation was given of the specific value of research data, research institutions were identified as important stakeholders in the emerging ecosystem of "data commons". In 2011, a JISC report estimated that there was 1.8 million knowledge workers in the United Kingdom working in R&D, IT,


id: economics-of-open-science-20260505-14
file: data/en.wikipedia.org/wiki/Economics_of_open_science-14.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T03:49:05.253185+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
== Economic regulation of open science == Economic regulation of scientific publishing has long be stuck in a "collective action dilemma", due to the lack of coordinations between all stakeholders: "To truly reduce their costs, librarians would have to build a shared online collection of scholarly resources jointly managed by the academic community as a whole, but individual academic institutions lack the private incentives necessary to invest in a shared collection." Although it was initially expected by some economists, that the academic publishing markets would be structurally disrupted by new open access competitors, change was mostly driven by scientific communities, scientific institutions and, lately, coordinations of funders. In the 2000s, forms of regulation appear at a local scale to solve obvious market failure in the management of open science outuput. Development of research data repositories has been sustained by the implementation of "government or funder mandates for open data that require the producers of data to make them openly accessible". Mandates have been less easily expanded to other scientific outputs such as publications, that could not be covered by open data programs and were already invested by large commercial structures. In the great recession, scientific institutions and libraries had to


id: aled-edwards-20260505-0
file: data/en.wikipedia.org/wiki/Aled_Edwards-0.md
category: reference
title: Aled Edwards
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Aled_Edwards
date_saved: 2026-05-05T03:49:06.519735+00:00
instance: kb-cron
parent: aled-edwards-20260505-0
summary:
Aled Morgan Edwards (born June 1, 1962) is the founder and Chief Executive of the Structural Genomics Consortium, a charitable public-private partnership. He is Professor of Medical Genetics and Medical Biophysics at the University of Toronto, Visiting Professor of Chemical Biology at the University of Oxford, and adjunct professor at McGill University. == Early life == Born in Holyhead, Wales, Edwards moved to Canada in 1965 with his parents Undeg and Iwan Edwards, a choral conductor who was awarded the Order of Canada in 1995 for his contributions to Canadian music. == Education == Edwards earned his bachelor's degree (1983) and his Ph.D. (1988) in biochemistry from McGill University supervised by Peter Braun. He carried out post-doctoral studies at Stanford University in the laboratory of Roger Kornberg, where he first crystallized RNA polymerase II, a structure for which Kornberg was awarded the Nobel Prize in Chemistry in 2006. == Research contributions == From 1992 to 1997, while a professor at McMaster University, Edwards became interested in developing structural biology methods and was among the first to use mass spectrometry to identify regions of proteins prone to crystallization. He used this technique to facilitate the crystallography of key proteins involved in


id: european-open-science-cloud-20260505-0
file: data/en.wikipedia.org/wiki/European_Open_Science_Cloud-0.md
category: reference
title: European Open Science Cloud
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/European_Open_Science_Cloud
date_saved: 2026-05-05T03:49:07.702753+00:00
instance: kb-cron
parent: european-open-science-cloud-20260505-0
summary:
The European Open Science Cloud (EOSC) is a European Commission initiative aiming at developing an infrastructure providing its users with services promoting open science practices. Besides being open science oriented, the envisaged infrastructure is built by aggregating services provided by several providers following a System of systems approach. Its goal is to establish a federation of infrastructures facilitating effortless access to interoperable research assets and enhanced services spanning geographical boundaries and diverse academic fields. The initiative started in 2015 with the plan that its organizers finish it by 2020. A European Union committee on research endorsed a plan for the cloud's development in May 2018. The European Open Science Cloud officially launched in November 2018, starting to provide access to services via their EOSC Portal. Public meetings about the project have emphasized the ideological motivations for promoting open science. == EOSC Governance == The development of EOSC is governed by three bodies: An executive board tasked to ensure implementation and accountability; a Governance board, working as an institutional group gathering representatives from the Member States and Associated Countries and from the Commission to ensure effective supervision of the EOSC implementation; and a Stakeholder Forum working as the community actively contributing


id: expression-atlas-20260505-0
file: data/en.wikipedia.org/wiki/Expression_Atlas-0.md
category: reference
title: Expression Atlas
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Expression_Atlas
date_saved: 2026-05-05T03:49:08.798435+00:00
instance: kb-cron
parent: expression-atlas-20260505-0
summary:
The Expression Atlas is a database maintained by the European Bioinformatics Institute that provides information on gene expression patterns from RNA-Seq and Microarray studies, and protein expression from Proteomics studies. The Expression Atlas allows searches by gene, splice variant, protein attribute, disease, treatment or organism part (cell types/tissues). Individual genes or gene sets can be searched for. All datasets in Expression Atlas have its metadata manually curated and its data analysed through standardised analysis pipelines. There are two components to the Expression Atlas, the Baseline Atlas and the Differential Atlas: == Baseline Atlas == The Baseline Atlas provides information about which gene products are present (and at what abundance) under "normal" conditions. This component of the Expression Atlas consists of RNA-seq experiments from ArrayExpress repositories. It aims to answer questions such as: Which genes are specifically expressed in kidney? What is the expression pattern for gene SAA4 in normal tissues? == Differential Atlas == The Differential Atlas allows users to identify genes that are up- or down-regulated in different experimental conditions. == See also == Human Protein Atlas The Cancer Genome Atlas == References == == Further reading == == External links == "About Expression Atlas". European Molecular Biology Laboratory


id: fair-data-20260505-0
file: data/en.wikipedia.org/wiki/FAIR_data-0.md
category: reference
title: FAIR data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/FAIR_data
date_saved: 2026-05-05T03:49:10.096945+00:00
instance: kb-cron
parent: fair-data-20260505-0
summary:
FAIR data is data which meets the 2016 FAIR principles of findability, accessibility, interoperability, and reusability (FAIR). The FAIR principles emphasize machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention) because humans increasingly rely on computational support to deal with data as a result of the increase in the volume, complexity, and rate of production of data. The abbreviation FAIR/O data is sometimes used to indicate that the dataset or database in question complies with the FAIR principles and also carries an explicit data‑capable open license. == FAIR principles published by GO FAIR == Findable The first step in (re)using data is to find them. Metadata and data should be easy to find for both humans and computers. Machine-readable metadata are essential for automatic discovery of datasets and services, so this is an essential component of the FAIRification process. F1. (Meta)data are assigned a globally unique and persistent identifier F2. Data are described with rich metadata (defined by R1 below) F3. Metadata clearly and explicitly include the identifier of the data they describe F4. (Meta)data are registered or indexed in a searchable resource Accessible Once the user finds the


id: figshare-20260505-0
file: data/en.wikipedia.org/wiki/Figshare-0.md
category: reference
title: Figshare
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Figshare
date_saved: 2026-05-05T03:49:11.518948+00:00
instance: kb-cron
parent: figshare-20260505-0
summary:
Figshare is an online open access repository where researchers can preserve and share their research outputs, including figures, datasets, images, and videos. It is free to upload content and free to access, in adherence to the principle of open data. Figshare is one of a number of portfolio businesses supported by Digital Science, a subsidiary of Springer Nature. == History == Figshare was launched in January 2011 by Mark Hahnel and has been supported by Digital Science since a January 2012 relaunch. Hahnel first developed the platform as a personal custom solution for the organization and publication of diverse research products generated in support of his PhD in stem cell biology. In January 2013, Figshare announced a partnership with PLOS to integrate Figshare data hosting, access, and visualization with their associated PLOS articles. In September 2013, the service launched a hosted institutional repository service. In December 2013, they announced integration with ImpactStory to support the collection of altmetrics. Figshare also hosts the Reproducibility Collection as a founding member of The Reproducibility Initiative, which acts as an independent and blinded validator for replication of submitted data. Figshare releases 'The State of Open Data' each year to assess the changing academic landscape


id: global-urban-evolution-project-20260505-0
file: data/en.wikipedia.org/wiki/Global_Urban_Evolution_Project-0.md
category: reference
title: Global Urban Evolution Project
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Global_Urban_Evolution_Project
date_saved: 2026-05-05T03:49:13.929625+00:00
instance: kb-cron
parent: global-urban-evolution-project-20260505-0
summary:
The Global Urban Evolution Project is an international collaborative project which was started by Marc T. J. Johnson at the Centre for Urban Environments of the University of Toronto Mississauga (UTM). It includes partners from at least 5 continents, 26 countries, and 160 cities. As a field study of evolution, and as a global study of the effects of urbanization on evolution, its scale is unprecedented. It has been described as "the best replicated test of parallel evolution, on the largest scale ever attempted". The project uses white clover as a model organism for studying global urbanization and urban evolution. White clover was chosen because it already grew in most cities worldwide. It examines the plant's production of hydrogen cyanide (HCN) in urban and more rural environments ("urban-rural clines"). Hydrogen cyanide deters herbivores and increases clover's tolerance for water stress. The project has demonstrated that urban environments are altering the ways in which plants evolve locally, and that similar changes are occurring globally, a demonstration of parallel evolution. It enables researchers to better understand the nature of urban environments, the adaptive capacity of species, and their ability to deal with rapid global environmental changes. == Project history == In 2018,


id: harking-20260505-0
file: data/en.wikipedia.org/wiki/HARKing-0.md
category: reference
title: HARKing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/HARKing
date_saved: 2026-05-05T03:49:15.371909+00:00
instance: kb-cron
parent: harking-20260505-0
summary:
HARKing (hypothesizing after the results are known) is an acronym coined by social psychologist Norbert Kerr that refers to the questionable research practice of "presenting a post hoc hypothesis in the introduction of a research report as if it were an a priori hypothesis". Hence, a key characteristic of HARKing is that post hoc hypothesizing is falsely portrayed as a priori hypothesizing. HARKing may occur when a researcher tests an a priori hypothesis but then omits that hypothesis from their research report after they find out the results of their test. Post hoc analysis or post hoc theorizing then may lead to a post hoc hypothesis. == Types == Several types of HARKing have been distinguished, including: THARKing Transparently hypothesizing after the results are known, rather than the secretive, undisclosed, HARKing that was first proposed by Kerr. In this case, researchers openly declare that they developed their hypotheses after they observed their research results. CHARKing (or Pure HARKing) CHARKing or "pure HARKing" refers to the practice of constructing new hypotheses after the results are known and presenting them as a priori hypotheses. CHARKing is often regarded as the prototypical form of HARKing. RHARKing RHARKing refers to retrieving old hypotheses from


id: initiative-for-open-citations-20260505-0
file: data/en.wikipedia.org/wiki/Initiative_for_Open_Citations-0.md
category: reference
title: Initiative for Open Citations
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Initiative_for_Open_Citations
date_saved: 2026-05-05T03:49:20.289810+00:00
instance: kb-cron
parent: initiative-for-open-citations-20260505-0
summary:
The Initiative for Open Citations (I4OC) is a project launched publicly in April 2017, that describes itself as: "a collaboration between scholarly publishers, researchers, and other interested parties to promote the unrestricted availability of scholarly citation data and to make these data available." It is intended to facilitate improved citation analysis. == Methodology == The citations are stored in Crossref and are made available through the Crossref REST API. They are also available from the OpenCitations Corpus, a database that harvests citation data from Crossref and other sources. The data are considered by those involved in the Initiative to be in the public domain, and so a CC0 licence is used. The stated benefits of this approach are: 1. discoverability of published content; 2. the building of new services, and 3. creation of a public citation graph to explore connections between knowledge fields. The Royal Society of Chemistry earmarked the I4OC as a feature of excellence in publishing, and IOP Publishing participates to implement their commitment to the San Francisco Declaration on Research Assessment. == Launch == The initiative was established in response to a paper on citations in Wikidata, Citations needed for the sum of all human knowledge: Wikidata


id: international-hapmap-project-20260505-0
file: data/en.wikipedia.org/wiki/International_HapMap_Project-0.md
category: reference
title: International HapMap Project
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/International_HapMap_Project
date_saved: 2026-05-05T03:49:21.458141+00:00
instance: kb-cron
parent: international-hapmap-project-20260505-0
summary:
The International HapMap Project is an organization that aimed to develop a haplotype map (HapMap) of the human genome, to describe the common patterns of human genetic variation. HapMap is used to find genetic variants affecting health, disease and responses to drugs and environmental factors. The information produced by the project is made freely available for research. The International HapMap Project is a collaboration among researchers at academic centers, non-profit biomedical research groups and private companies in Canada, China (including Hong Kong), Japan, Nigeria, the United Kingdom, and the United States. It officially started with a meeting on October 27 to 29, 2002, and was expected to take about three years. It comprises three phases; the complete data obtained in Phase I were published on 27 October 2005. The analysis of the Phase II dataset was published in October 2007. The Phase III dataset was released in spring 2009 and the publication presenting the final results published in September 2010. == Background == Unlike with the rarer Mendelian diseases, combinations of different genes and the environment play a role in the development and progression of common diseases (such as diabetes, cancer, heart disease, stroke, depression, and asthma), or in the


id: international-hapmap-project-20260505-1
file: data/en.wikipedia.org/wiki/International_HapMap_Project-1.md
category: reference
title: International HapMap Project
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/International_HapMap_Project
date_saved: 2026-05-05T03:49:21.458141+00:00
instance: kb-cron
parent: international-hapmap-project-20260505-0
summary:
== Scientific strategy == It was expensive in the 1990s to sequence patients' whole genomes. So the National Institutes of Health embraced the idea for a "shortcut", which was to look just at sites on the genome where many people have a variant DNA unit. The theory behind the shortcut was that, since the major diseases are common, so too would be the genetic variants that caused them. Natural selection keeps the human genome free of variants that damage health before children are grown, the theory held, but fails against variants that strike later in life, allowing them to become quite common (In 2002 the National Institutes of Health started a $138 million project called the HapMap to catalog the common variants in European, East Asian and African genomes). For the Phase I, one common SNP was genotyped every 5,000 bases. Overall, more than one million SNPs were genotyped. The genotyping was carried out by 10 centres using five different genotyping technologies. Genotyping quality was assessed by using duplicate or related samples and by having periodic quality checks where centres had to genotype common sets of SNPs. The Canadian team was led by Thomas J. Hudson at McGill University in


id: journal-article-tag-suite-20260505-0
file: data/en.wikipedia.org/wiki/Journal_Article_Tag_Suite-0.md
category: reference
title: Journal Article Tag Suite
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Journal_Article_Tag_Suite
date_saved: 2026-05-05T03:49:22.745801+00:00
instance: kb-cron
parent: journal-article-tag-suite-20260505-0
summary:
The Journal Article Tag Suite (JATS) is format used to describe scientific literature published online. It is a technical standard developed by the National Information Standards Organization (NISO) and approved by the American National Standards Institute with the code Z39.96-2012. The NISO project was a continuation of the work done by NLM/NCBI, and popularized by the NLM's PubMed Central as a de facto standard for archiving and interchange of scientific open-access journals and its contents with XML. With the NISO standardization the NLM initiative has gained a wider reach, and several other repositories, such as SciELO and Redalyc, adopted the XML formatting for scientific articles. The JATS provides a set of XML elements and attributes for describing the textual and graphical content of journal articles as well as some non-article material such as letters, editorials, and book and product reviews. JATS allows for descriptions of the full article content or just the article header metadata; and allows other kinds of contents, including research and non-research articles, letters, editorials, and book and product reviews. == History == Since its introduction, NCBI's NLM Archiving and Interchange DTD suite has become the de facto standard for journal article markup in scholarly publishing. With


id: journal-article-tag-suite-20260505-1
file: data/en.wikipedia.org/wiki/Journal_Article_Tag_Suite-1.md
category: reference
title: Journal Article Tag Suite
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Journal_Article_Tag_Suite
date_saved: 2026-05-05T03:49:22.745801+00:00
instance: kb-cron
parent: journal-article-tag-suite-20260505-0
summary:
The DOCTYPE header is optional, a legacy from SGML and DTD-oriented validators. The dtd-version attribute can be used even without a DTD header. The root element article is common for any version of JATS or "JATS family", as NLM DTDs. The rules for front, body and back tags validation, depends on the JATS version, but all versions have similar structure, with good compatibility in a range of years. The evolution of the schema preserves an overall stability. Less common, "only front", "only front and back" variations are also used for other finalities than full-content representation. The general article composition (as an DTD-content expression) is (front, body?, back?, floats-group?, (sub-article* | response*)) == Tools == There are a variety of tools for create, edit, convert and transform JATS. They range from simple forms to complete conversion automation: === Conversion to JATS === Take as input a scientific document, and, with some human support, produce a JATS output. OpenOffice (LibreOffice) and MS Word documents to JATS: Typeset: provides automated set of converters for MS-Word to JATS XML. OxGarage: can convert documents from various formats into "National Library of Medicine (NLM) DTD 3.0". meTypeset: meTypeset "is a fork of the OxGarage stack" "to


id: metanetx-20260505-0
file: data/en.wikipedia.org/wiki/MetaNetX-0.md
category: reference
title: MetaNetX
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/MetaNetX
date_saved: 2026-05-05T03:49:24.009125+00:00
instance: kb-cron
parent: metanetx-20260505-0
summary:
MetaNetX is a database maintained by the SIB Swiss Institute of Bioinformatics for the automated model construction, and the genome annotation for large-scale metabolic networks. MetaNetX provides a number of tools to access, analyse and manipulate metabolic networks. MetaNetX provides a bunch of pre-mapped metabolic models. To ease model comparison, MetaNetX has developed a resource to unify metabolites and biochemical reactions in the context of metabolic models. This unified namespace is called MetaNetX/MNXref. MNXref reconciles chemical compounds by structural similarity and biochemical reaction context. Then reconciles biochemical reactions on the basis of the chemical compound reconciliation in an iterative way. Each reconciled group of chemical compounds, biochemical reactions and cellular compartments is a bag of similar items. MNXref sets a referent for each group. MetaNetX allows search in MNXref by chemical compounds, biochemical reactions and cellular compartments. Currently, MetaNetX/MNXref reconciles those resources: BiGG ChEBI enviPath HMDB GO KEGG LipidMaps MetaCyc Reactome Rhea SABIO-RK SwissLipids The SEED VMH == References ==


id: mixed-signals-preprocessing-psychophysiological-data-in-brain-vision-analyzer-20260505-0
category: reference
title: Mixed Signals: Preprocessing Psychophysiological Data in Brain Vision Analyzer
tags: science, encyclopedia
date_saved: 2026-05-05T03:49:25.200239+00:00
instance: kb-cron
parent: mixed-signals-preprocessing-psychophysiological-data-in-brain-vision-analyzer-20260505-0
file:
data/en.wikipedia.org/wiki/Mixed_Signals:_Preprocessing_Psychophysiological_Data_in_Brain_Vision_Analyzer-0.md

summary:
Mixed Signals: Preprocessing Psychophysiological Data in Brain Vision Analyzer is a psychophysiology manual for experimental psychologists. Originally compiled by Paul Pfaff at the Experimental Psychopathology and Clinical Psychology lab at Utrecht University, the updated edition of the manual was printed in 2025. The manual covers the preprocessing of a wide range of psychophysiological data types common in experimental psychology. Specific sections are dedicated to skin conductance response, facial electromyography (EMG), startle EMG, smiling/frowning EMG, and postural sway. Preprocessing steps outlined include baseline correction, filtering, artifact rejection, and signal standardization. Recommendations are provided based on reviews of the latest literature in the field. The publication is part of ongoing open science initiatives in psychology to standardize research procedures in the aftermath of the replication crisis and has received positive reviews. == Further reading == Cacioppo, J. T., Tassinary, L. G., & Berntson, G. (Eds.). (2007). Handbook of psychophysiology. Cambridge University Press. Brain Vision Analyzer User Manual Version 1.05 accessible at: https://www.linguistik.hu-berlin.de/de/institut/professuren/psycholinguistik/psyling/archiv/files/ekp/Analyzer.pdf/@@download/file/Analyzer.pdf == References ==

source_url:
https://en.wikipedia.org/wiki/Mixed_Signals:_Preprocessing_Psychophysiological_Data_in_Brain_Vision_Analyzer


id: peter-murray-rust-20260505-0
file: data/en.wikipedia.org/wiki/Peter_Murray-Rust-0.md
category: reference
title: Peter Murray-Rust
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Peter_Murray-Rust
date_saved: 2026-05-05T03:49:26.337246+00:00
instance: kb-cron
parent: peter-murray-rust-20260505-0
summary:
Peter Murray-Rust is a chemist currently working at the University of Cambridge. As well as his work in chemistry, Murray-Rust is also known for his support of open access and open data. == Education == He was educated at Bootham School, a private school in York, and at Balliol College, Oxford. After obtaining a Doctor of Philosophy with a thesis entitled A structural investigation of some compounds showing charge-transfer properties, he became lecturer in chemistry at the (new) University of Stirling and was first warden of Andrew Stewart Hall of Residence. In 1982, he moved to Glaxo Group Research at Greenford to head Molecular Graphics, Computational Chemistry and later protein structure determination. He was Professor of Pharmacy in the University of Nottingham from 1996 to 2000, setting up the Virtual School of Molecular Sciences. He is now Reader Emeritus in Molecular Informatics at the University of Cambridge and Senior Research Fellow Emeritus at Churchill College, Cambridge. == Research == His research interests have involved the automated analysis of data in scientific publications, creation of virtual communities, e.g. The Virtual School of Natural Sciences in the Globewide Network Academy, and the Semantic Web. With Henry Rzepa, he has extended this to


id: open-energy-modelling-initiative-20260505-0
file: data/en.wikipedia.org/wiki/Open_Energy_Modelling_Initiative-0.md
category: reference
title: Open Energy Modelling Initiative
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Energy_Modelling_Initiative
date_saved: 2026-05-05T03:49:27.553982+00:00
instance: kb-cron
parent: open-energy-modelling-initiative-20260505-0
summary:
The Open Energy Modelling Initiative (openmod) is a grassroots community of energy system modellers from universities and research institutes across Europe and elsewhere. The initiative promotes the use of open-source software and open data in energy modelling for research and policy advice. The Open Energy Modelling Initiative documents a variety of open-source energy models and addresses practical and conceptual issues regarding their development and application. The initiative runs an email list, an internet forum, and a wiki and hosts occasional academic workshops. A statement of aims is available. == Context == The application of open-source development to energy modelling dates back to around 2003. This section provides some background for the growing interest in open methods. === Growth in open energy modelling === Just two active open energy modelling projects were cited in a 2011 paper: OSeMOSYS and TEMOA. Balmorel was also public at that time, having been made available on a website in 2001. As of October 2021, the Open Energy Platform lists 17 open energy frameworks and about 50 open energy models. === Academic literature === This 2012 paper presents the case for using "open, publicly accessible software and data as well as crowdsourcing techniques to develop robust


id: open-energy-modelling-initiative-20260505-1
file: data/en.wikipedia.org/wiki/Open_Energy_Modelling_Initiative-1.md
category: reference
title: Open Energy Modelling Initiative
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Energy_Modelling_Initiative
date_saved: 2026-05-05T03:49:27.553982+00:00
instance: kb-cron
parent: open-energy-modelling-initiative-20260505-0
summary:
=== Public policy support === In May 2016, the European Union announced that "all scientific articles in Europe must be freely accessible as of 2020". This is a step in the right direction, but the new policy makes no mention of open software and its importance to the scientific process. In August 2016, the United States government announced a new federal source code policy which mandates that at least 20% of custom source code developed by or for any agency of the federal government be released as open-source software (OSS). The US Department of Energy (DOE) is participating in the program. The project is hosted on a dedicated website and subject to a three-year pilot. Open-source campaigners are using the initiative to advocate that European governments adopt similar practices. In 2017 the Free Software Foundation Europe (FSFE) issued a position paper calling for free software and open standards to be central to European science funding, including the flagship EU program Horizon 2020. The position paper focuses on open data and open data processing and the question of open modelling is not traversed per se. === Adoption by regulators and industry generally === A trend evident by 2023 is the adoption


id: open-energy-system-databases-20260505-0
file: data/en.wikipedia.org/wiki/Open_energy_system_databases-0.md
category: reference
title: Open energy system databases
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_databases
date_saved: 2026-05-05T03:49:28.737080+00:00
instance: kb-cron
parent: open-energy-system-databases-20260505-0
summary:
Open energy system database projects employ open data methods to collect, clean, and republish energy-related datasets for open use. The resulting information is then available, given a suitable open license, for statistical analysis and for building numerical energy system models, including open energy system models. Permissive licenses like Creative Commons CC0 and CC BY are preferred, but some projects will house data made public under market transparency regulations and carrying unqualified copyright. The databases themselves may furnish information on national power plant fleets, renewable generation assets, transmission networks, time series for electricity loads, dispatch, spot prices, and cross-border trades, weather information, and similar. They may also offer other energy statistics including fossil fuel imports and exports, gas, oil, and coal prices, emissions certificate prices, and information on energy efficiency costs and benefits. Much of the data is sourced from official or semi-official agencies, including national statistics offices, transmission system operators, and electricity market operators. Data is also crowdsourced using public wikis and public upload facilities. Projects usually also maintain a strict record of the provenance and version histories of the datasets they hold. Some projects, as part of their mandate, also try to persuade primary data providers to release their


id: open-energy-system-databases-20260505-1
file: data/en.wikipedia.org/wiki/Open_energy_system_databases-1.md
category: reference
title: Open energy system databases
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_databases
date_saved: 2026-05-05T03:49:28.737080+00:00
instance: kb-cron
parent: open-energy-system-databases-20260505-0
summary:
== Open energy system database projects == Energy system models are data intensive and normally require detailed information from a number of sources. Dedicated projects to collect, collate, document, and republish energy system datasets have arisen to service this need. Most database projects prefer open data, issued under free licenses, but some will accept datasets with proprietary licenses in the absence of other options. The OpenStreetMap project, which uses the Open Database License (ODbL), contains geographic information about energy system components, including transmission lines. Wikimedia projects such as Wikidata and Wikipedia have a growing set of information related to national energy systems, such as descriptions of individual power stations. The following table summarizes projects that specifically publish open energy system data. Some are general repositories while others (for instance, oedb) are designed to interact with open energy system models in real-time. Three of the projects listed work with linked open data (LOD), a method of publishing structured data on the web so that it can be networked and subject to semantic queries. The overarching concept is termed the semantic web. Technically, such projects support RESTful APIs, RDF, and the SPARQL query language. A 2012 paper reviews the use of LOD


id: open-energy-system-databases-20260505-2
file: data/en.wikipedia.org/wiki/Open_energy_system_databases-2.md
category: reference
title: Open energy system databases
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_databases
date_saved: 2026-05-05T03:49:28.737080+00:00
instance: kb-cron
parent: open-energy-system-databases-20260505-0
summary:
The Open Data Energy Networks (Open Data Réseaux Énergies or ODRÉ) portal is run by eight partners, led by the French national transmission system operator (TSO) Réseau de Transport d'Électricité (RTE). The portal was previously known as Open Data RTE. The site offers electricity system datasets under a Creative Commons CC BY 2.0 compatible license, with metadata, an RSS feed for notifying updates, and an interface for submitting questions. Re-users of information obtained from the site can also register third-party URLs (be they publications or webpages) against specific datasets. The portal uses the French Government Licence Ouverte license and this is explicitly compatible with the United Kingdom Open Government Licence (OGL), the Creative Commons CC BY 2.0 license (and thereby later versions), and the Open Data Commons ODC-BY license. The site hosts electricity, gas, and weather information related to France. === UK Power Networks Open Data Portal === The Open Data Portal is run by UK Power Networks, a GB Distribution Network Operator (DNO), hosted on the OpenDataSoft platform. The Portal offers electricity network datasets under a Creative Commons CC BY 4.0 compatible license, with metadata, a newsfeed, and a data request form. Re-users of information obtained from the site


id: open-energy-system-databases-20260505-3
file: data/en.wikipedia.org/wiki/Open_energy_system_databases-3.md
category: reference
title: Open energy system databases
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_databases
date_saved: 2026-05-05T03:49:28.737080+00:00
instance: kb-cron
parent: open-energy-system-databases-20260505-0
summary:
Open Energy Information (OpenEI) is a collaborative website, run by the US government, providing open energy data to software developers, analysts, users, consumers, and policymakers. The platform is sponsored by the United States Department of Energy (DOE) and is being developed by the National Renewable Energy Laboratory (NREL). OpenEI launched on 9 December 2009. While much of its data is from US government sources, the platform is intended to be open and global in scope. OpenEI provides two mechanisms for contributing structured information: a semantic wiki (using MediaWiki and the Semantic MediaWiki extension) for collaboratively-managed resources and a dataset upload facility for contributor-controlled resources. US government data is distributed under a CC0 public domain dedication, whereas other contributors are free to select an open data license of their choice. Users can rate data using a five-star system, based on accessibility, adaptability, usefulness, and general quality. Individual datasets can be manually downloaded in an appropriate format, often as CSV files. Scripts for processing data can also be shared through the site. In order to build a community around the platform, a number of forums are offered covering energy system data and related topics. Most of the data on OpenEI is exposed


id: open-energy-system-databases-20260505-4
file: data/en.wikipedia.org/wiki/Open_energy_system_databases-4.md
category: reference
title: Open energy system databases
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_databases
date_saved: 2026-05-05T03:49:28.737080+00:00
instance: kb-cron
parent: open-energy-system-databases-20260505-0
summary:
reegle is a clean energy information portal covering renewable energy, energy efficiency, and climate compatible development topics. reegle was launched in 2006 by REEEP and REN21 with funding from the Dutch (VROM), German (BMU), and UK (Defra) environment ministries. Originally released as a specialized internet search engine, reegle was relaunched in 2011 as an information portal. reegle offers and utilizes linked open data (LOD) (described elsewhere on this page). Sources of data include UN and World Bank databases, as well as dedicated partners around the world. reegle maintains a comprehensive structured glossary (driven by an LOD-compliant thesaurus) of energy and climate compatible development terms to assist with the tagging of datasets. The glossary also facilitates intelligent web searches. reegle offers country profiles which collate and display energy data on a per-country basis for most of the world. These profiles are kept current automatically using LOD techniques. As of 2021, the portal is no longer active. === Renewables.ninja === Renewables.ninja is a website that can calculate the hourly power output from solar photovoltaic installations and wind farms located anywhere in the world. The website is a joint project between the Department of Environmental Systems Science, ETH Zurich, Zürich, Switzerland and the


id: open-energy-system-models-20260505-0
file: data/en.wikipedia.org/wiki/Open_energy_system_models-0.md
category: reference
title: Open energy system models
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_models
date_saved: 2026-05-05T03:49:30.157219+00:00
instance: kb-cron
parent: open-energy-system-models-20260505-0
summary:
Open energy-system models are energy-system models that are open source. However, some of them may use third-party proprietary software as part of their workflows to input, process, or output data. Preferably, these models use open data, which facilitates open science. Energy-system models are used to explore future energy systems and are often applied to questions involving energy and climate policy. The models themselves vary widely in terms of their type, design, programming, application, scope, level of detail, sophistication, and shortcomings. For many models, some form of mathematical optimization is used to inform the solution process. Energy regulators and system operators in Europe and North America began adopting open energy-system models for planning purposes in the early‑2020s. Open models and open data are increasingly being used by government agencies to guide the develop of net‑zero public policy as well. Companies and engineering consultancies are likewise adopting open models for analysis. == General considerations == === Organization === The open energy modeling projects listed here fall exclusively within the bottom-up paradigm, in which a model is a relatively literal representation of the underlying system. Several drivers favor the development of open models and open data. There is an increasing interest in making


id: open-energy-system-models-20260505-1
file: data/en.wikipedia.org/wiki/Open_energy_system_models-1.md
category: reference
title: Open energy system models
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_models
date_saved: 2026-05-05T03:49:30.157219+00:00
instance: kb-cron
parent: open-energy-system-models-20260505-0
summary:
=== Surveys === A survey completed in 2021 investigated the degree to which open energy-system modeling frameworks support flexibility options, broken down by supply, demand, storage, sector coupled, and network response. Of the frameworks surveyed, none supported all types, which suggests that the soft coupling of complementary frameworks could provide more holistic assessments of flexibility. Even so, most candidates opt for perfect foresight and do not natively admit probabilistic actions or explicit behavioral responses. == Electricity sector models == Open electricity sector models are confined to just the electricity sector. These models invariably have a temporal resolution of one hour or less. Some models concentrate on the engineering characteristics of the system, including a good representation of high-voltage transmission networks and AC power flow. Others models depict electricity spot markets and are known as dispatch models. While other models embed autonomous agents to capture, for instance, bidding decisions using techniques from bounded rationality. The ability to handle variable renewable energy, transmission systems, and grid storage are becoming important considerations. === AMIRIS === AMIRIS is the open Agent-based Market model for the Investigation of Renewable and Integrated energy Systems. The AMIRIS simulation framework was first developed by the German Aerospace Center


id: open-energy-system-models-20260505-2
file: data/en.wikipedia.org/wiki/Open_energy_system_models-2.md
category: reference
title: Open energy system models
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_models
date_saved: 2026-05-05T03:49:30.157219+00:00
instance: kb-cron
parent: open-energy-system-models-20260505-0
summary:
Under development at the European Commission's Joint Research Centre (JRC), Petten, the Netherlands, Dispa-SET is a unit commitment and dispatch model intended primarily for Europe. It is written in Python (with Pyomo) and GAMS and uses Python for data processing. A valid GAMS license is required. The model is formulated as a mixed integer problem and JRC uses the proprietary CPLEX sover although open source libraries may also be deployed. Technical descriptions are available for versions 2.0 and 2.1. Dispa-SET is hosted on GitHub, together with a trial dataset, and third-party contributions are encouraged. The codebase has been tested on Windows, macOS, and Linux. Online documentation is available. The SET in the project name refers to the European Strategic Energy Technology Plan (SET-Plan), which seeks to make Europe a leader in energy technologies that can fulfill future (2020 and 2050) energy and climate targets. Energy system modeling, in various forms, is central to this European Commission initiative. The model power system is managed by a single operator with full knowledge of the economic and technical characteristics of the generation units, the loads at each node, and the heavily simplified transmission network. Demand is deemed fully inelastic. The system is subject


id: open-energy-system-models-20260505-3
file: data/en.wikipedia.org/wiki/Open_energy_system_models-3.md
category: reference
title: Open energy system models
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_models
date_saved: 2026-05-05T03:49:30.157219+00:00
instance: kb-cron
parent: open-energy-system-models-20260505-0
summary:
EMMA is the European Electricity Market Model. It is a techno-economic model covering the integrated Northwestern European power system. EMMA is being developed by the energy economics consultancy Neon Neue Energieökonomik, Berlin, Germany. The source code and datasets can be downloaded from the project website. A manual is available. EMMA is written in GAMS and uses the CPLEX commercial solver. EMMA models electricity dispatch and investment, minimizing the total cost with respect to investment, generation, and trades between market areas. In economic terms, EMMA classifies as a partial equilibrium model of the wholesale electricity market with a focus on the supply-side. EMMA identifies short-term or long-term optima (or equilibria) and estimates the corresponding capacity mix, hourly prices, dispatch, and cross-border trading. Technically, EMMA is a pure linear program (no integer variables) with about two million non-zero variables. As of 2016, the model covers Belgium, France, Germany, the Netherlands, and Poland and supports conventional generation, renewable generation, and cogeneration. EMMA has been used to study the economic effects of the increasing penetration of variable renewable energy (VRE), specifically solar power and wind power, in the Northwestern European power system. A 2013 study finds that increasing VRE shares will depress prices and,


id: open-energy-system-models-20260505-4
file: data/en.wikipedia.org/wiki/Open_energy_system_models-4.md
category: reference
title: Open energy system models
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_models
date_saved: 2026-05-05T03:49:30.157219+00:00
instance: kb-cron
parent: open-energy-system-models-20260505-0
summary:
NEMO, the National Electricity Market Optimiser, is a chronological dispatch model for testing and optimizing different portfolios of conventional and renewable electricity generation technologies. It applies solely to the Australian National Electricity Market (NEM), which, despite its name, is limited to east and south Australia. NEMO has been in development at the Centre for Energy and Environmental Markets (CEEM), University of New South Wales (UNSW), Sydney, Australia since 2011. The project maintains a small website and runs an email list. NEMO is written in Python. NEMO itself is described in two publications. The data sources are also noted. Optimizations are carried out using a single-objective evaluation function, with penalties. The solution space of generator capacities is searched using the CMA-ES (covariance matrix adaptation evolution strategy) algorithm. The timestep is arbitrary but one hour is normally employed. NEMO has been used to explore generation options for the year 2030 under a variety of renewable energy (RE) and abated fossil fuel technology scenarios. A 2012 study investigates the feasibility of a fully renewable system using concentrated solar power (CSP) with thermal storage, windfarms, photovoltaics, existing hydroelectricity, and biofuelled gas turbines. A number of potential systems, which also meet NEM reliability criteria, are


id: open-energy-system-models-20260505-5
file: data/en.wikipedia.org/wiki/Open_energy_system_models-5.md
category: reference
title: Open energy system models
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_models
date_saved: 2026-05-05T03:49:30.157219+00:00
instance: kb-cron
parent: open-energy-system-models-20260505-0
summary:
pandapower is a power system analysis and optimization program being jointly developed by the Energy Management and Power System Operation research group, University of Kassel and the Department for Distribution System Operation, Fraunhofer Institute for Energy Economics and Energy System Technology (IEE), both of Kassel, Germany. The codebase is hosted on GitHub and is also available as a package. The project maintains a website, an emailing list, and online documentation. pandapower is written in Python. It uses the pandas library for data manipulation and analysis and the PYPOWER library to solve for power flow. Unlike some open source power system tools, pandapower does not depend on proprietary platforms like MATLAB. pandapower supports the automated analysis and optimization of distribution and transmission networks. This allows a large of number of scenarios to be explored, based on different future grid configurations and technologies. pandapower offers a collection of power system elements, including: lines, 2-winding transformers, 3-winding transformers, and ward-equivalents. It also contains a switch model that allows the modeling of ideal bus-bus switches as well as bus-line/bus-trafo switches. The software supports topological searching. The network itself can be plotted, with or without geographical information, using the matplotlib and plotly libraries. A 2016


id: open-energy-system-models-20260505-6
file: data/en.wikipedia.org/wiki/Open_energy_system_models-6.md
category: reference
title: Open energy system models
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_models
date_saved: 2026-05-05T03:49:30.157219+00:00
instance: kb-cron
parent: open-energy-system-models-20260505-0
summary:
renpass is an acronym for Renewable Energy Pathways Simulation System. renpass is a simulation electricity model with high regional and temporal resolution, designed to capture existing systems and future systems with up to 100% renewable generation. The software is being developed by the Centre for Sustainable Energy Systems (CSES or ZNES), University of Flensburg, Germany. The project runs a website, from where the codebase can be download. renpass is written in R and links to a MySQL database. A PDF manual is available. renpass is also described in a PhD thesis. As of 2015, renpass is being extended as renpassG!S, based on oemof. renpass is an electricity dispatch model which minimizes system costs for each time step (optimization) within the limits of a given infrastructure (simulation). Time steps are optionally 15 minutes or one hour. The method assumes perfect foresight. renpass supports the electricity systems found in Austria, Belgium, the Czech Republic, Denmark, Estonia, France, Finland, Germany, Latvia, Lithuania, Luxembourg, the Netherlands, Norway, Poland, Sweden, and Switzerland. The optimization problem for each time step is to minimize the electricity supply cost using the existing power plant fleet for all regions. After this regional dispatch, the exchange between the regions is


id: open-energy-system-models-20260505-7
file: data/en.wikipedia.org/wiki/Open_energy_system_models-7.md
category: reference
title: Open energy system models
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_models
date_saved: 2026-05-05T03:49:30.157219+00:00
instance: kb-cron
parent: open-energy-system-models-20260505-0
summary:
SWITCH is a loose acronym for solar, wind, conventional and hydroelectric generation, and transmission. SWITCH is an optimal planning model for power systems with large shares of renewable energy. SWITCH is being developed by the Department of Electrical Engineering, University of Hawaiʻi at Mānoa, Hawaii, USA. The project runs a small website and hosts its codebase and datasets on GitHub. SWITCH is written in Pyomo, an optimization components library programmed in Python. It can use either the open source GLPK solver or the commercial CPLEX solver. SWITCH is a power system model, focused on renewables integration. It can identify which generator and transmission projects to build in order to satisfy electricity demand at the lowest cost over a several-year period while also reducing CO2 emissions. SWITCH utilizes multi-stage stochastic linear optimization with the objective of minimizing the present value of the cost of power plants, transmission capacity, fuel usage, and an arbitrary per-tonne CO2 charge (to represent either a carbon tax or a certificate price), over the course of a multi-year investment period. It has two major sets of decision variables. First, at the start of each investment period, SWITCH selects how much generation capacity to build in each of


id: open-energy-system-models-20260505-8
file: data/en.wikipedia.org/wiki/Open_energy_system_models-8.md
category: reference
title: Open energy system models
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_models
date_saved: 2026-05-05T03:49:30.157219+00:00
instance: kb-cron
parent: open-energy-system-models-20260505-0
summary:
AnyMOD.jl is a framework for planning macro‑energy systems at a high level of spatio-temporal detail. The framework covers the expansion and operation of short-term and seasonal storage, fossil and renewable generation, transmission infrastructure, and sector coupling technologies. It can be used to plan long‑term pathways under perfect foresight. AnyMOD.jl is implemented in Julia and relies on the JuMP library for optimization and DataFrames.jl for data management. Models are formulated as linear optimization problems and can be solved with open-source libraries like HiGHS or commercial solvers like CPLEX. To increase accessibility and enable version-controlled development, specific models are fully defined using CSV files. Compared to similar tools, AnyMOD.jl puts an emphasis on innovative methods to achieve high detail and capture intermittent renewables, while maintaining a comprehensive scope in terms of regions and sectors. These methods include varying the spatio-temporal resolution by energy carrier within the same model and a scaling algorithm to improve the properties of the underlying optimization problem. Methods from stochastic programming are now being implemented to better address the uncertainties associated with renewable generation. As of 2022, most studies deploying the tool have focused on the German energy system in a European context, for instance investigating the trade‑offs


id: open-energy-system-models-20260505-9
file: data/en.wikipedia.org/wiki/Open_energy_system_models-9.md
category: reference
title: Open energy system models
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_models
date_saved: 2026-05-05T03:49:30.157219+00:00
instance: kb-cron
parent: open-energy-system-models-20260505-0
summary:
Calliope is an energy system modeling framework, with a focus on flexibility, high spatial and temporal resolution, and the ability to execute different runs using the same base-case dataset. The project is being developed at the Department of Environmental Systems Science, ETH Zurich, Zürich, Switzerland. The project maintains a website, hosts the codebase at GitHub, operates an issues tracker, and runs two email lists. Calliope is written in Python and uses the Pyomo library. It can link to the open source GLPK solver and the commercial CPLEX solver. PDF documentation is available. And a two‑page software review is available. A Calliope model consists of a collection of structured text files, in YAML and CSV formats, that define the technologies, locations, and resource potentials. Calliope takes these files, constructs a pure linear optimization (no integer variables) problem, solves it, and reports the results in the form of pandas data structures for analysis. The framework contains five abstract base technologies – supply, demand, conversion, storage, transmission – from which new concrete technologies can be derived. The design of Calliope enforces the clear separation of framework (code) and model (data). A 2015 study uses Calliope to compare the future roles of nuclear power


id: open-energy-system-models-20260505-10
file: data/en.wikipedia.org/wiki/Open_energy_system_models-10.md
category: reference
title: Open energy system models
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_models
date_saved: 2026-05-05T03:49:30.157219+00:00
instance: kb-cron
parent: open-energy-system-models-20260505-0
summary:
EnergyPATHWAYS is a bottom-up energy sector model used to explore the near-term implications of long-term deep decarbonization. The lead developer is energy and climate protection consultancy, Evolved Energy Research, San Francisco, USA. The code is hosted on GitHub. EnergyPATHWAYS is written in Python and links to the open source Cbc solver. Alternatively, the GLPK, or CPLEX solvers can be employed. EnergyPATHWAYS utilizes the PostgreSQL object-relational database management system (ORDBMS) to manage its data. EnergyPATHWAYS is a comprehensive accounting framework used to construct economy-wide energy infrastructure scenarios. While portions of the model do use linear programming techniques, for instance, for electricity dispatch, the EnergyPATHWAYS model is not fundamentally an optimization model and embeds few decision dynamics. EnergyPATHWAYS offers detailed energy, cost, and emissions accounting for the energy flows from primary supply to final demand. The energy system representation is flexible, allowing for differing levels of detail and the nesting of cities, states, and countries. The model uses hourly least-cost electricity dispatch and supports power-to-gas, short-duration energy storage, long-duration energy storage, and demand response. Scenarios typically run to 2050. A predecessor of the EnergyPATHWAYS software, named simply PATHWAYS, has been used to construct policy models. The California PATHWAYS model was used to


id: open-energy-system-models-20260505-11
file: data/en.wikipedia.org/wiki/Open_energy_system_models-11.md
category: reference
title: Open energy system models
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_models
date_saved: 2026-05-05T03:49:30.157219+00:00
instance: kb-cron
parent: open-energy-system-models-20260505-0
summary:
GENeSYS‑MOD couples the demand sectors covering electricity, buildings, industry, and transport and finds the cost-optimal investment into conventional and renewable energy generation, storage, and infrastructure. The research focus is on long-term system development and pathway analysis. The model was first used to analyze decarbonization scenarios at the global level, broken down into ten regions. However, the framework is highly flexible, allowing for calculations at various levels of detail, from individual households to global aggregations, depending on the desired research question and availability of input data. A 2019 study examined the low‑carbon transition of the European energy system and specifically the problem of stranded assets under a range of scenarios. It found that up to €200 billion in fossil-fueled capacities could be stranded by 2035 unless stronger policy signals are able to address short‑term planning biases. Another 2019 study evaluates China's energy system transformation, highlighting the need to reduce coal consumption by 60% by 2050 to meet global climate targets. Renewable energies, and in particular photovoltaics and onshore wind, emerge as cost-effective solutions, but overcoming local resistance and increasing stakeholder engagement remain crucial for success. A 2021 study investigates the European Green Deal goal of achieving 100% greenhouse gas reductions by


id: open-energy-system-models-20260505-12
file: data/en.wikipedia.org/wiki/Open_energy_system_models-12.md
category: reference
title: Open energy system models
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_models
date_saved: 2026-05-05T03:49:30.157219+00:00
instance: kb-cron
parent: open-energy-system-models-20260505-0
summary:
A key paper describing OSeMOSYS is available. A 2011 study uses OSeMOSYS to investigate the role of household investment decisions. A 2012 study extends OSeMOSYS to capture the salient features of a smart grid. The paper explains how to model variability in generation, flexible demand, and grid storage and how these impact on the stability of the grid. OSeMOSYS has been applied to village systems. A 2015 paper compares the merits of stand-alone, mini-grid, and grid electrification for rural areas in Timor-Leste under differing levels of access. In a 2016 study, OSeMOSYS is modified to take into account realistic consumer behavior. Another 2016 study uses OSeMOSYS to build a local multi-regional energy system model of the Lombardy region in Italy. One of the aims of the exercise was to encourage citizens to participate in the energy planning process. Preliminary results indicate that this was successful and that open modeling is needed to properly include both the technological dynamics and the non-technological issues. A 2017 paper covering Alberta, Canada factors in the risk of overrunning specified emissions targets because of technological uncertainty. Among other results, the paper finds that solar and wind technologies are built out seven and five years earlier


id: open-energy-system-models-20260505-13
file: data/en.wikipedia.org/wiki/Open_energy_system_models-13.md
category: reference
title: Open energy system models
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_models
date_saved: 2026-05-05T03:49:30.157219+00:00
instance: kb-cron
parent: open-energy-system-models-20260505-0
summary:
The basic functionality of PyPSA is described in a 2018 paper. PyPSA bridges traditional steady-state power flow analysis software and full multi-period energy system models. It can be invoked using either non-linear power flow equations for system simulation or linearized approximations to enable the joint optimization of operations and investment across multiple periods. Generator ramping and multi-period up and down-times can be specified, DSM is supported, but demand remains price inelastic. A 2018 study examines potential synergies between sector coupling and transmission reinforcement in a future European energy system constrained to reduce carbon emissions by 95%. The PyPSA-Eur-Sec-30 model captures the demand-side management potential of battery electric vehicles (BEV) as well as the role that power-to-gas, long-term thermal energy storage, and related technologies can play. Results indicate that BEVs can smooth the daily variations in solar power while the remaining technologies smooth the synoptic and seasonal variations in both demand and renewable supply. Substantial buildout of the electricity grid is required for a least-cost configuration. More generally, such a system is both feasible and affordable. The underlying datasets are available from Zenodo. As of January 2018, PyPSA is used by more than a dozen research institutes and companies worldwide. Some


id: open-energy-system-models-20260505-14
file: data/en.wikipedia.org/wiki/Open_energy_system_models-14.md
category: reference
title: Open energy system models
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_models
date_saved: 2026-05-05T03:49:30.157219+00:00
instance: kb-cron
parent: open-energy-system-models-20260505-0
summary:
In practical terms, the framework allows for modeling competition between technologies that can serve the same purpose, such as power generation, while also providing insights into when and where a specific technology is required. Additionally, it can be applied to transportation problems, where the optimal exchange of a commodity between at least two distinct regions needs to be determined. Furthermore, it addresses storage problems, where the optimal balance between production and consumption at different points in time is calculated. REMix offers several key features that make it a robust tool for energy system modeling. It is designed to handle large-scale models with high spatial and technological resolutions, making it suitable for complex analyses. The framework also incorporates path optimization, allowing for multi-year analyses and strategic planning over extended periods. Ongoing work deals with very large instances involving path optimization using the parallel solver PIPS-IPM++. A notable feature is its custom accounting capability, provided through the indicator module, which enables flexible definitions of what contributes to the objective functions. Additionally, REMix supports flexible modeling, offering multiple approaches to integrate and model technologies, allowing users to tailor the framework to their specific needs. Finally, it supports multi-criteria optimization, where, beyond cost minimization,


id: open-energy-system-models-20260505-15
file: data/en.wikipedia.org/wiki/Open_energy_system_models-15.md
category: reference
title: Open energy system models
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_energy_system_models
date_saved: 2026-05-05T03:49:30.157219+00:00
instance: kb-cron
parent: open-energy-system-models-20260505-0
summary:
The GAMS language requires a proprietary environment and its significant cost effectively limits participation to those who can access an institutional copy. == Programming components == Programming components, in this context, are coherent blocks of code or compiled libraries that can be relatively easily imported or linked to by higher‑level modeling frameworks in order to obtain some well‑defined functionality. === Technology modules === A number of technical component models are now also open source. While these component models do not constitute systems models aimed at public policy development (the focus of this page), they nonetheless warrant a mention. Technology modules can be linked or otherwise adapted into these broader initiatives. Sandia photovoltaic array performance model pvlib photovoltaics facility library hplib heat pump facility library windpowerlib wind turbine library hydropowerlib hydroelectricity library === Auction models === A number of electricity auction models have been written in GAMS, AMPL, MathProg, and other languages. These include: the EPOC nodal pricing model Australian National Electricity Market examples using MathProg can be found at b:GLPK/Electricity markets === Open solvers === Many projects rely on a pure linear or mixed integer solver to perform classical optimization, constraint satisfaction, or some mix of the two. While there


id: open-notebook-science-challenge-20260505-0
file: data/en.wikipedia.org/wiki/Open_Notebook_Science_Challenge-0.md
category: reference
title: Open Notebook Science Challenge
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Notebook_Science_Challenge
date_saved: 2026-05-05T03:49:31.605154+00:00
instance: kb-cron
parent: open-notebook-science-challenge-20260505-0
summary:
The Open Notebook Science Challenge is a crowdsourcing research project which collects measurements of the non-aqueous solubility of organic compounds and publishes these as open data; findings are reported in an open notebook science manner. Although anyone may contribute research data, the competition is only open to post-secondary students in the US and UK. The challenge in turn forms part of the UsefulChem project, an ongoing open notebook science effort to synthesize and screen potential new anti-malarial drugs. Data from the Solubility Challenge will be used to build predictive computational models of solubility for use in optimising syntheses. The challenge began on September 28, 2008 and, as of February 2014, involves researchers and their students from at least 4 different institutions and has resulted in the acquisition of over 7672 solubility measurements. == Prizes == To encourage participation, each month an award is given to the student who does, in the opinion of the judges, the best work. In order to participate, students have to be a US or UK resident. The award is a US$500 cash prize. The first three winners also received a year's subscription to the journal Nature. The awards are sponsored by Submeta and Nature. ==


id: open-peer-review-20260505-0
file: data/en.wikipedia.org/wiki/Open_peer_review-0.md
category: reference
title: Open peer review
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_peer_review
date_saved: 2026-05-05T03:49:36.870107+00:00
instance: kb-cron
parent: open-peer-review-20260505-0
summary:
Open peer review is the various possible modifications of the traditional scholarly peer review process. The three most common modifications to which the term is applied are: Open identities: Authors and reviewers are aware of each other's identity. Open reports: Review reports are published alongside the relevant article (rather than being kept confidential). Open participation: The wider community (and not just invited reviewers) are able to contribute to the review process. These modifications are supposed to address various perceived shortcomings of the traditional scholarly peer review process, in particular its lack of transparency, lack of incentives, wastefulness, bullying and harassment. == Definitions == Open identities Open peer review may be defined as "any scholarly review mechanism providing disclosure of author and referee identities to one another at any point during the peer review or publication process". Then reviewer's identities may or may not be disclosed to the public. This is in contrast to the traditional peer review process where reviewers remain anonymous to anyone but the journal's editors. Authors' names are disclosed during the process in a single-blind organisation of reviews. In the double-blind process, authors' names and reviewers' names all remain anonymous except to the editor. Open reports Open


id: open-peer-review-20260505-1
file: data/en.wikipedia.org/wiki/Open_peer_review-1.md
category: reference
title: Open peer review
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_peer_review
date_saved: 2026-05-05T03:49:36.870107+00:00
instance: kb-cron
parent: open-peer-review-20260505-0
summary:
== History == In 1997, the open participation journal Electronic Transactions on Artificial Intelligence was launched. Articles were first "published" (meaning the day when the article is first made public), then "reviewed" (meaning a open process of public discussion), and then "refereed" (meaning the confidential pass/fail decision of whether to accept the article or not). In 1999, the open access journal Journal of Medical Internet Research was launched, which from its inception decided to publish the names of the reviewers at the bottom of each published article. Also in 1999, the British Medical Journal moved to an open peer review system, revealing reviewers' identities to the authors but not the readers, and in 2000, the medical journals in the open access BMC series published by BioMed Central, launched using open peer review. As with the BMJ, the reviewers' names are included on the peer review reports. In addition, if the article is published the reports are made available online as part of the "pre-publication history"'. Several other journals published by the BMJ Group allow optional open peer review, as does PLoS Medicine, published by the Public Library of Science. The BMJ's Rapid Responses allows ongoing debate and criticism following publication.


id: open-peer-review-20260505-2
file: data/en.wikipedia.org/wiki/Open_peer_review-2.md
category: reference
title: Open peer review
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_peer_review
date_saved: 2026-05-05T03:49:36.870107+00:00
instance: kb-cron
parent: open-peer-review-20260505-0
summary:
Publishers: BioMed Central BMJ Group Copernicus Publications European Molecular Biology Organization (EMBO) Frontiers MDPI (authors have the option to publish peer review reports, etc.) Nature Research Open Research Europe (the European Union publishing platform for Horizon Europe and Horizon 2020 projects) Journals: eLife GigaScience Nature PeerJ PLOS ReScience C Semantic Web journal by IOS Press WikiJournal SciPost Peer review at The BMJ, BioMed Central, EMBO, eLife, ReScience C, and the Semantic Web journal involves posting the entire pre-publication history of the article online, including not only signed reviews of the article, but also its previous versions and in some cases names of handling editors and author responses to the reviewers. Furthermore, the Semantic Web journal publishes reviews of all submissions, including rejected ones, on its website, while eLife plans to publish the reviews not only for published articles, but also for rejected articles. The European Geosciences Union operates public discussions where open peer review is conducted before suitable articles are accepted for publication in the journal. Sci, an open access journal which covers all research fields, adapted a post publication public peer-review (P4R) in which it promised authors immediate visibility of their manuscripts on the journal's online platform after a


id: open-research-20260505-0
file: data/en.wikipedia.org/wiki/Open_research-0.md
category: reference
title: Open research
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_research
date_saved: 2026-05-05T03:49:38.077952+00:00
instance: kb-cron
parent: open-research-20260505-0
summary:
Open research is research that is openly accessible by others. Those who publish research in this way are often concerned with making research more transparent, more collaborative, more wide-reaching, and more efficient. Open research aims to make both research methods and the resulting data freely available, often via the internet, in order to support reproducibility and, potentially, massively distributed research collaboration. In this regard, it is related to both open source software and citizen science. Especially for research that is scientific in nature, open research may be referred to as open science. However, the term can also implicate research done in fields as varied as the social sciences, the humanities, mathematics, engineering and medicine. == Types of open projects == Important distinctions exist between different types of open projects. Projects that provide open data but don't offer open collaboration are referred to as "open access" rather than open research. Providing open data is a necessary but not sufficient condition for open research, because although the data may be used by anyone, there is no requirement for subsequent research to take place openly. For example, though there have been many calls for more open collaborative research in drug discovery and the


id: open-science-award-for-open-source-research-software-20260505-0
file: data/en.wikipedia.org/wiki/Open_Science_Award_for_Open_Source_Research_Software-0.md
category: reference
title: Open Science Award for Open Source Research Software
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Award_for_Open_Source_Research_Software
date_saved: 2026-05-05T03:49:39.274982+00:00
instance: kb-cron
parent: open-science-award-for-open-source-research-software-20260505-0
summary:
The Open Science Award for Open Source Research Software (French: Prix science ouverte du logiciel libre de la recherche) is a French scientific award given since 2022. The prize is part of the second National Plan for open science and rewards projects, teams and young researchers engaged in exemplary practices of management, dissemination and reuse of research data. It is awarded by the French Ministry of Higher Education and Research and Space. The prize has four categories: The "Scientific and Technical" (Scientifique et technique) category rewards software that stands out for its scientific quality, methodological rigour and technical excellence. The "Community" (Communauté) category highlights projects that have successfully built and nurtured an active community of users and contributors. The "Documentation" category recognises software that offers exemplary documentation facilitating use, adoption and contribution to the project. The "Jury's Favourite" (Coup de cœur du jury) category rewards an exemplary project combining several of these dimensions. In each category, the jury awards a main prize as well as a "rising star" (espoir) award for promising projects, typically started less than five years ago. == Winners == == Notes and references == == See also == Open science Open Science Award for Research Data


id: open-science-infrastructure-20260505-0
file: data/en.wikipedia.org/wiki/Open_Science_Infrastructure-0.md
category: reference
title: Open Science Infrastructure
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Infrastructure
date_saved: 2026-05-05T03:49:40.430585+00:00
instance: kb-cron
parent: open-science-infrastructure-20260505-0
summary:
Open Science Infrastructure (or open scholarly infrastructure) is information infrastructure that supports the open sharing of scientific productions such as publications, datasets, metadata or code. In November 2021 the Unesco recommendation on Open Science describes it as "shared research infrastructures that are needed to support open science and serve the needs of different communities". Open science infrastructures are a form of scientific infrastructure (also called cyberinfrastructure, e-Science or e-infrastructure) that support the production of open knowledge. Beyond the management of common resources, they are frequently structured as community-led initiatives with a set collective norms and governance regulations, which makes them also a form of knowledge commons. The definition of open science infrastructures usually exclude privately owned scientific infrastructures run by leading commercial publishers. Conversely it may include actors not always characterized as scientific infrastructures that play a critical role in the ecosystem of open science, such as publishing platforms in open access (open scholarly communication service). Computing infrastructures and online services have played a key role in the production and diffusion of scientific knowledge since the 1960s. While these early scientific infrastructure were initially envisioned as community initiatives, they could not be openly used due to the lack of interconnectivity


id: open-science-infrastructure-20260505-1
file: data/en.wikipedia.org/wiki/Open_Science_Infrastructure-1.md
category: reference
title: Open Science Infrastructure
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Infrastructure
date_saved: 2026-05-05T03:49:40.430585+00:00
instance: kb-cron
parent: open-science-infrastructure-20260505-0
summary:
=== Openness and the commons === Open science infrastructures are open, which differentiate them with other scientific and knowledge infrastructure and, more specifically, with subscription-based commercial infrastructures. Openness is both a core value and a directing principle that affect the aims, the governance and the management of the infrastructure. Open science infrastructure face similar issues met by other open institutions such as open data repositories or large scale collaborative project such as Wikipedia: "When we study contemporary knowledge infrastructures we find values of openness often embedded there, but translating the values of openness into the design of infrastructures and the practices of infrastructuring is a complex and contingent process". The conceptual definition of open science infrastructures has been largely influenced by the analysis of Elinor Ostrom on the commons and more specifically on the knowledge commons. In accordance with Ostrom, Cameron Neylon understates that open infrastructures are not only characterized by the management of a pool of common resources but also by the elaboration of common governance and norms. The economic theory of the commons make it possible to expand beyond the scope of limited scope of scholar associations toward large scale community-led initiatives: "Ostrom's work (…) provides a template


id: open-science-infrastructure-20260505-2
file: data/en.wikipedia.org/wiki/Open_Science_Infrastructure-2.md
category: reference
title: Open Science Infrastructure
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Infrastructure
date_saved: 2026-05-05T03:49:40.430585+00:00
instance: kb-cron
parent: open-science-infrastructure-20260505-0
summary:
Scientific projects have been among the earliest use case for digital infrastructure. The theorization of scientific knowledge infrastructure even predates the development of computing technologies. The knowledge network envisioned by Paul Otlet or Vannevar Bush already incorporated numerous features of online scientific infrastructures. After the Second World War, the United States faced a "periodical crisis": existing journals could not keep up with the rapidly increasing scientific output. The issue became politically relevant after the successful launch of Sputnik: "The Sputnik crisis turned the librarians' problem of bibliographic control into a national information crisis." The emerging computing technologies were immediately considered as a potential solution to make a larger amount of scientific output readable and searchable. Access to foreign language publication was also a key issue that was expected to be solved by machine translation: in the 1950s, a significant amount of scientific publications were not available in English, especially the one coming from the Soviet bloc. Influent members of the National Science Foundation like Joshua Ledeberg advocated for the creation of a "centralized information system", SCITEL that would at first coexist with printed journals and gradually replace them altogether on account of its efficiency. In the plan laid out by


id: open-science-infrastructure-20260505-3
file: data/en.wikipedia.org/wiki/Open_Science_Infrastructure-3.md
category: reference
title: Open Science Infrastructure
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Infrastructure
date_saved: 2026-05-05T03:49:40.430585+00:00
instance: kb-cron
parent: open-science-infrastructure-20260505-0
summary:
=== The Web Revolution (1990–1995) === The World Wide Web was originally framed as an open scientific infrastructure. The project was inspired by ENQUIRE, an information management software commissioned to Tim Berners-Lee by the CERN for the specific needs of high energy physics. The structure of ENQUIRE was closer to an internal web of data: it connected "nodes" that "could refer to a person, a software module, etc. and that could be interlined with various relations such as made, include, describes and so forth". While it "facilitated some random linkage between information" Enquire was not able to "facilitate the collaboration that was desired for in the international high-energy physics research community". Like any significant computing scientific infrastructure before the 1990s, the development of ENQUIRE was ultimately impeded by the lack of interoperability and the complexity of managing network communications: "although Enquire provided a way to link documents and databases, and hypertext provided a common format in which to display them, there was still the problem of getting different computers with different operating systems to communicate with each other". Sharing of data and data documentation was a major focus in the initial communication of the World Wide Web when the project


id: open-science-infrastructure-20260505-4
file: data/en.wikipedia.org/wiki/Open_Science_Infrastructure-4.md
category: reference
title: Open Science Infrastructure
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Infrastructure
date_saved: 2026-05-05T03:49:40.430585+00:00
instance: kb-cron
parent: open-science-infrastructure-20260505-0
summary:
The development of the World-Wide Web had rendered numerous pre-existing scientific infrastructure obsolete. It also lifted numerous restrictions and obstacles to online contribution and network management that made it possible to attempt more ambitious project. By the end of the 1990s, the creation of public scientific computing infrastructure became a major policy issue. The first wave of web-based scientific projects in the 1990s and the early 2000s revealed critical issues of sustainability. As funding was allocated on a specific time period, critical databases, online tools or publishing platforms could hardly be maintained; and project managers were faced with a valley of death "between grant funding and ongoing operational funding". Several competing terms appeared to fill this need. In the United States, the cyber-infrastructure was used in a scientific context by a US National Science Foundation (NSF) blue-ribbon committee in 2003: "The newer term cyberinfrastructure refers to infrastructure based upon distributed computer, information and communication technology. If infrastructure is required for an industrial economy, then we could say that cyberinfrastructure is required for a knowledge economy." E-infrastructure or e-science were used in a similar meaning in the United Kingdom and European countries. Thanks to "sizable investments", major national and international infrastructures


id: open-science-infrastructure-20260505-5
file: data/en.wikipedia.org/wiki/Open_Science_Infrastructure-5.md
category: reference
title: Open Science Infrastructure
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Infrastructure
date_saved: 2026-05-05T03:49:40.430585+00:00
instance: kb-cron
parent: open-science-infrastructure-20260505-0
summary:
=== Toward open science infrastructures (2015-…) === The consolidation and expansion of commercial scientific infrastructure had entailed renewed calls to secure "community-controlled infrastructure". The acquisition of the open repositories Digital Commons and SSRN by Elsevier has highlighted the lack of reliability of critical scientific infrastructure for open science. The SPARC report on European Infrastructures underlines that "a number of important infrastructures at risk and as a consequence, the products and services that comprise open infrastructure are increasingly being tempted by buyout offers from large commercial enterprises. This threat affects both not-for-profit open infrastructure as well as closed, and is evidenced by the buyout in recent years of commonly relied on tools and platforms such as SSRN, bepress, Mendeley, and Github." In contrast with the consolidation of privately owned infrastructure, the open science movement "has tended to overlook the importance of social structures and systemic constraints in the design of new forms of knowledge infrastructures". It remained mostly focused to the content of scientific research, with little integration of technical tools and few large community initiatives. "Common pool of resources is not governed or managed by the current scholarly commons initiative. There is no dedicated hard infrastructure and though there may


id: open-science-infrastructure-20260505-6
file: data/en.wikipedia.org/wiki/Open_Science_Infrastructure-6.md
category: reference
title: Open Science Infrastructure
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Infrastructure
date_saved: 2026-05-05T03:49:40.430585+00:00
instance: kb-cron
parent: open-science-infrastructure-20260505-0
summary:
=== Type and roles === Open Access repositories are the most frequent form of Open Science Infrastructure with 5,791 repositories in existence in December 2021 according to OpenDOAR Yet, there is a significant diversification of the roles and the activities of open science infrastructure, at least among the largest infrastructures. In the survey of European infrastructure conducted by SPARC Europe, 95% of the respondents mention that they provide services in at least three different stages of research production out of six (Creation, Evaluation, Publishing, Hosting, Discovering and Archiving). Aggregation, hosting and indexing are especially central activities, common to most Open Science Infrastructures regardless of their focus. Specialization does happen at a higher level. A network analysis identifies "two main clusters of activities": Publishing-focused infrastructures which are associated with the "publishing and hosting traditional text formats". Among them, "paper submission (41 out of 70) and review (30) were the most commonly reported activities". Creation-focused infrastructures which deal preferably with the "processing and storing research outputs, particularly data". Theses actors provide specific services in the field of "data gathering (47 out of 71), and data analysis (40)". Besides, "computation and machine learning (18) and Experimentation (15) were roughly half as common". ===


id: open-science-infrastructure-20260505-7
file: data/en.wikipedia.org/wiki/Open_Science_Infrastructure-7.md
category: reference
title: Open Science Infrastructure
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Infrastructure
date_saved: 2026-05-05T03:49:40.430585+00:00
instance: kb-cron
parent: open-science-infrastructure-20260505-0
summary:
=== Economics === Many Open Science Infrastructure run "at a relatively low cost" as small infrastructures are an important part of the open science ecosystem. In 2020, 21 out of 53 surveyed European infrastructures "report spending less than €50,000". Consequently, more than 75% of surveyed European infrastructures are run by small teams of 5 FTEs or less. The size of the infrastructure and the extent of its funding is far from always proportional to the critical service it offers: "some of the most heavily used services make ends meet with a tiny core team of two to five people." Volunteer contributions are significant as well with is both "a strength and weakness to an OSI's sustainability". The landscape of open science infrastructures is therefore rather close to the ideals of a "decentralised network of small projects" envisioned by theoricians of the scholarly commons. A very large majority of open science infrastructure are non-commercial and collaborations or financial support from the private sector remain very limited. Overall, European infrastructures were financially sustainable in 2020 which contrasts with the situation ten years prior: in 2010, European infrastructures had much less visibility: they usually lacked "a long-term perspective" and struggled "with securing the


id: open-science-monitor-20260505-0
file: data/en.wikipedia.org/wiki/Open_science_monitor-0.md
category: reference
title: Open science monitor
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science_monitor
date_saved: 2026-05-05T03:49:41.653595+00:00
instance: kb-cron
parent: open-science-monitor-20260505-0
summary:
An open science monitor or open access monitor is a scientific framework that aims to assess the spread of open practices in a scientific context. Open science monitors or dashboards are built at different scales: from institutional to national or international. They require an accurate assessment of the total scientific output and a further breakdown between open and closed content. They rely on a variety of data sources and methodologies to achieve this end. Consequently, open science monitors have also become relevant tools for bibliometric analysis. While initially conceived to track publications in academic journals, open science monitor have diversify their scopes and indicators. A recent trend has been to map other major outputs of open science research such as datasets, software or clinical trials. == Definition == Open science monitor are a scientific infrastructure that provide a "good knowledge of the state" of scientific outputs and their "open access rate". They are also a policy tool that aims to better assess the discrepancy between actual practices and long-term objectives: they "can inform future strategies at institutional and national levels, provides guidance for policy development and review, helps to assess the effects of funding mechanisms and is crucial to negotiate


id: open-science-monitor-20260505-1
file: data/en.wikipedia.org/wiki/Open_science_monitor-1.md
category: reference
title: Open science monitor
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science_monitor
date_saved: 2026-05-05T03:49:41.653595+00:00
instance: kb-cron
parent: open-science-monitor-20260505-0
summary:
The first open science monitors were created in the 2000s and the early 2010s. They were usually conceived as a natural outgrowth of new national and international policy in favor of open access and open science. The Berlin Declaration from 2003 especially introduced the concept of a global "transition of scientific publishing toward an open access system" which require "information on publication output and on subscription and publication fees." Additionally the diversification of open science publishing into various publication venues (journals, repositories, overlay journals...) and formats (articles, conferences, datasets...) created unprecedented challenges. One of the earliest form of open science monitor was the Dutch project NARCIS ("National Academic Research and Collaborations Information System") that started operating in December 2005. NARCIS is primarily a national scientific portal that aims to integrate "all kinds of types of information from scientific institutes in the Netherlands." Yet it also has a special focus on "academic OAI repositories" and publishes global statistics on the rate of open restricted and embargoed scientific works since 2000. By 2013, Finland pioneered the influential Jyväskylä Model through its national portal JUULI. First experimented at the Open Science Centre of the University of Jyväskyl this approach aims "to centralize all


id: open-science-monitor-20260505-2
file: data/en.wikipedia.org/wiki/Open_science_monitor-2.md
category: reference
title: Open science monitor
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science_monitor
date_saved: 2026-05-05T03:49:41.653595+00:00
instance: kb-cron
parent: open-science-monitor-20260505-0
summary:
=== Local infrastructures and repositories === Local infrastructures include Current Research Information Systems directly managed by scientific institutions and universities that "help manage, understand, and evaluate research activities". At the institutional level they can bring the most extensive coverage of scientific output, especially taking into account locally published journals that would not necessarily be indexed in global scientific infrastructures. Due to their direct connections with scientific communities, local infrastructures can incentivize researchers to "enter their publications into those systems" and implement a more various range of indicators than what is commonly available in international databases. Local infrastructures are managed in a decentralized way, with varying levels of coverage and information depending on the institutions. In some cases, local repository are "fed solely by the large commercial databases" and will not have any added value. The integration of diverse local sources of data into a common and standardized schemes is a major challenge for open science monitors. The preexistence of ambitious funding policy considerably ease this process, as institutions will be already encouraged to adopt specific norms and metadata requirements. While local infrastructures are generally thoughts as providers of data for an open science monitor, the relationship can go both way.


id: open-science-monitor-20260505-3
file: data/en.wikipedia.org/wiki/Open_science_monitor-3.md
category: reference
title: Open science monitor
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science_monitor
date_saved: 2026-05-05T03:49:41.653595+00:00
instance: kb-cron
parent: open-science-monitor-20260505-0
summary:
=== Tracking open science adoption === The French Open Science Monitor was conceived from the start to capture "open access dynamic". This has significant implication in terms of design and data flow as the "OA status of a publication evolves over time" due to embargo policies as well retrospective opening of past content. Despite significant differences in regards to methodologies or to data source, Pierre Mounier underlined in 2022 that "we observe the same dynamic" in the open access monitors of "three different European countries": the French, German and Dutch monitor all convege to show that slightly more than 60% of research is published in open access. === Economic analysis === Open science monitors aim to facilitate the estimation of scientific publishing costs. Without any aggregation of publication data, "information on expenditure for open access publication fees and especially for non-open access publication fees is often not available centrally" The monitor can also contribute to better assess the economic impact of open science across the entire academic ecosystem. While it is generally assumed that the conversion to open access publishing should not be costlier than the existing system, there can still be significant variations, especially with an APC-based model: institutions


id: open-scientific-data-20260505-0
file: data/en.wikipedia.org/wiki/Open_scientific_data-0.md
category: reference
title: Open scientific data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_scientific_data
date_saved: 2026-05-05T03:49:42.862927+00:00
instance: kb-cron
parent: open-scientific-data-20260505-0
summary:
Open scientific data or open research data is a type of open data focused on publishing observations and results of scientific activities available for anyone to analyze and reuse. A major purpose of the drive for open data is to allow the verification of scientific claims, by allowing others to look at the reproducibility of results, and to allow data from many sources to be integrated to give new knowledge. The modern concept of scientific data emerged in the second half of the 20th century, with the development of large knowledge infrastructure to compute scientific information and observation. The sharing and distribution of data has been early identified as an important stake but was impeded by the technical limitations of the infrastructure and the lack of common standards for data communication. The World Wide Web was immediately conceived as a universal protocol for the sharing of scientific data, especially coming from high-energy physics. == Definition == === Scientific data === The concept of open scientific data has developed in parallel with the concept of scientific data. Scientific data was not formally defined until the late 20th century. Before the generalization of computational analysis, data has been mostly an informal terms,


id: open-scientific-data-20260505-1
file: data/en.wikipedia.org/wiki/Open_scientific_data-1.md
category: reference
title: Open scientific data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_scientific_data
date_saved: 2026-05-05T03:49:42.862927+00:00
instance: kb-cron
parent: open-scientific-data-20260505-0
summary:
The emergence of scientific data is associated with a semantic shift in the way core scientific concepts like data, information and knowledge are commonly understood. Following the development of computing technologies, data and information are increasingly described as "things": "Like computation, data always have a material aspect. Data are things. They are not just numbers but also numerals, with dimensionality, weight, and texture". After the Second World War large scientific projects have increasingly relied on knowledge infrastructure to collect, process and analyze important amount of data. Punch-cards system were first used experimentally on climate data in the 1920s and were applied on a large scale in the following decade: "In one of the first Depression-era government make-work projects, Civil Works Administration workers punched some 2 million ship log observations for the period 1880–1933." By 1960, the meteorological data collections of the US National Weather Records Center has expanded to 400 millions cards and had a global reach. The physically of scientific data was by then fully apparent and threatened the stability of entire buildings: "By 1966 the cards occupied so much space that the Center began to fill its main entrance hall with card storage cabinets (figure 5.4). Officials became


id: open-scientific-data-20260505-2
file: data/en.wikipedia.org/wiki/Open_scientific_data-2.md
category: reference
title: Open scientific data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_scientific_data
date_saved: 2026-05-05T03:49:42.862927+00:00
instance: kb-cron
parent: open-scientific-data-20260505-0
summary:
=== Sharing scientific data on the web (1990-1995) === The World Wide Web was originally conceived as an infrastructure for open scientific data. Sharing of data and data documentation was a major focus in the initial communication of the World Wide Web when the project was first unveiled in August 1991 : "The WWW project was started to allow high energy physicists to share data, news, and documentation. We are very interested in spreading the web to other areas, and having gateway servers for other data". The project stemmed from a close knowledge infrastructure, ENQUIRE. It was an information management software commissioned to Tim Berners-Lee by the CERN for the specific needs of high energy physics. The structure of ENQUIRE was closer to an internal web of data: it connected "nodes" that "could refer to a person, a software module, etc. and that could be interlined with various relations such as made, include, describes and so forth". While it "facilitated some random linkage between information" Enquire was not able to "facilitate the collaboration that was desired for in the international high-energy physics research community". Like any significant computing scientific infrastructure before the 1990s, the development of ENQUIRE was ultimately impeded


id: open-scientific-data-20260505-3
file: data/en.wikipedia.org/wiki/Open_scientific_data-3.md
category: reference
title: Open scientific data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_scientific_data
date_saved: 2026-05-05T03:49:42.862927+00:00
instance: kb-cron
parent: open-scientific-data-20260505-0
summary:
=== Policy implementations (2010-…) === After 2010, national and supra-national institutions took a more interventionist stance. New policies have been implemented not only to ensure and incentivize the opening of scientific data, usually in continuation to existing open data program. In Europe, the "European Union Commissioner for Research, Science, and Innovation, Carlos Moedas made open research data one of the EU's priorities in 2015." First published in 2016, the FAIR Guiding Principles have become an influential framework for opening scientific data. The principles have been originally designed two years earlier during a policy ad research workshop at Lorentz, Jointly Designing a Data FAIRport. During the deliberations of the workshop, "the notion emerged that, through the definition of, and widespread support for, a minimal set of community-agreed guiding principles and practice" The principles do not attempt to define scientific data, which remains a relatively plastic concept, but strive to describe "what constitutes 'good data management'". They cover four foundational principles, "that serve to guide data producer": Findability, Accessibility, Interoperability, and Reusability. and also aim to provide a step toward machine-actionability by expliciting the underlying semantics of data. As it fully acknowledge the complexity of data management, the principles do not claim


id: open-scientific-data-20260505-4
file: data/en.wikipedia.org/wiki/Open_scientific_data-4.md
category: reference
title: Open scientific data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_scientific_data
date_saved: 2026-05-05T03:49:42.862927+00:00
instance: kb-cron
parent: open-scientific-data-20260505-0
summary:
=== Citation and indexation === The first digital databases of the 1950s and the 1960s have immediately raised issues of citability and bibliographic descriptions. The mutability of computer memory was especially challenging: in contrast with printed publications, digital data could not be expected to remain stable on the long run. In 1965, Ralph Bisco underlined that this uncertainty affected all the associated documents like code notebooks, which may become increasingly out of date. Data management have to find a middle ground between continuous enhancements and some form of generic stability: "the concept of a fluid, changeable, continually improving data archive means that study cleaning and other processing must be carried to such a point that changes will not significantly affect prior analyses" Structured bibliographic metadata for database has been a debated topic since the 1960s. In 1977, the American Standard for Bibliographic Reference adopted a definition of "data file" with a strong focus on the materiability and the mutability of the dataset: neither dates nor authors were indicated but the medium or "Packaging Method" had to be specified. Two years later, Sue Dodd introduced an alternative convention, that brought the citation of data closer to the standard of references of


id: open-scientific-data-20260505-5
file: data/en.wikipedia.org/wiki/Open_scientific_data-5.md
category: reference
title: Open scientific data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_scientific_data
date_saved: 2026-05-05T03:49:42.862927+00:00
instance: kb-cron
parent: open-scientific-data-20260505-0
summary:
Research reproducibility: lack of reproducibility is frequently attributed to deficiencies in research transparency and data analysis process. Consequently, as "a rationale for sharing research data, [research reproducibility] is powerful yet problematic". Reproducibility only applies to "certain kinds of research", mostly in regards to experimental sciences. Public accessibility: this rationale that "products of public funding should be available to the public" is "found in arguments for open government". While directly inspired by similar arguments made in favor of open access to publications, its range is more limited as scientific open data "has direct benefits to far fewer people, and those benefits vary by stakeholder" Research valorization: open scientific data may bring a substantial value to the private sector. This argument is especially used to support "the need for more repositories that can accept and curate research data, for better tools and services to exploit data, and for other investments in knowledge infrastructure". Increased research and innovation: open scientific data may significantly enhanced the quality of private and public research. This argument aims for "investing in knowledge infrastructure to sustain research data, curated to high standards of professional practices" Yet collaboration between the different actors and stakeholders of the data lifecycle is


id: open-scientific-data-20260505-6
file: data/en.wikipedia.org/wiki/Open_scientific_data-6.md
category: reference
title: Open scientific data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_scientific_data
date_saved: 2026-05-05T03:49:42.862927+00:00
instance: kb-cron
parent: open-scientific-data-20260505-0
summary:
== Legal status == The opening of scientific data has raised a variety of legal issues in regards to ownership rights, copyrights, privacy and ethics. While it is commonly considered that researchers "own the data they collect in the course of their research", this "view is incorrect": the creation of dataset involves potentially the rights of numerous additional actors such as institutions (research agencies, funders, public bodies), associated data producers, personal data on private citizens. The legal situation of digital data has been consequently described as a "bundle of rights" due to the fact that the "legal category of "property" (...) is not a suitable model for dealing with the complexity of data governance problems" === Copyright === Copyright has been the primary focus of the legal literature of open scientific data until the 2010s. The legality of data sharing was early on identified a crucial issue. In contrast with the sharing of scientific publication, the main impediment was not copyright but uncertainty: "the concept of 'data' [was] a new concept, created in the computer age, while copyright law emerged at the time of printed publications." In theory, copyright and author rights provisions do not apply to simple collections of


id: open-scientific-data-20260505-7
file: data/en.wikipedia.org/wiki/Open_scientific_data-7.md
category: reference
title: Open scientific data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_scientific_data
date_saved: 2026-05-05T03:49:42.862927+00:00
instance: kb-cron
parent: open-scientific-data-20260505-0
summary:
=== Ownership === Copyright issues with scientific datasets have been further complicated by uncertainties regarding ownership. Research is largely a collaborative activity that involves a wide range of contributions. Initiatives like CRediT (Contributor Roles Taxonomy) have identified 14 different roles, of which 4 are explicitly related to data management (Formal Analysis, Investigation, Data curation and Visualization). In the United States, ownership of research data is usually "determined by the employer of the researcher", with the principal investigator acting as the caretaker of the data rather than the owner. Until the development of research open data, US institutions have been usually more reluctant to waive copyrights on data than on publications, as they are considered strategic assets. In the European Union, there is no largely agreed framework on the ownership of data. The additional rights of external stakeholders has also been raised, especially in the context of medical research. Since the 1970s, patients have claimed some form of ownership of the data produced in the context of clinical trials, notably with important controversies concerning 'whether research subjects and patients actually own their own tissue or DNA." === Privacy === Numerous scientific projects rely on data collection of persons, notably in medical


id: open-scientific-data-20260505-8
file: data/en.wikipedia.org/wiki/Open_scientific_data-8.md
category: reference
title: Open scientific data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_scientific_data
date_saved: 2026-05-05T03:49:42.862927+00:00
instance: kb-cron
parent: open-scientific-data-20260505-0
summary:
=== Integration to the research workflow === In contrast with the broad incitations for data sharing included in the early policies in favor of open scientific data, the complexity and the underlying costs and requirements of scientific data management are increasingly acknowledged: "Data sharing is difficult to do and to justify by the return on investment." Open data is not simply a supplementary task but has to be envisioned throughout the entire research process as it "requires changes in methods and practices of research." The opening of research data creates a new settlement of costs and benefits. Public data sharing introduces a new communication setting that primarily contrasts with private data exchange with research collaborators or partners. The collection, the purpose, and the limitation of data have to be explicit as it is impossible to rely on pre-existing informal knowledge: "the documentation and representations are the only means of communicating between data creator and user." Lack of proper documentation means that the burden of recontextualization falls on the potential users and may render the dataset useless. Publication requires further verification regarding the ownership of the data and the potential legal liability if the data is misused. This clarification phase becomes


id: open-scientific-data-20260505-9
file: data/en.wikipedia.org/wiki/Open_scientific_data-9.md
category: reference
title: Open scientific data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_scientific_data
date_saved: 2026-05-05T03:49:42.862927+00:00
instance: kb-cron
parent: open-scientific-data-20260505-0
summary:
Research data management can be laid out in a data management plan or DMP. Data management plans were incepted in 1966 for the specific needs of aeronautic and engineering research, which already faced increasingly complex data frictions. These first examples were focused on material issues associated with the access, transfer, and storage of the data: "Until the early 2000s, DMPs were utilised in this manner: in limited fields, for projects of great technical complexity, and for limited mid-study data collection and processing purposes" After 2000, the implementation of extensive research infrastructure and the development of open science changed the scope and the purpose of data management plans. Policy-makers, rather than scientists, have been instrumental in this development: "The first publications to provide general advice and guidance to researchers around the creation of DMPs were published from 2009 following the publications from JISC and the OECD (…) DMP use, we infer, has been imposed onto the research community through external forces" Empirical studies of data practices in research have "highlighted the need for organizations to offer more formal training and assistance in data management to scientists" In a 2017-2018 international survey of 1372 scientist, most requests for help and formalization were


id: open-scientific-data-20260505-10
file: data/en.wikipedia.org/wiki/Open_scientific_data-10.md
category: reference
title: Open scientific data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_scientific_data
date_saved: 2026-05-05T03:49:42.862927+00:00
instance: kb-cron
parent: open-scientific-data-20260505-0
summary:
The Unesco recommendation of Open Science approved in November 2021 defines open science infrastructures as "shared research infrastructures that are needed to support open science and serve the needs of different communities" Open science infrastructures have been recognized as a major factor in the implementation and the development of data sharing policies. Leading infrastructures for open scientific data include data repositories, data analysis platforms, indexes, digitized libraries, or digitized archives. Infrastructures ensure that individual researchers and institutions do not entirely support the costs of publishing, maintaining, and indexing datasets. They are also critical stakeholders in the definition and adoption of open data standards, especially regarding licensing or documentation. By the end of the 1990s, the creation of public scientific computing infrastructure became a major policy issue: "The lack of infrastructure to support release and reuse was acknowledged in some of the earliest policy reports on data sharing." The first wave of web-based scientific projects in the 1990s and the early 2000s revealed critical issues of sustainability. As funding was allocated on a specific period, critical databases, online tools or publishing platforms could hardly be maintained. Project managers were faced with a valley of death "between grant funding and ongoing operational


id: open-source-20260505-0
file: data/en.wikipedia.org/wiki/Open_source-0.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T03:49:44.361173+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
Open source is software that is made freely available for possible modification and redistribution, also in form of source code. The licensing conditions include permission to use and view the source code, design documents, or content of the product. The open source model is a decentralized software development model that encourages open collaboration. A main principle of open source software development is peer production, with products such as source code, blueprints, and documentation freely available to the public. The open source movement in software began as a response to the limitations of proprietary code. The model is used for projects such as in open source eCommerce, open source appropriate technology, and open source drug discovery. Open source promotes universal access via an open-source or free license to a product's design or blueprint, and universal redistribution of that design or blueprint. Before the phrase open source became widely adopted, developers and producers used a variety of other terms, such as free software, shareware, and public domain software. The term Open source was introduced in 1998 and gained hold with the rise of the Internet. The open-source software movement arose to clarify copyright, licensing, domain, and consumer issues. Generally, open source refers


id: open-source-20260505-1
file: data/en.wikipedia.org/wiki/Open_source-1.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T03:49:44.361173+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
Some economists agree that open-source is an information good or "knowledge good" with original work involving a significant amount of time, money, and effort. The cost of reproducing the work is low enough that additional users may be added at zero or near zero cost – this is referred to as the marginal cost of a product. Copyright creates a monopoly so that the price charged to consumers can be significantly higher than the marginal cost of production. This allows the author to recoup the cost of making the original work. Copyright thus creates access costs for consumers who value the work more than the marginal cost but less than the initial production cost. Access costs also pose problems for authors who wish to create a derivative work—such as a copy of a software program modified to fix a bug or add a feature, or a remix of a song—but are unable or unwilling to pay the copyright holder for the right to do so. Open source eliminates some of the access costs of consumers and creators of derivative works by reducing the restrictions of copyright. Basic economic theory predicts that lower costs would lead to higher consumption and also


id: open-source-20260505-2
file: data/en.wikipedia.org/wiki/Open_source-2.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T03:49:44.361173+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
The open-source model is a decentralized software development model that encourages open collaboration, meaning "any system of innovation or production that relies on goal-oriented yet loosely coordinated participants who interact to create a product (or service) of economic value, which they make available to contributors and noncontributors alike." A main principle of open-source software development is peer production, with products such as source code, blueprints, and documentation freely available to the public. The open-source movement in software began as a response to the limitations of proprietary code. The model is used for projects such as in open-source appropriate technology, and open-source drug discovery. The open-source model for software development inspired the use of the term to refer to other forms of open collaboration, such as in Internet forums, mailing lists and online communities. Open collaboration is also thought to be the operating principle underlining a gamut of diverse ventures, including TEDx and Wikipedia. Open collaboration is the principle underlying peer production, mass collaboration, and wikinomics. It was observed initially in open-source software, but can also be found in many other instances, such as in Internet forums, mailing lists, Internet communities, and many instances of open content, such as Creative Commons.


id: open-source-20260505-3
file: data/en.wikipedia.org/wiki/Open_source-3.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T03:49:44.361173+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
Linux (that much of world's server parks are running) MediaWiki (that Wikipedia is based upon) Many more: List of free and open-source software packages List of formerly proprietary software The Google Summer of Code, often abbreviated to GSoC, is an international annual program in which Google awards stipends to contributors who successfully complete a free and open-source software coding project during the summer. GSoC is a large scale project with 202 participating organizations in 2021. There are similar smaller scale projects such as the Talawa Project run by the Palisadoes Foundation (a non profit based in California, originally to promote the use of information technology in Jamaica, but now also supporting underprivileged communities in the US) === Electronics === Open-source hardware is hardware which initial specification, usually in a software format, is published and made available to the public, enabling anyone to copy, modify and redistribute the hardware and source code without paying royalties or fees. Open-source hardware evolves through community cooperation. These communities are composed of individual hardware/software developers, hobbyists, as well as very large companies. Examples of open-source hardware initiatives are: Openmoko: a family of open-source mobile phones, including the hardware specification and the operating system. OpenRISC: an


id: open-source-20260505-4
file: data/en.wikipedia.org/wiki/Open_source-4.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T03:49:44.361173+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
Open-source principles can be applied to technical areas such as digital communication protocols and data storage formats. Open-design – which involves applying open-source methodologies to the design of artifacts and systems in the physical world. It is very nascent but has huge potential. Open-source appropriate technology (OSAT) refers to technologies that are designed in the same fashion as free and open-source software. These technologies must be "appropriate technology" (AT) – meaning technology that is designed with special consideration to the environmental, ethical, cultural, social, political, and economic aspects of the community it is intended for. An example of this application is the use of open-source 3D printers like the RepRap to manufacture appropriate technology. Teaching – which involves applying the concepts of open source to instruction using a shared web space as a platform to improve upon learning, organizational, and management challenges. An example of an Open-source courseware is the Java Education & Development Initiative (JEDI). Other examples include Khan Academy and wikiversity. At the university level, the use of open-source-appropriate technology classroom projects has been shown to be successful in forging the connection between science/engineering and social benefit: This approach has the potential to use university students' access to


id: open-source-20260505-5
file: data/en.wikipedia.org/wiki/Open_source-5.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T03:49:44.361173+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
== Agriculture, economy, manufacturing and production == Open-source appropriate technology (OSAT), is designed for environmental, ethical, cultural, social, political, economic, and community aspects Open-design movement, development of physical products, machines and systems via publicly shared design information, including free and open-source software and open-source hardware, among many others: Open Architecture Network, improving global living conditions through innovative sustainable design OpenCores, a community developing digital electronic open-source hardware Open Design Alliance, develops Teigha, a software development platform to create engineering applications including CAD software Open Hardware and Design Alliance (OHANDA), sharing open hardware and designs via free online services Open Source Ecology (OSE), a network of farmers, engineers, architects and supporters striving to manufacture the Global Village Construction Set (GVCS) OpenStructures (OSP), a modular construction model where everyone designs on the basis of one shared geometrical OS grid Open manufacturing or "Open Production" or "Design Global, Manufacture Local", a new socioeconomic production model to openly and collaboratively produce and distribute physical objects Open-source architecture (OSArc), emerging procedures in imagination and formation of virtual and real spaces within an inclusive universal infrastructure Open-source cola, cola soft drinks made to open-sourced recipes Open-source hardware, or open hardware, computer hardware, such as microprocessors, that


id: open-source-20260505-6
file: data/en.wikipedia.org/wiki/Open_source-6.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T03:49:44.361173+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
== Society == The rise of open-source culture in the 20th century resulted from a growing tension between creative practices that involve require access to content that is often copyrighted, and restrictive intellectual property laws and policies governing access to copyrighted content. The two main ways in which intellectual property laws became more restrictive in the 20th century were extensions to the term of copyright (particularly in the United States) and penalties, such as those articulated in the Digital Millennium Copyright Act (DMCA), placed on attempts to circumvent anti-piracy technologies. Although artistic appropriation is often permitted under fair-use doctrines, the complexity and ambiguity of these doctrines create an atmosphere of uncertainty among cultural practitioners. Also, the protective actions of copyright owners create what some call a "chilling effect" among cultural practitioners. The idea of an "open-source" culture runs parallel to "Free Culture", but is substantively different. Free culture is a term derived from the free software movement, and in contrast to that vision of culture, proponents of open-source culture (OSC) maintain that some intellectual property law needs to exist to protect cultural producers. Yet they propose a more nuanced position than corporations have traditionally sought. Instead of seeing intellectual property


id: open-source-20260505-7
file: data/en.wikipedia.org/wiki/Open_source-7.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T03:49:44.361173+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
=== Media === Open-source journalism formerly referred to the standard journalistic techniques of news gathering and fact checking, reflecting open-source intelligence, a similar term used in military intelligence circles. Now, open-source journalism commonly refers to forms of innovative publishing of online journalism, rather than the sourcing of news stories by a professional journalist. In the 25 December 2006 issue of TIME magazine this is referred to as user created content and listed alongside more traditional open-source projects such as OpenSolaris and Linux. Weblogs, or blogs, are another significant platform for open-source culture. Blogs consist of periodic, reverse chronologically ordered posts, using a technology that makes webpages easily updatable with no understanding of design, code, or file transfer required. While corporations, political campaigns and other formal institutions have begun using these tools to distribute information, many blogs are used by individuals for personal expression, political organizing, and socializing. Some, such as LiveJournal or WordPress, use open-source software that is open to the public and can be modified by users to fit their own tastes. Whether the code is open or not, this format represents a nimble tool for people to borrow and re-present culture; whereas traditional websites made the illegal reproduction


id: open-source-20260505-8
file: data/en.wikipedia.org/wiki/Open_source-8.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T03:49:44.361173+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
Within the academic community, there is discussion about expanding what could be called the "intellectual commons" (analogous to the Creative Commons). Proponents of this view have hailed the Connexions Project at Rice University, OpenCourseWare project at MIT, Eugene Thacker's article on "open-source DNA", the "Open Source Cultural Database", Salman Khan's Khan Academy and Wikipedia as examples of applying open source outside the realm of computer software. Open-source curricula are instructional resources whose digital source can be freely used, distributed and modified. Another strand to the academic community is in the area of research. Many funded research projects produce software as part of their work. Due to the benefits of sharing software openly in scientific endeavours, there is an increasing interest in making the outputs of research projects available under an open-source license. In the UK the Joint Information Systems Committee (JISC) has developed a policy on open-source software. JISC also funds a development service called OSS Watch which acts as an advisory service for higher and further education institutions wishing to use, contribute to and develop open-source software. On 30 March 2010, President Barack Obama signed the Health Care and Education Reconciliation Act, which included $2 billion over four years


id: open-source-20260505-9
file: data/en.wikipedia.org/wiki/Open_source-9.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T03:49:44.361173+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
=== Ideologically-related movements === The open-access movement is a movement that is similar in ideology to the open source movement. Members of this movement maintain that academic material should be readily available to provide help with "future research, assist in teaching and aid in academic purposes." The open-access movement aims to eliminate subscription fees and licensing restrictions of academic materials. The free-culture movement is a movement that seeks to achieve a culture that engages in collective freedom via freedom of expression, free public access to knowledge and information, full demonstration of creativity and innovation in various arenas, and promotion of citizen liberties. Creative Commons is an organization that "develops, supports, and stewards legal and technical infrastructure that maximizes digital creativity, sharing, and innovation." It encourages the use of protected properties online for research, education, and creative purposes in pursuit of a universal access. Creative Commons provides an infrastructure through a set of copyright licenses and tools that creates a better balance within the realm of "all rights reserved" properties. The Creative Commons license offers a slightly more lenient alternative to "all rights reserved" copyrights for those who do not wish to exclude the use of their material. The Zeitgeist Movement


id: open-source-20260505-10
file: data/en.wikipedia.org/wiki/Open_source-10.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T03:49:44.361173+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
=== Literature on legal and economic aspects === Abramson, Bruce (2005). Digital Phoenix; Why the Information Economy Collapsed and How it Will Rise Again. MIT Press. ISBN 978-0-262-51196-4. Benkler, Y. (December 2002). "Coase's Penguin, or, Linux and The Nature of the Firm" (PDF). Yale Law Journal. 112 (3): 369–446. arXiv:cs/0109077. doi:10.2307/1562247. hdl:10535/2974. ISSN 0044-0094. JSTOR 1562247. S2CID 16684329. Berry, D.M.; Moss, G. (2008). "Libre Culture: Meditations on Free Culture" (PDF). Canada: Pygmalion Books. Bitzer, J.; Schröder, P.J.H. (2005). "The Impact of Entry and Competition by Open Source Software on Innovation Activity" (PDF). Industrial Organization. EconWPA. v. Engelhardt, S. (2008). "The Economic Properties of Software" (PDF). Jena Economic Research Papers. 2: 2008–045. v. Engelhardt, S. (2008): "Intellectual Property Rights and Ex-Post Transaction Costs: the Case of Open and Closed Source Software", Jena Economic Research Papers 2008-047. (PDF) v. Engelhardt, S.; Swaminathan, S. (2008). "Open Source Software, Closed Source Software or Both: Impacts on Industry Growth and the Role of Intellectual Property Rights" (PDF). Discussion Papers of Diw Berlin. European Commission. (2006). Economic impact of open source software on innovation and the competitiveness of the Information and Communication Technologies sector in the EU. Brussels. v. Hippel, E.; v. Krogh, G. (2003). "Open


id: open-synthetic-biology-20260505-0
file: data/en.wikipedia.org/wiki/Open_synthetic_biology-0.md
category: reference
title: Open synthetic biology
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_synthetic_biology
date_saved: 2026-05-05T03:49:45.513393+00:00
instance: kb-cron
parent: open-synthetic-biology-20260505-0
summary:
Open synthetic biology is the idea that scientific knowledge and data should be openly accessible through common rights licensing to enable the rapid development of safe, effective and commercially viable synthetic biology applications. == Concepts == Its foundational concepts are open science and the Bermuda Principles. Open science is the idea that scientific research should be openly shared to enable massive collaboration (e.g., the Polymath Project). The Bermuda Principles is a private accord declaring that all DNA sequence data should be released in publicly accessible databases within 24 hours after generation. Open synthetic biology is a theoretical framework supporting a global ecosystem of responsible and capable research scientists working collaboratively on synthetic biology application development projects to reduce cost, time, and risks of developing new synthetic biology applications (including open synthetic biology therapeutics) from the inception of primary science to applications reaching market readiness and commercial viability. Its general principle is that participating research scientists agree to share research, data, findings and results with the open synthetic biology community and the public generally. The Open SynBio community will set standards and expectations of the participants and their "science to market" process and the community will work collaboratively with downstream stakeholders


id: open-notebook-science-20260505-0
file: data/en.wikipedia.org/wiki/Open-notebook_science-0.md
category: reference
title: Open-notebook science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open-notebook_science
date_saved: 2026-05-05T03:49:46.721658+00:00
instance: kb-cron
parent: open-notebook-science-20260505-0
summary:
Open-notebook science is the practice of making the entire primary record of a research project publicly available online as it is recorded. This involves placing the personal, or laboratory, notebook of the researcher online along with all raw and processed data, and any associated material, as this material is generated. The approach may be summed up by the slogan 'no insider information'. It is the logical extreme of transparent approaches to research and explicitly includes the making available of failed, less significant, and otherwise unpublished experiments; so called 'dark data'. The practice of open notebook science, although not the norm in the academic community, has gained significant recent attention in the research and general media as part of a general trend towards more open approaches in research practice and publishing. Open notebook science can therefore be described as part of a wider open science movement that includes the advocacy and adoption of open access publication, open data, crowdsourcing data, and citizen science. It is inspired in part by the success of open-source software and draws on many of its ideas. == History == The term "open-notebook science" was first used in 2006 in a blog post by Jean-Claude Bradley, an


id: open-notebook-science-20260505-1
file: data/en.wikipedia.org/wiki/Open-notebook_science-1.md
category: reference
title: Open-notebook science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open-notebook_science
date_saved: 2026-05-05T03:49:46.721658+00:00
instance: kb-cron
parent: open-notebook-science-20260505-0
summary:
== Drawbacks == The arguments against adopting open notebook science fall mainly into three categories which have differing importance in different fields of science. The primary concern, expressed particularly by biological and medical scientists is that of 'data theft' or 'being scooped'. While the degree to which research groups steal or adapt the results of others remains a subject of debate it is certainly the case that the fear of not being first to publish drives much behavior, particularly in some fields. This is related to the focus in these fields on the published peer-reviewed paper as being the main metric of career success. The second argument advanced against open notebook science is that it constitutes prior publication, thus making it impossible to patent and difficult to publish the results in the traditional peer reviewed literature. With respect to patents, publication on the web is clearly classified as disclosure. Therefore, while there may be arguments over the value of patents, and approaches that get around this problem, it is clear that open notebook science is not appropriate for research for which patent protection is an expected and desired outcome. With respect to publication in the peer-reviewed literature the case is


id: openbci-20260505-0
file: data/en.wikipedia.org/wiki/OpenBCI-0.md
category: reference
title: OpenBCI
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/OpenBCI
date_saved: 2026-05-05T03:49:47.934225+00:00
instance: kb-cron
parent: openbci-20260505-0
summary:
OpenBCI is an open-source brain–computer interface platform created by Joel Murphy and Conor Russomanno, after a successful Kickstarter campaign in late 2013. The company's headquarters is based in Brooklyn, NY. OpenBCI boards are low-cost biometric amplifiers used to measure and record electrical activity produced by the brain (EEG), muscles (EMG), and heart (EKG). The boards are compatible with standard EEG electrodes. They can be used with the open-source OpenBCI GUI software, or they can be integrated with other open-source EEG signal processing tools. OpenBCI boards have been scientifically validated in numerous research studies. == Hardware == The OpenBCI 32-bit board uses the ADS1299, an IC developed by Texas Instruments for biopotential measurements. The OpenBCI uses a microcontroller for on-board processing — the 8bit version (now deprecated) uses an Arduino-compatible ATmega328P IC, while the 32bit board uses a PIC microcontroller — and can write the EEG data to an SD card, or transmit it to software on a computer over a bluetooth link. In 2015, OpenBCI announced the Ganglion board with a 2nd Kickstarter campaign. It has 4 input channels for measuring EEG, EMG, and EKG, and is also Bluetooth enabled. Initially it was offered on Kickstarter at $99, before later


id: opencitations-20260505-0
file: data/en.wikipedia.org/wiki/OpenCitations-0.md
category: reference
title: OpenCitations
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/OpenCitations
date_saved: 2026-05-05T03:49:53.403939+00:00
instance: kb-cron
parent: opencitations-20260505-0
summary:
OpenCitations (established in 2010) is a project aiming to publish open bibliographic citation information in RDF. It produces the "OpenCitations Corpus" citation database in the process. == Datasets == OpenCitations publishes the following datasets which encompass bibliographic data, citation metadata, and in-text reference data. The datasets can be accessed via SPARQL, a REST API, as dumps on Figshare, as individual bibliographic entities, or using OSCAR (OpenCitations RDF Search Application) or Lucinda (The OpenCitations RDF Resource Browser). === OpenCitations Corpus === The OpenCitations Corpus (OCC) is an open repository of scholarly citation data. The repository is released under the CC0 public domain to ensure that the scholarly citation data is open to all. As of March 19, 2022, the OCC has ingested the references from 326,743 citing bibliographic resources and contains information about 13,964,148 citation links to 7,565,367 cited resources. === OpenCitations Indexes === The OpenCitations Indexes are collections of citations, which treat citations as first-class data objects that include citation metadata, as well as identifiers to the citing and cited works. For example, COCI is the OpenCitations Index of Crossref open DOI-to-DOI citations. A 2021 comparison with other citations tools found that COCI was the smallest in coverage, and a


id: openneuro-20260505-0
file: data/en.wikipedia.org/wiki/OpenNeuro-0.md
category: reference
title: OpenNeuro
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/OpenNeuro
date_saved: 2026-05-05T03:49:54.647190+00:00
instance: kb-cron
parent: openneuro-20260505-0
summary:
OpenNeuro (originally OpenfMRI) is an open-science neuroinformatics database storing datasets from human brain imaging research studies. The database is available online. OpenNeuro accepts datasets formatted from brain imaging research according to a community-developed standard, and uploaded datasets are made available with minimal restrictions to the public at large. The Research Resource Identifier for OpenNeuro is SCR_005031. Datasets that cannot be shared openly are not currently supported. The research group that runs OpenNeuro described the system in a Frontiers in Neuroinformatics article in 2013 and a NeuroImage article in 2015. As of 2025, the National Institutes of Health has awarded OpenNeuro over 8 million dollars in research funding, and researchers have mentioned OpenNeuro in over 200 articles in open access literature. == History == The Neuroimaging Informatics Tools and Resources Clearinghouse made available two other online neuroimaging databases, which both predated OpenNeuro. One was the fMRI Data Center (fMRIDC), which collected similar data but distributed via physical media. The fMRIDC no longer accepts data submissions. The other repository was the 1000 Functional Connectomes Project, which collected data from resting-state fMRI studies. In February 2018, the research group behind OpenfMRI renamed the database to OpenNeuro to reflect broader range of accepted data


id: openworm-20260505-0
file: data/en.wikipedia.org/wiki/OpenWorm-0.md
category: reference
title: OpenWorm
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/OpenWorm
date_saved: 2026-05-05T03:49:55.963108+00:00
instance: kb-cron
parent: openworm-20260505-0
summary:
OpenWorm is an international open science project for the purpose of simulating the roundworm Caenorhabditis elegans at the cellular level. Although the long-term goal is to model all 959 cells of the C. elegans, the first stage is to model the worm's locomotion by simulating the 302 neurons and 95 muscle cells. This bottom up simulation is being pursued by the OpenWorm community. As of 2014, a physics engine called Sibernetic has been built for the project and models of the neural connectome and a muscle cell have been created in NeuroML format. A 3D model of the worm anatomy can be accessed through the web via the OpenWorm browser. The OpenWorm project is also contributing to develop Geppetto, a web-based multi-algorithm, multi-scale simulation platform engineered to support the simulation of the whole organism. == Background: C. elegans == The roundworm Caenorhabditis elegans is a free-living, transparent nematode, about 1 mm in length, that lives in temperate soil environments. It is the type species of its genus. C. elegans has one of the simplest nervous systems of any organism - its hermaphrodite type possesses only 302 neurons. Furthermore, the structural connectome of these neurons is fully mapped. There are fewer


id: panton-principles-20260505-0
file: data/en.wikipedia.org/wiki/Panton_Principles-0.md
category: reference
title: Panton Principles
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Panton_Principles
date_saved: 2026-05-05T03:49:57.291746+00:00
instance: kb-cron
parent: panton-principles-20260505-0
summary:
The Panton Principles are a set of principles which were written to promote open science. They were first drafted in July 2009 at the Panton Arms pub in Cambridge. == History == The principles were written by Peter Murray-Rust, Cameron Neylon, Rufus Pollock, and John Wilbanks. They were then refined by the Open Knowledge Foundation and officially launched in February 2010. == The Principles == 1. Where data or collections of data are published it is critical that they be published with a clear and explicit statement of the wishes and expectations of the publishers concerning the re-use and re-purposing of individual data elements, the whole data collection, and subsets of the collection. This statement should be precise, irrevocable, and based on an appropriate and recognized legal statement in the form of a waiver or license. When publishing data make an explicit and robust statement of your wishes. 2. Many widely recognized licenses are not intended for, and are not appropriate for, data or collections of data. A variety of waivers and licenses that are designed for and appropriate for the treatment of data are described here. Creative Commons licenses (apart from CCZero), GFDL, GPL, BSD, etc. are NOT appropriate


id: polymath-project-20260505-0
file: data/en.wikipedia.org/wiki/Polymath_Project-0.md
category: reference
title: Polymath Project
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Polymath_Project
date_saved: 2026-05-05T03:49:58.411121+00:00
instance: kb-cron
parent: polymath-project-20260505-0
summary:
The Polymath Project is a collaboration among mathematicians to solve important and difficult mathematical problems by coordinating many mathematicians to communicate with each other on finding the best route to the solution. The project began in January 2009 on Timothy Gowers's blog when he posted a problem and asked his readers to post partial ideas and partial progress toward a solution. This experiment resulted in a new answer to a difficult problem, and since then the Polymath Project has grown to describe a particular crowdsourcing process of using an online collaboration to solve any math problem. == Origin == In January 2009, Gowers chose to start a social experiment on his blog by choosing an important unsolved mathematical problem and issuing an invitation for other people to help solve it collaboratively in the comments section of his blog. Along with the math problem itself, Gowers asked a question which was included in the title of his blog post, "is massively collaborative mathematics possible?" This post led to his creation of the Polymath Project. == Projects for high school and college == Since its inception, it has now sponsored a "Crowdmath" project in collaboration with MIT PRIMES program and the Art


id: polymath-project-20260505-1
file: data/en.wikipedia.org/wiki/Polymath_Project-1.md
category: reference
title: Polymath Project
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Polymath_Project
date_saved: 2026-05-05T03:49:58.411121+00:00
instance: kb-cron
parent: polymath-project-20260505-0
summary:
== Publications == Polymath, D. H. J. (2010), "Density Hales-Jewett and Moser numbers", An irregular mind, Bolyai Soc. Math. Stud., vol. 21, János Bolyai Math. Soc., Budapest, pp. 689–753, arXiv:1002.0374, doi:10.1007/978-3-642-14444-8_22, ISBN 978-3-642-14443-1, MR 2815620, S2CID 15547977. From the Polymath1 project. Polymath, D. H. J. (2012), "A new proof of the density Hales-Jewett theorem", Annals of Mathematics, Second Series, 175 (3): 1283–1327, arXiv:0910.3926, doi:10.4007/annals.2012.175.3.6, MR 2912706, S2CID 60078. From the Polymath1 project. Tao, Terence; Croot, Ernest III; Helfgott, Harald (2012), "Deterministic methods to find primes", Mathematics of Computation, 81 (278): 1233–1246, arXiv:1009.3956, doi:10.1090/S0025-5718-2011-02542-1, MR 2869058. From the Polymath4 project. Although the journal editors required the authors to use their real names, the arXiv version uses the Polymath pseudonym. Polymath, D. H. J. (2014), "New equidistribution estimates of Zhang type", Algebra & Number Theory, 9 (8): 2067–2199, arXiv:1402.0811, Bibcode:2014arXiv1402.0811P, doi:10.2140/ant.2014.8.2067. From the Polymath8 project. Polymath, D.H.J. (2014), "Variants of the Selberg sieve, and bounded intervals containing many primes", Research in the Mathematical Sciences, 1 (12) 12, arXiv:1407.4897, Bibcode:2014arXiv1407.4897P, doi:10.1186/s40687-014-0012-7, MR 3373710, S2CID 119699189 From the Polymath8 project. Polymath, D. H. J. (2014), "The "bounded gaps between primes" Polymath project: A retrospective analysis" (PDF), Newsletter of the European Mathematical Society, 94: 13–23,


id: preprints-org-20260505-0
file: data/en.wikipedia.org/wiki/Preprints.org-0.md
category: reference
title: Preprints.org
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Preprints.org
date_saved: 2026-05-05T03:49:59.555487+00:00
instance: kb-cron
parent: preprints-org-20260505-0
summary:
Preprints.org is an open-access platform of electronic preprints approved for posting after moderation. Research in various areas can be posted as preprints on Preprints.org, including manuscripts from all fields of research. Preprints was established by MDPI in 2016. As of March 2026, Preprints.org contains more than 124,000 preprints. == Abstracting and indexing == As of May 2023, preprints posted on Preprints.org appear in: Web of Science (Preprint Citation Index) Europe PMC Crossref Google Scholar PrePubMed Portico == See also == List of academic databases and search engines List of academic journals by preprint policy Open-access repository List of preprint repositories == References ==


id: pubpeer-20260505-0
file: data/en.wikipedia.org/wiki/PubPeer-0.md
category: reference
title: PubPeer
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/PubPeer
date_saved: 2026-05-05T03:50:02.187200+00:00
instance: kb-cron
parent: pubpeer-20260505-0
summary:
PubPeer is a website that allows users to discuss and review scientific research after publication, i.e. post-publication peer review, established in 2012. The site has served as a whistleblowing platform, in that it highlighted shortcomings in several high-profile papers, in some cases leading to retractions and to accusations of scientific fraud, as noted by Retraction Watch. Contrary to most platforms, it allows anonymous post-publication commenting, a controversial feature which is the main factor for its success. Consequently, accusations of libel have been levelled at some of PubPeer's users; correspondingly the website has since 2016 told commentators to use only facts that can be publicly verified. Questions have been raised about the copyright ownership of PubPeer's often-anonymous contents. In 2021 a study found that "more than two-thirds of comments [on PubPeer] are posted to report some type of misconduct, mainly about image manipulation". Health sciences and life sciences were shown to have most comments, and most comments reporting publishing fraud and data manipulation. Social science and humanities disciplines in turn had fewer comments, but the highest percentage comments about critical reviews about theory and highlight methodological flaws. The research concluded that "while biochemists access the site to report misconduct... social scientists


id: pubref-org-20260505-0
file: data/en.wikipedia.org/wiki/PubRef.org-0.md
category: reference
title: PubRef.org
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/PubRef.org
date_saved: 2026-05-05T03:50:03.374654+00:00
instance: kb-cron
parent: pubref-org-20260505-0
summary:
PubRef.org was a short lived project that is now discontinued. The website is not accessible anymore. An old version can be accessed from the Internet Archive. They used the same name PubRef which was a service provided by PubMed for linking bibliographies, defeated by the independent service Crossref. PubRef was a composition and project management application used by researchers and students for scholarly writing and communication. PubRef uses an extended form of Markdown as a primary authoring format and converts this to JATS, the archive format used by the US National Library of Medicine. == Research asset containerization == Researchers manage scholarly writing projects within version-controlled file repositories called containers that function similarly to git repositories and docker containers to provide enhanced reproducibility, transparency and re-usability in digital science publishing. == Manuscript writing == A PubRef manuscript is a Markdown file within a container that contains extra embedded information that describes the essential front matter elements of a scholarly manuscript such as the title, short title, list of authors, author affiliations, key words. This information is captured in embedded YAML blocks within the primary manuscript called Meta. Figures, tables, equations and other special content can be similarly embedded within the


id: registry-of-research-data-repositories-20260505-0
file: data/en.wikipedia.org/wiki/Registry_of_Research_Data_Repositories-0.md
category: reference
title: Registry of Research Data Repositories
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Registry_of_Research_Data_Repositories
date_saved: 2026-05-05T03:50:04.585151+00:00
instance: kb-cron
parent: registry-of-research-data-repositories-20260505-0
summary:
The Registry of Research Data Repositories (re3data.org) is an open science tool that offers researchers, funding organizations, libraries, and publishers an overview of existing international repositories for research data. == Background == re3data.org is a global registry of research data repositories from all academic disciplines. It provides an overview of existing research data repositories in order to help researchers to identify a suitable repository for their data and thus comply with requirements set out in data policies. The registry went live in autumn 2012. == Content == In 2023 the registry lists over 3000 research data repositories from around the world covering all academic disciplines. They are described in detail using the re3data.org schema. The service makes all metadata in the registry available for open use under the Creative Commons deed CC0. == Features == The majority of the listed research data repositories are described in detail by a comprehensive schema, namely the re3data.org Schema for the Description of Research Data Repositories. Information icons support researchers to identify an adequate repository for the storage and reuse of their data. == Inclusion criteria == A repository is indexed when the minimum requirements for inclusion in re3data.org are met: the repository has


id: reinventing-discovery-20260505-0
file: data/en.wikipedia.org/wiki/Reinventing_Discovery-0.md
category: reference
title: Reinventing Discovery
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Reinventing_Discovery
date_saved: 2026-05-05T03:50:09.310809+00:00
instance: kb-cron
parent: reinventing-discovery-20260505-0
summary:
Reinventing Discovery: The New Era of Networked Science is a book written by Michael Nielsen and released in October 2011. It argues for the benefits of applying the philosophy of open science to research. == Summary == The following is a list of major topics in the book's chapters. Reinventing Discovery Online Tools Make Us Smarter Kasparov versus the World, The Wisdom of Crowds, various online collaborative projects Restructuring Expert Attention InnoCentive, collective intelligence, Paul Seabright's economic theory, online chat Patterns of Online Collaboration History of Linux, Open Architecture Network, Wikipedia, MathWorks' computer programming contest The Limits and the Potential of Collective Intelligence communication in small groups, particularly as studied by Stasser and Titus; praxis of science; a discussion of communication among scientists All the World's Knowledge Don R. Swanson and Literature-based discovery, predicting influenza with Google searches, Sloan Digital Sky Survey, Allen Institute for Brain Science, Ocean Observatories Initiative, Human Genome Project, Google Translate, playchess.com Tournaments Democratizing Science Galaxy Zoo, Foldit, citizen science, eBird, open access, arXiv, PLoS The Challenge of Doing Science in the Open Complexity Zoo, academic publishing, Bayh–Dole Act The Open Science Imperative Open science, academic journal publishing reform, SPIRES appendix - The problem solved by


id: research-square-20260505-0
file: data/en.wikipedia.org/wiki/Research_Square-0.md
category: reference
title: Research Square
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research_Square
date_saved: 2026-05-05T03:50:10.466168+00:00
instance: kb-cron
parent: research-square-20260505-0
summary:
Research Square is an open-access platform of electronic preprints approved for posting after moderation, but not peer review. The predecessor of Research Square was American Journal Experts. The platform, Research Square, was established in 2013 and acquired by Springer Nature in 2022. The server accepts submissions from all fields of research, such as physical, biomedical, and social sciences. As of May 2023, Research Square contains more than 223,000 preprints. Pre-prints uploaded to Research Square must have a CC-BY license. If it was uploaded elsewhere under a different license (eg. CC-BY-SA) it would violate the terms of that license. == See also == List of academic databases and search engines List of academic journals by preprint policy Open-access repository List of preprint repositories == References ==


id: research-transparency-20260505-0
file: data/en.wikipedia.org/wiki/Research_transparency-0.md
category: reference
title: Research transparency
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research_transparency
date_saved: 2026-05-05T03:50:11.648451+00:00
instance: kb-cron
parent: research-transparency-20260505-0
summary:
Research transparency is a major aspect of scientific research. It covers a variety of scientific principles and practices: reproducibility, data and code sharing, citation standards or verifiability. The definitions and norms of research transparency significantly differ depending on the disciplines and fields of research. Due to the lack of consistent terminology, research transparency has frequently been defined negatively by addressing non-transparent usages (which are part of questionable research practices). After 2010, recurrent issues of research methodology have been increasingly acknowledged as structural crisis, that involve deep changes at all stages of the research process. Transparency has become a key value of the open science movement, which evolved from an initial focus on publishing to encompass a large diversity of research outputs. New common standards for research transparency, like the TOP Guidelines, aims to build and strengthen open research culture across disciplines and epistemic cultures. == Definitions == === Confused terminologies === There is no widespread consensus on the definition of research transparency. Differences between disciplines and epistemic cultures has largely contributed to different acceptions. The reproduction of past research has been a leading source of dissent. In an experimental setting, reproduction relies on the same set-up and apparatus, while replication


id: research-transparency-20260505-1
file: data/en.wikipedia.org/wiki/Research_transparency-1.md
category: reference
title: Research transparency
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research_transparency
date_saved: 2026-05-05T03:50:11.648451+00:00
instance: kb-cron
parent: research-transparency-20260505-0
summary:
=== A new dimension of open science? === Transparency has been increasingly acknowledged as an important component of open science. Until the 2010s, definitions of open science have been mostly focused on technical access and enhanced participation and collaboration between academics and non-academics. In 2016, Liz Lyon identified transparency as a "third dimension" of open science, due to the fact that "the concept of transparency and the associated term 'reproducibility', have become increasingly important in the current interdisciplinary research environment." According to Kevin Elliott, the open science movement "encompasses a number of different initiatives aimed at somewhat different forms of transparency." First drafted in 2014, the TOP guidelines have significantly contributed to bring transparency on the agenda of the open science movements. They aim to promote an "open research culture" and implement "strong incentives to be more transparent". They rely on eight standards, with different levels of compliance. While the standards are modular, they also aim to articulate a consistent ethos of science as "they also complement each other, in that commitment to one standard may facilitate adoption of others.". This open science framework of transparency has been in turn coopted by leading contributors and institutions on the topic of


id: research-transparency-20260505-2
file: data/en.wikipedia.org/wiki/Research_transparency-2.md
category: reference
title: Research transparency
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research_transparency
date_saved: 2026-05-05T03:50:11.648451+00:00
instance: kb-cron
parent: research-transparency-20260505-0
summary:
=== Preconditions of the transparency crisis (1945–2000) === The development of big science after the Second World War has created unprecedented challenges for research transparency. The generalization of statistical methods across a large number of fields, as well as the increasing breadth and complexity of research projects, entailed a series of concerns about the lack of proper documentation of the scientific process. Due to the expansion of the published research output, new quantitative methods for literature surveys have been developed under the label of meta-analysis or meta-science. These rely on the assumption that quantitative results and the details of the experimental and observational framework are sound (such as the size or the composition of the sample). In 1966, Stanley Schor and Irving Karten published one of the first generic evaluation of statistical methods in 67 leading medical journals. While few outright problematic papers were found, "in almost 73% of the reports read (those needing revision and those which should have been rejected), conclusions were drawn when the justification for these conclusions was invalid" In the 1970s and the 1980s, scientific misconducts gradually ceased to be presented as individual misconducts and became collective problems that need to be addressed by scientific


id: research-transparency-20260505-3
file: data/en.wikipedia.org/wiki/Research_transparency-3.md
category: reference
title: Research transparency
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research_transparency
date_saved: 2026-05-05T03:50:11.648451+00:00
instance: kb-cron
parent: research-transparency-20260505-0
summary:
=== Research transparency and open science (2015–) === Since 2000, the open science movement has expanded beyond access to scientific outputs (publication, data or software) to encompass the entire process of scientific production. In 2018, Vicente-Saez and Martinez-Fuentes have attempted to map the common values shared by the standard definitions of open science in the English-speaking scientific literature indexed on Scopus and the Web of Science. Access is no longer the main dimension of open science, as it has been extended by more recent commitments toward transparency, collaborative work and social impact. Through this process, open science has been increasingly structured over a consisting set of ethical principles: "novel open science practices have developed in tandem with novel organising forms of conducting and sharing research through open repositories, open physical labs, and transdisciplinary research platforms. Together, these novel practices and organising forms are expanding the ethos of science at universities." The global scale of the open science movement and its integration in a large variety of technical tools, standards and regulations makes it possible to overcome the "classic collective action problem" embodied by research transparency: there is a structural discrepancy between the stated objective of scientific institutions and the lack


id: research-transparency-20260505-4
file: data/en.wikipedia.org/wiki/Research_transparency-4.md
category: reference
title: Research transparency
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research_transparency
date_saved: 2026-05-05T03:50:11.648451+00:00
instance: kb-cron
parent: research-transparency-20260505-0
summary:
==== Result reproducibility ==== Goodman, Fanelli and Ioannidis define result reproducibility as "obtaining the same results from the conduct of an independent study whose procedures are as closely matched". Result reproducibility is comparable to replication in an experimental context and reproducibility in a computational context. The definition of replicability retained in the National Academies of Science, largely applies to it: "obtaining consistent results across studies aimed at answering the same scientific question, each of which has obtained its own data.". The reproducibility crisis met in experimental disciplines like psychology or medicine is mostly a crisis of "result reproducibility", since it concerns research that cannot been simply re-executed, but involve the independent recreation of the experimental design. As such it is arguably the most debated form of research transparency in the recent years. Result reproducibility is harder to achieve than other forms of research transparency. It involve a variety of issues that may include computational reproducibility, accuracy of scientific measurement and diversity of methodological approaches. There are no universal standard to determine how close are the original procedures matched and criterium may vary depending on the disciplines or, even on the field of research. Consequently, meta-analysis of reproducibility have faced significant


id: research-transparency-20260505-5
file: data/en.wikipedia.org/wiki/Research_transparency-5.md
category: reference
title: Research transparency
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research_transparency
date_saved: 2026-05-05T03:50:11.648451+00:00
instance: kb-cron
parent: research-transparency-20260505-0
summary:
=== Sharing of research outputs === Data sharing has been early on identified as major potential solution to the reproducibility crisis and the lack of solid guidelines for statistical indicators. In 2005, John Ioannidis hypothesized that "some kind of registration or networking of data collections or investigators within fields may be more feasible than registration of each and every hypothesis-generating experiment." The sharing of research outputs is covered by three standards of the TOPs guidelines: on Data transparency (2), Analytic/code methods transparency (3) and Research materials transparency (4). All the relevant data, code and research materials are to be stored on a "trusted repository" and all analysis being already reproduced independently prior to publication. === Extended citation standards === While citation standards are commonly applied to academic reference, there is much less formalization for all the other research output, such as data, code, primary sources or qualitative assessments. In 2012, the American Political Science Association adopted new policies for open qualitative research. They covered three dimensions of transparency: data transparency (in the sense of precise bibliographic data to the original sources), analytic transparency (in regards to claims extrapolated from the cited sources) and production transparency (in reference to the editorial


id: sage-bionetworks-20260505-0
file: data/en.wikipedia.org/wiki/Sage_Bionetworks-0.md
category: reference
title: Sage Bionetworks
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Sage_Bionetworks
date_saved: 2026-05-05T03:50:12.893436+00:00
instance: kb-cron
parent: sage-bionetworks-20260505-0
summary:
Sage Bionetworks is a nonprofit organization in Seattle that promotes open science and patient engagement in the research process. It is led by Luca Foschini. It was co-founded by Stephen Friend and Eric Schadt. == Open science == Sage Bionetworks is notable for being an early advocate of open science. The company operates a software platform for collaborative data analysis called Synapse that allows researchers to work together on data curation and computational modeling asynchronously in a manner inspired by GitHub. Synapse also serves as the software infrastructure for running computational challenges. Sage is also developing a citizen-science platform called Bridge. == Research == The bulk of Sage's scientific results emerge from cancer and neurosciences, with notable contributions to the Cancer Genome Atlas Pan-Cancer project. Another Sage initiative, The Resilience Project describes itself as a search for individuals who have genetic changes expected to cause severe illness but who remain perfectly healthy. The hope is to yield insight into factors that protect these individuals from disease. In 2019 Sage Bionetworks has joined Open-AD Drug Discovery Center, which aims to find new Alzheimer's drugs. “This project stitches together open science approaches in computational and experimental research,” Sage president Dr. Lara Mangravite


id: science-2-0-20260505-0
file: data/en.wikipedia.org/wiki/Science_2.0-0.md
category: reference
title: Science 2.0
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Science_2.0
date_saved: 2026-05-05T03:50:15.406926+00:00
instance: kb-cron
parent: science-2-0-20260505-0
summary:
Science 2.0 is a suggested new approach to science that uses information-sharing and collaboration made possible by network technologies. It is similar to the open research and open science movements and is inspired by Web 2.0 technologies. Science 2.0 stresses the benefits of increased collaboration between scientists. Science 2.0 uses collaborative tools like wikis, blogs and video journals to share findings, raw data and "nascent theories" online. Science 2.0 benefits from openness and sharing, regarding papers and research ideas and partial solutions. A general view is that Science 2.0 is gaining traction with websites beginning to proliferate, yet at the same time there is considerable resistance within the scientific community about aspects of the transition as well as discussion about what, exactly, the term means. There are several views that there is a "sea change" happening in the status quo of scientific publishing, and substantive change regarding how scientists share research data. There is considerable discussion in the scientific community about whether scientists should embrace the model and exactly how Science 2.0 might work, as well as several reports that many scientists are slow to embrace collaborative methods and are somewhat "inhibited and slow to adopt a lot of online


id: science-2-0-20260505-1
file: data/en.wikipedia.org/wiki/Science_2.0-1.md
category: reference
title: Science 2.0
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Science_2.0
date_saved: 2026-05-05T03:50:15.406926+00:00
instance: kb-cron
parent: science-2-0-20260505-0
summary:
Before the Internet, scientific publishing has been described as a "highly integrated and controlled process." Research was done in private. Next, it was submitted to scientific publications and reviewed by editors and gatekeepers and other scientists. Last, it was published. This has been the traditional pathway of scientific advancement, sometimes dubbed Science 1.0. Established journals provided a "critical service", according to one view. Publications such as Science and Nature have large editorial staffs to manage the peer-review process as well as have hired fact-checkers and screeners to look over submissions. These publications get revenue from subscriptions, including online ones, as well as advertising revenue and fees paid by authors. According to advocates of Science 2.0, however, this process of paper-submission and review was rather long. Detractors complained that the system is "hidebound, expensive and elitist", sometimes "reductionist", as well as being slow and "prohibitively costly". Only a select group of gatekeepers—those in charge of the traditional publications—limited the flow of information. Proponents of open science claimed that scientists could learn more and learn faster if there is a "friction-free collaboration over the Internet." Yet there is considerable resistance within the scientific community to a change of approach. The act of


id: science-2-0-20260505-2
file: data/en.wikipedia.org/wiki/Science_2.0-2.md
category: reference
title: Science 2.0
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Science_2.0
date_saved: 2026-05-05T03:50:15.406926+00:00
instance: kb-cron
parent: science-2-0-20260505-0
summary:
Public Library of Science. This project, sometimes termed PLoS, is a nonprofit open-access scientific publishing project aimed at creating a library of open access journals and other scientific literature under an open content license. By 2012, it publishes seven peer reviewed journals. It makes scientific papers immediately available online without charges for access or restrictions on passing them along, provided that the authors and sources are properly cited with the Creative Commons Attribution License. According to one report, the PLoS has gained "pretty wide acceptance" although many researchers in biomedicine still hope to be published in established journals such as Nature, Cell, and Science, according to one report. PLoS publishes 600 articles a month in 2012. arXiv, pronounced archive, is an online-accessible archive for electronic preprints of scientific papers in the fields of mathematics, physics, astronomy, computer science, quantitative biology, statistics, and quantitative finance. Galaxy Zoo is an online astronomy project which invites members of the public to assist in the morphological classification of large numbers of galaxies. It has been termed a citizen science project. The information has led to a substantial increase in scientific papers, according to one account. A website entitled Science 2.0 lets scientists share information.


id: science-commons-20260505-0
file: data/en.wikipedia.org/wiki/Science_Commons-0.md
category: reference
title: Science Commons
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Science_Commons
date_saved: 2026-05-05T03:50:16.566072+00:00
instance: kb-cron
parent: science-commons-20260505-0
summary:
Science Commons (SC) was a Creative Commons project for designing strategies and tools for faster, more efficient web-enabled scientific research. The organization's goals were to identify unnecessary barriers to research, craft policy guidelines and legal agreements to lower those barriers, and develop technology to make research data and materials easier to find and use. Its overarching goal was to speed the translation of data into discovery and thereby the value of research. Science Commons was located at the MIT Computer Science and Artificial Intelligence Laboratory in the Ray and Maria Stata Center at the Massachusetts Institute of Technology in Cambridge, Massachusetts. == History == Creative Commons launched the Science Commons project in early 2005. The project sought to achieve for science what Creative Commons had achieved for the world of culture, art and educational material: to ease unnecessary legal and technical barriers to sharing, to promote innovation, and to provide easy, high quality tools that let individuals and organizations specify the terms under which they wished to share their material. In 2009, Creative Commons terminated the Science Commons project. == Projects == === Biological Materials Transfer Project === The Biological Materials Transfer Project, a Material transfer agreement (MTA), developed and


id: studierfenster-20260505-0
file: data/en.wikipedia.org/wiki/Studierfenster-0.md
category: reference
title: Studierfenster
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Studierfenster
date_saved: 2026-05-05T03:50:17.856104+00:00
instance: kb-cron
parent: studierfenster-20260505-0
summary:
Studierfenster or StudierFenster (SF) is a free, non-commercial open science client/server-based medical imaging processing online framework. It offers capabilities, like viewing medical data (computed tomography (CT), magnetic resonance imaging (MRI), etc.) in two- and three-dimensional space directly in the standard web browsers, like Google Chrome, Mozilla Firefox, Safari, and Microsoft Edge. Other functionalities are the calculation of medical metrics (dice score and Hausdorff distance), manual slice-by-slice outlining of structures in medical images (segmentation), manual placing of (anatomical) landmarks in medical image data, viewing medical data in virtual reality, a facial reconstruction and registration of medical data for augmented reality, one click showcases for COVID-19 and veterinary scans, and a Radiomics module. Other features of Studierfenster are the automatic cranial implant design with a neural network, the inpainting of aortic dissections with a generative adversarial network, an automatic aortic landmark detection with deep learning in computed tomography angiography scans, and a GrowCut algorithm implementation for image segmentation. Studierfenster is currently hosted on a server at the Graz University of Technology in Austria, and expanded jointly with the Institute for Artificial Intelligence in Medicine (IKIM) in Essen, Germany. == History == Studierfenster was initiated within two bachelor theses during the summer bachelor


id: synapse-org-20260505-0
file: data/en.wikipedia.org/wiki/Synapse.org-0.md
category: reference
title: Synapse.org
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Synapse.org
date_saved: 2026-05-05T03:50:19.083216+00:00
instance: kb-cron
parent: synapse-org-20260505-0
summary:
Synapse.org is an open source platform for collaborative scientific data analysis. It can store data, code, results, and descriptions research work. It is operated by nonprofit organization Sage Bionetworks. The Synapse web portal is an online registry of research projects that allows data scientists to discover and share data, models, and analysis methods. == References ==


id: target-2035-20260505-0
file: data/en.wikipedia.org/wiki/Target_2035-0.md
category: reference
title: Target 2035
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Target_2035
date_saved: 2026-05-05T03:50:20.289609+00:00
instance: kb-cron
parent: target-2035-20260505-0
summary:
Target 2035 is a global effort or movement to discover open science, pharmacological modulator(s) for every protein in the human proteome by the year 2035. The effort is led by the Structural Genomics Consortium with the intention that this movement evolves organically. Target 2035 has been borne out of the success that chemical probes have had in elevating or de-prioritizing the therapeutic potential of protein targets. The availability of open access pharmacological tools is a largely unmet aspect of drug discovery especially for the dark proteome. The first five years will include building mechanisms (Phase 1 below) which allow researchers to find collaborators with like-minded goals towards discovering a pharmacological tool for a specific protein or protein family, and make it open access (without encumbrances due to intellectual property). One strategic goal is seeding new open science programs on components of the drug discovery pipeline with the goal to bring medicines to the bedside equitably, affordably and rapidly. Phase 1 will also build a framework that welcomes new and (re-)emerging enabling technologies in hit-finding and characterization. An update on the progress was published. Target 2035 will draw on successes from past and current publicly-funded programs including National Institutes of Health


id: jon-tennant-20260505-0
file: data/en.wikipedia.org/wiki/Jon_Tennant-0.md
category: reference
title: Jon Tennant
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Jon_Tennant
date_saved: 2026-05-05T03:50:25.671137+00:00
instance: kb-cron
parent: jon-tennant-20260505-0
summary:
Jonathan Tennant (6 May 1988 – 9 April 2020) was an English open science activist, science communicator and vertebrate paleontologist. == Early life and paleontology == Tennant was born in 1988 in Kirby Muxloe, Leicestershire. His first 18 years were in Leicester with his parents and two sisters, Rebecca and Sarah. Jon attended Granby Primary School, Bushloe High School and then Beauchamp College. He obtained a PhD from Imperial College London in 2017, on a potential extinction event at the Jurassic-Cretaceous boundary. He also published research on atoposaurids, an extinct group of small early crocodilian relatives. As a science communicator, Jon was a regular contributor to Discover on paleontology. == Open Science movement == A key advocate, speaker and activist in the Open Science movement, he was a supporter of open access to knowledge and cultural change within the scientific community. He was an Editor for the PLOS Paleo Community, executive editor for Geoscience Communication, part of the Mozilla Open Leadership Cohort, and worked as Communications Director for ScienceOpen. With Jennifer Beamer, Jeroen Bosman, Björn Brembs, Neo Christopher Chung, Gail Clement, and others, he wrote an influential guide and strategy on open access and open research. He was a panelist


id: uses-of-open-science-20260505-0
file: data/en.wikipedia.org/wiki/Uses_of_open_science-0.md
category: reference
title: Uses of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Uses_of_open_science
date_saved: 2026-05-05T03:50:26.910892+00:00
instance: kb-cron
parent: uses-of-open-science-20260505-0
summary:
The open science movement has expanded the uses of scientific output beyond specialized academic circles. Non-academic audience of journals and other scientific outputs has always been significant but was not recorded by the leading metrics of scientific reception, which favor citation data. In the late 1990s, the first open-access online publications started to attract a large number of individual visits. This transformation has renewed the theories of scientific dissemination, as direct access to publications curtailed the classic model of scientific popularization. Social impact and potential uses by lay readers have become focal points of discussion in the development of open science platforms and infrastructures. Analysis of open science uses has required the development of new methods, including log analysis, crosslinking analysis or altmetrics, as the standard bibliometric approach failed to record the non-academic reception of scientific productions. In the 2010s, several detailed studies were devoted to the reception of specific open science platforms due to the increasing availability of use data. Log analysis and surveys showed that professional academics do not make up the majority of the audience, as recurrent reader profiles include students, non-academic professionals (policy makers, industrial R&D, knowledge workers) and "private citizens" with various motivations (personal health,


id: uses-of-open-science-20260505-1
file: data/en.wikipedia.org/wiki/Uses_of_open_science-1.md
category: reference
title: Uses of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Uses_of_open_science
date_saved: 2026-05-05T03:50:26.910892+00:00
instance: kb-cron
parent: uses-of-open-science-20260505-0
summary:
=== Non-academic audience === Academic journals have always had a significant non-academic audience, be they students, professionals, or amateurs. In 2000, one-third of these readers had never authored a scientific publication. This rate may be higher for social science journals, which may also act as intellectual periodicals. During the second half of the 20th century, the non-academic audience may have continuously expanded in Western countries, along with the increasing prevalence of high school education: "the percentage of U.S. adults with a minimal level of understanding of the meaning of scientific study has increased from 12 percent in 1957 to 21 percent in 1999". The prevalence of non-academic audience raises additional issues on the relevance and scope of classic bibliometric measures, as they would "never appear in citation data". The infrastructures and business models put in place by leading scientific publishers do not consider non-academic uses. Following the periodical crisis of the 1980s and the inflation of subscription prices, major journals have largely become unattainable for lay readers or independent researchers not affiliated with a large research institution. Search engines and bibliographic databases developed since the 1960s and the 1970s were meant to be used by professional librarians. Leading scientific publishers


id: uses-of-open-science-20260505-2
file: data/en.wikipedia.org/wiki/Uses_of_open_science-2.md
category: reference
title: Uses of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Uses_of_open_science
date_saved: 2026-05-05T03:50:26.910892+00:00
instance: kb-cron
parent: uses-of-open-science-20260505-0
summary:
I turn our attention to these alternative, public forms of research impact and reach by examining the Latin American case. In this study, impact will be assessed through evidence of the research literature being saved, discussed, forwarded, recommended, mentioned, or cited, both within and beyond the academic community (…) Reach refers, in this study, to the extent to which the research literature is viewed or downloaded by members of various audiences, beginning with the traditional academic readership and extending outward through related professions, and perhaps journalists, teachers, enthusiasts, and members of the public (…) By looking at a broad range of indicators of impact and reach, far beyond the typical measures of one article citing another, I argue, it is possible to gain a sense of the people that are using Latin American research, thereby opening the door for others to see the ways in which it has touched those individuals and communities. The unprecedented focus on the social impact of science fits with alternative models of scientific popularization. In 2009, Alesia Zuccala introduced a radiant model of open science dissemination with a variety of mediated and unmediated connections between non-academic audience and academic production: "Sometimes [research] engages the lay


id: uses-of-open-science-20260505-3
file: data/en.wikipedia.org/wiki/Uses_of_open_science-3.md
category: reference
title: Uses of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Uses_of_open_science
date_saved: 2026-05-05T03:50:26.910892+00:00
instance: kb-cron
parent: uses-of-open-science-20260505-0
summary:
=== Log Analysis === Academic publications have been among the earliest corpora used for log analysis. The first applied studies in the area long predate the web, as interconnected scientific infrastructures were already widely used in North America and Europe by the 1970s and 1980s. In 1983, several studies, pioneered by the Online Computer Library Center, analyzed "transaction logs" left by database users. Logs were stored on magnetic tapes at the time, and a large part of the analysis was devoted to the reformatting and standardization of the data. Standard methods of log analysis were already implemented in these early studies, such as the use of probabilistic approaches based on Markov Chains, in order to identify the more regular patterns of user behavior or the comparison with more user surveys. The use of logs and other reader metrics to measure the reception of academic work has remained marginal. Large commercial databases, like the Web of Science and Scopus, had no incentives to divulge reading statistics and mostly use them for internal purposes. Bibliometric indices based on aggregated citation counts, like the impact factor or the h-index, have been favored as the leading measures of academic impact. Beyond the restrictions imposed


id: uses-of-open-science-20260505-4
file: data/en.wikipedia.org/wiki/Uses_of_open_science-4.md
category: reference
title: Uses of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Uses_of_open_science
date_saved: 2026-05-05T03:50:26.910892+00:00
instance: kb-cron
parent: uses-of-open-science-20260505-0
summary:
=== Altmetrics === During the 2000s and 2010s, the web was increasingly dominated by very large social media platforms that curate and shape a significant part of the digital public sphere. The public reception of scientific literature has also largely migrated to these platforms. This evolution has prompted the development of new metrics and quantitative methods aiming to map the circulation of publications on social media: the altmetrics. The concept of alt-metrics was introduced in 2009 by Cameron Neylon and Shirly Wu as article-level metrics. In contrast with the focus of leading metrics on journals (impact factor) or, more recently, on individual researchers (h-index), the article-level metrics makes it possible to track the circulation of individual publications: "article that used to live on a shelf now lives in Mendeley, CiteULike, or Zotero – where we can see and count it" As such they are more compatible with the diversity of publication strategies that has characterized open science: preprints, reports or even non-textual outputs like dataset or software may also have associated metrics. In their original research proposition, Neylon and Wu favored the use of data from reference management software like Zotero or Mendeley. The concept of altmetrics evolved and came


id: uses-of-open-science-20260505-5
file: data/en.wikipedia.org/wiki/Uses_of_open_science-5.md
category: reference
title: Uses of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Uses_of_open_science
date_saved: 2026-05-05T03:50:26.910892+00:00
instance: kb-cron
parent: uses-of-open-science-20260505-0
summary:
=== User practices and motivations === Studies of user practices have mostly focused on specific user profiles. Few general surveys have been undertaken. In Japan, a 2011 poll of 800 adults showed that a "majority of respondents (55%) claimed that Open Access is useful or slightly useful to them", which suggests a rather large awareness of open science in a population with a significant share of high school education. The issues facing medical patients have been especially highlighted. An important field of research on health-information-seeking behavior (HISB) emerged prior to the development of open science. In a 2003 survey, half of American Internet users had attempted to find qualified information about their health, but regularly faced access issues: "Many current Internet health users want to expand access to information-laden sites that are currently closed to non-subscribers". A qualitative research on English medical patients, subscription paywalls were cited as the main barrier to access to scientific knowledge, along with the complexity of scientific terminology. While the specific needs patients make a strong case for open science, they have also overshadowed the variety of potential uses of academic research: "open access is not just a public health matter: It has a much


id: uses-of-open-science-20260505-6
file: data/en.wikipedia.org/wiki/Uses_of_open_science-6.md
category: reference
title: Uses of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Uses_of_open_science
date_saved: 2026-05-05T03:50:26.910892+00:00
instance: kb-cron
parent: uses-of-open-science-20260505-0
summary:
=== Book & thesis === Matthews, Joseph R.; Lawrence, Gary S.; Ferguson, Douglas K. (1983). Using Online Catalogs: A Nationwide Survey: a Report of a Study Sponsored by the Council on Library Resources. Neal-Schuman. ISBN 978-0-918212-76-4. Tenopir, Carol; King, Donald W (2000). Towards electronic journals: realities for scientists, librarians, and publishers. Washington, DC: Special Libraries Association. ISBN 978-0-87111-507-2. Willinsky, John (2006). The access principle: the case for open access to research and scholarship. Digital libraries and electronic publishing. Cambridge, Mass: MIT Press. ISBN 978-0-262-23242-5. Bellis, Nicola De (2009-03-09). Bibliometrics and Citation Analysis: From the Science Citation Index to Cybermetrics. Scarecrow Press. ISBN 978-0-8108-6714-7. Montgomery, Scott L. (2013-05-06). Does Science Need a Global Language?: English and the Future of Research. University of Chicago Press. ISBN 978-0-226-01004-5. Hogan, A. (2014-04-09). Reasoning Techniques for the Web of Data. IOS Press. ISBN 978-1-61499-383-4. Alperin, Juan Pablo (2015). The public impact of Latin America's approach to open access (Thesis). Stanford University. Sugimoto, Cassidy R.; Larivière, Vincent (2018). Measuring Research: What Everyone Needs to Know. Oxford University Press. ISBN 978-0-19-064011-8. Gillespie, Tarleton (2018). Custodians of the internet: platforms, content moderation, and the hidden decisions that shape social media. New Haven: Yale University Press. ISBN 978-0-300-17313-0. ===


id: uses-of-open-science-20260505-7
file: data/en.wikipedia.org/wiki/Uses_of_open_science-7.md
category: reference
title: Uses of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Uses_of_open_science
date_saved: 2026-05-05T03:50:26.910892+00:00
instance: kb-cron
parent: uses-of-open-science-20260505-0
summary:
=== Academic articles & chapters === Miller, Jon D. (July 2004). "Public Understanding of, and Attitudes toward, Scientific Research: What We Know and What We Need to Know". Public Understanding of Science. 13 (3): 273–294. doi:10.1177/0963662504044908. ISSN 0963-6625. S2CID 144736762. van Raan, Anthony F. J. (March 2004). "Sleeping Beauties in science". Scientometrics. 59 (3): 467–472. doi:10.1023/B:SCIE.0000018543.82441.f1. ISSN 1588-2861. S2CID 189864678. Johnson, Richard K. (2006-09-13). "Will Research Sharing Keep Pace with the Internet?". The Journal of Neuroscience. 26 (37): 9349–9351. doi:10.1523/JNEUROSCI.3130-06.2006. ISSN 0270-6474. PMC 6674599. PMID 16971518. Davis, Philip M.; Price, Jason (July 2006). "eJournal interface can influence usage statistics: implications for libraries, publishers, and Project COUNTER". Journal of the American Society for Information Science and Technology. 57 (9): 1243–1248. arXiv:cs/0602060. doi:10.1002/asi.20405. ISSN 1532-2882. S2CID 261212798. Retrieved 2022-05-07. Duy, Joanna; Vaughan, Liwen (September 2006). "Can electronic journal usage data replace citation data as a measure of journal use? An empirical examination1" (PDF). The Journal of Academic Librarianship. 32 (5): 512–517. doi:10.1016/j.acalib.2006.05.005. ISSN 0099-1333. Warwick, Claire; Terras, Melissa; Huntington, Paul; Pappa, Nikoleta (April 2008). "If You Build It Will They Come? The LAIRAH Study: Quantifying the Use of Online Resources in the Arts and Humanities through Statistical Analysis of User Log Data".


id: uses-of-open-science-20260505-8
file: data/en.wikipedia.org/wiki/Uses_of_open_science-8.md
category: reference
title: Uses of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Uses_of_open_science
date_saved: 2026-05-05T03:50:26.910892+00:00
instance: kb-cron
parent: uses-of-open-science-20260505-0
summary:
"Does open access to academic research help small, science-based companies?". Journal of Industry-University Collaboration. 2 (3): 95–109. doi:10.1108/JIUC-04-2020-0004. ISSN 2631-357X. Tunger, Dirk; Meier, Andreas (2020-12-07). "4.1 The Future Has Already Begun: Origin, Classification, and Applications of Altmetrics in Scholarly Communication". In Ball, Rafael (ed.). Handbook Bibliometrics. De Gruyter Saur. pp. 181–190. doi:10.1515/9783110646610-019. ISBN 978-3-11-064661-0. S2CID 235879114. Pölönen, Janne; Syrjämäki, Sami; Nygård, Antti-Jussi; Hammarfelt, Björn (October 2021). "Who are the users of national open access journals? The case of the Finnish Journal.fi platform". Learned Publishing. 34 (4): 585–592. doi:10.1002/leap.1405. ISSN 1741-4857. Hicks, Diana; Zullo, Matteo; Doshi, Ameet; Asensio, Omar I. (March 2022). "Widespread use of National Academies consensus reports by the American public". Proceedings of the National Academy of Sciences. 119 (9): –2107760119. Bibcode:2022PNAS..11907760H. doi:10.1073/pnas.2107760119. PMC 8892306. PMID 35193972. Ross-Hellauer, Tony; Reichmann, Stefan; Cole, Nicki Lisa; Fessl, Angela; Klebel, Thomas; Pontika, Nancy (2022). "Dynamics of cumulative advantage and threats to equity in open science: a scoping review". Royal Society Open Science. 9 (1) 211032. Bibcode:2022RSOS....911032R. doi:10.1098/rsos.211032. PMC 8767192. PMID 35116143. === Conference === Tolle, John E. (1983). "Transaction log analysis online catalogs". Proceedings of the 6th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '83.


id: john-wilbanks-20260505-0
file: data/en.wikipedia.org/wiki/John_Wilbanks-0.md
category: reference
title: John Wilbanks
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/John_Wilbanks
date_saved: 2026-05-05T03:50:28.195707+00:00
instance: kb-cron
parent: john-wilbanks-20260505-0
summary:
John Wilbanks is a Senior Fellow at the Datasphere Initiative, former Head of Data at Biogen Digital Health, former Chief Commons Officer at Sage Bionetworks, and Executive Director at Science Commons. He served as a Senior Fellow at the Ewing Marion Kauffman Foundation and at FasterCures. He is known for his work on informed consent, open science and research networks. Wilbanks led a We the People petition supporting the free access of taxpayer-funded research data, which gained over 65,000 signatures. In February 2013, the White House responded, detailing a plan to freely publicize taxpayer-funded research data. Scientific American featured Wilbanks in "The Machine That Would Predict The Future" in 2011. Seed magazine named Wilbanks among their Revolutionary Minds of 2008, as a "Game Changer" and the Utne Reader named him in 2009 as one of "50 visionaries who are changing your world". He frequently campaigns for wider adoption of open access publishing in science and the increased sharing of data by scientists. == Education and career == Wilbanks grew up in Knoxville, Tennessee, US. He attended Tulane University and received a Bachelor of Arts in philosophy in 1994. He also studied modern letters at the Sorbonne in Paris. From 1994


id: florimontane-academy-20260505-0
file: data/en.wikipedia.org/wiki/Florimontane_Academy-0.md
category: reference
title: Florimontane Academy
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Florimontane_Academy
date_saved: 2026-05-05T03:50:33.671470+00:00
instance: kb-cron
parent: florimontane-academy-20260505-0
summary:
The Florimontane Academy, originally established as the Florimontane Society, is a learned society founded in Annecy in 1606–1607. The society ceased to operate in 1610 and was reestablished in 1851. == History == === Foundation === During the winter of 1606–1607, the Florimontane Academy was established in Annecy, taking inspiration from the Italian academies of the 16th century. The society was founded by two prominent Savoyards: Antoine Favre, Baron of Pérouges and President of the State Council of Genevois, and François de Sales, Prince-Bishop of Geneva. The academy sought to encourage and develop activity across theological, philosophical, scientific, and literary fields. Meetings were held at the Hôtel Bagnoréa on Rue Sainte-Claire in Annecy, the residence of Antoine Favre, which Galeazzo Gegald had constructed. The first Florimontane Academy benefited from the prominence of its founders and enjoyed considerable prestige. It was one of the earliest French-speaking academies, predating the French Academy by 29 years. The society comprised 40 members and operated under the patronage of Henri I of Savoy-Nemours, Duke of Geneva. The name “Florimontane” was selected to reflect the idea that “the muses flourished among the mountains of Savoy.” In 1610, the Florimontane Academy ceased to function following the departure


id: florimontane-academy-20260505-1
file: data/en.wikipedia.org/wiki/Florimontane_Academy-1.md
category: reference
title: Florimontane Academy
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Florimontane_Academy
date_saved: 2026-05-05T03:50:33.671470+00:00
instance: kb-cron
parent: florimontane-academy-20260505-0
summary:
==== Notable figures of the Academy ==== Baron and Doctor Charles-Humbert-Antoine Despine (1777–1852) Alphonse-Louis-Joseph Despine (1818–1872), lawyer and professor of law in Annecy, author of several works on regional history and literature, member of the Société des Antiquaires de France Camille Dunant (1819–1909) Venance Payot (1826–1902), guide, collector, scholar, editor, and naturalist in Chamonix Aimé Constantin (1832–1900), scholar, philologist, writer; his work led to the first dictionary of the Savoyard dialect Jean-François Gonthier (1847–1913), priest of the Diocese of Annecy and historian of Savoy, honorary president of the Salésian Academy Léon Marès (1854–1916), collector Louis Balleydier (1856–1927), professor of law, Dean of the Faculty of Law of Grenoble, father-in-law of Louis Aussedat Charles Buttin (1856–1933), scholar and collector, author of 140 works for 286 publications, mainly on ancient arms, including the Catalogue de la Collection d'armes anciennes, européennes et orientales (1933) Aimé Vaschy (1857–1899), telegraph engineer and mathematician René Payot (1894–1970), Swiss journalist Georges Chapier (1906–1975), historian of Savoy, member of the Florimontane Academy in 1973, correspondent of the Academy of Philately, and honorary president of the Lyon circle for philatelic and numismatic studies (1974) == See also == Learned society History of Savoy == Notes == == References ==


id: learned-society-20260505-0
file: data/en.wikipedia.org/wiki/Learned_society-0.md
category: reference
title: Learned society
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Learned_society
date_saved: 2026-05-05T03:50:34.914134+00:00
instance: kb-cron
parent: learned-society-20260505-0
summary:
A learned society ( LEHRN-id; also scholarly, intellectual, or academic society) is an organization that exists to promote an academic discipline, profession, or a group of related disciplines such as the arts and sciences. Membership may be open to all, may require possession of some qualification, or may be an honour conferred by election. Most learned societies are non-profit organizations, and many are professional associations. Their activities typically include holding regular conferences for the presentation and discussion of new research results, and publishing or sponsoring academic journals in their discipline. Some also act as professional bodies, regulating the activities of their members in the public interest or the collective interest of the membership. == History == Some of the oldest learned societies are the Académie des Jeux floraux (founded 1323), Sodalitas Litterarum Vistulana (founded 1488), Accademia della Crusca (founded 1583), Accademia dei Lincei (founded 1603), Académie Française (founded 1635), German National Academy of Sciences Leopoldina (founded 1652), Royal Society (founded 1660) and French Academy of Sciences (founded 1666). == Significance == Scholars in the sociology of science argue that learned societies are of key importance and their formation assists in the emergence and development of new disciplines or professions. In


id: list-of-scientific-bodies-explicitly-rejecting-intelligent-design-20260505-0
file: data/en.wikipedia.org/wiki/List_of_scientific_bodies_explicitly_rejecting_intelligent_design-0.md
category: reference
title: List of scientific bodies explicitly rejecting intelligent design
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_scientific_bodies_explicitly_rejecting_intelligent_design
date_saved: 2026-05-05T03:50:36.121108+00:00
instance: kb-cron
parent: list-of-scientific-bodies-explicitly-rejecting-intelligent-design-20260505-0
summary:
This article lists those scientific organisations and other nationally or internationally recognised groups that specifically reject intelligent design as a valid alternative to evolutionary theory. == United States ==


id: list-of-scientific-bodies-explicitly-rejecting-intelligent-design-20260505-1
file: data/en.wikipedia.org/wiki/List_of_scientific_bodies_explicitly_rejecting_intelligent_design-1.md
category: reference
title: List of scientific bodies explicitly rejecting intelligent design
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_scientific_bodies_explicitly_rejecting_intelligent_design
date_saved: 2026-05-05T03:50:36.121108+00:00
instance: kb-cron
parent: list-of-scientific-bodies-explicitly-rejecting-intelligent-design-20260505-0
summary:
=== National === The American Association for the Advancement of Science is the world's largest general scientific society. The AAAS serves some 262 affiliated societies and academies of science, serving 10 million individuals. A 2002 statement states: "[T]he lack of scientific warrant for so-called 'intelligent design theory' makes it improper to include as a part of science education." A 2006 statement on the teaching of evolution: "Some bills seek to discredit evolution by emphasizing so-called "flaws" in the theory of evolution or "disagreements" within the scientific community. Others insist that teachers have absolute freedom within their classrooms and cannot be disciplined for teaching non-scientific "alternatives" to evolution. A number of bills require that students be taught to "critically analyze" evolution or to understand "the controversy." But there is no significant controversy within the scientific community about the validity of the theory of evolution. The current controversy surrounding the teaching of evolution is not a scientific one." Q & A on Evolution and Intelligent Design: Is intelligent design a scientific alternative to contemporary evolutionary theory? No. Intelligent design proponents may use the language of science, but they do not use its methodology. They have yet to propose meaningful tests for their


id: list-of-scientific-bodies-explicitly-rejecting-intelligent-design-20260505-2
file: data/en.wikipedia.org/wiki/List_of_scientific_bodies_explicitly_rejecting_intelligent_design-2.md
category: reference
title: List of scientific bodies explicitly rejecting intelligent design
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_scientific_bodies_explicitly_rejecting_intelligent_design
date_saved: 2026-05-05T03:50:36.121108+00:00
instance: kb-cron
parent: list-of-scientific-bodies-explicitly-rejecting-intelligent-design-20260505-0
summary:
Underlying both of these concepts, and foundational to IDC itself, is an early 19th-century British theological view, the 'argument from design.'" The NCSE also maintains lists of organizations from around the world that oppose the teaching of creationism, including intelligent design, listing 71 scientific organizations, 23 religious organizations, 43 educational organizations, and 10 civil liberties organizations. The National Science Teachers Association NSTA is a professional association of 55,000 science teachers and administrators. "We stand with the nation's leading scientific organizations and scientists, including Dr. John Marburger, the president's top science advisor, in stating that intelligent design is not science. … It is simply not fair to present pseudoscience to students in the science classroom." United States National Academy of Sciences The academy wrote a statement entitled "Science and Creationism: A View from the National Academy of Sciences, Second Edition National Academy of Sciences" which said that "Creationism, Intelligent Design, and other claims of supernatural intervention in the origin of life or of species are not science". There was also a letter from Bruce Alberts, former president, NAS: "We stand ready to help others in addressing the increasingly strident attempts to limit the teaching of evolution or to introduce non-scientific 'alternatives'


id: list-of-scientific-bodies-explicitly-rejecting-intelligent-design-20260505-3
file: data/en.wikipedia.org/wiki/List_of_scientific_bodies_explicitly_rejecting_intelligent_design-3.md
category: reference
title: List of scientific bodies explicitly rejecting intelligent design
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_scientific_bodies_explicitly_rejecting_intelligent_design
date_saved: 2026-05-05T03:50:36.121108+00:00
instance: kb-cron
parent: list-of-scientific-bodies-explicitly-rejecting-intelligent-design-20260505-0
summary:
=== State and university === Kentucky Academy of Science states "...in the strongest and most determined ways possible deplores the decision to substitute "change over time" for "evolution" in the state teaching standards, urges that the original wording be reinstated, and decries any attempt to remove the teaching of basic evolutionary theory..." Adopted by KAS Governing Board November 6, 1999. Passed unanimously by KAS membership November 6, 1999. Unanimously approved again at its annual business meeting on November 11, 2005. The KAS also voted to endorse the October 2002 AAAS Board Resolution on Intelligent Design Theory. The Kentucky Paleontological Society Statement on Teaching Evolution states that "KPS is opposed to any attempt to teach creationism or omit mention of evolution from public school instruction. Furthermore, evolution should be called "evolution" in curriculum guidelines and other documents; euphemisms such as "change over time" are intellectually dishonest for they attempt to conceal the terminology used by scientists." Executive Committee approved this statement in 1999. The Lehigh University Department of Biological Sciences responded to faculty member and intelligent design proponent Michael Behe's claims about the scientific validity and usefulness of intelligent design, publishing an official position statement which says "It is our collective


id: mircen-20260505-0
file: data/en.wikipedia.org/wiki/MIRCEN-0.md
category: reference
title: MIRCEN
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/MIRCEN
date_saved: 2026-05-05T03:50:37.630787+00:00
instance: kb-cron
parent: mircen-20260505-0
summary:
MIRCEN (Microbial Resources Centers) is an international network of microbiology and biotechnology centres established with support from UNESCO. == See also == UNESCO World Federation for Culture Collections Culture collection Biotechnology == References ==


id: research-site-20260505-0
file: data/en.wikipedia.org/wiki/Research_site-0.md
category: reference
title: Research site
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research_site
date_saved: 2026-05-05T03:50:41.242537+00:00
instance: kb-cron
parent: research-site-20260505-0
summary:
CHALLENGES of MATHEMATICS LEARNING In joining extracurricular activities == Clinical research == In clinical research a research site conducts all or part of a clinical trial. For clinical trials which recruit research participants in multiple locations, often the research will have a headquarters then multiple regional research sites to conduct the research in that region. In a network of research sites where all are recruiting study participants, sites with low recruitment benefit from coaching from sites with high recruitment. Characteristics of good clinical research sites include setting good timelines, early participant recruitment, and having a management plan for efficiency. Researchers in nursing have reported challenges accessing the facilities designated for conventional medical research. The design of a research site should have a means of detecting fraud. == Ethnographic research == Researchers who do not have a cultural tie to a research population may have difficulty doing ethnographic research with that community. == References == == External links == Basic Requirements for Starting a Research Site from American Society of Clinical Oncology


id: virtual-scientific-community-20260505-0
file: data/en.wikipedia.org/wiki/Virtual_scientific_community-0.md
category: reference
title: Virtual scientific community
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Virtual_scientific_community
date_saved: 2026-05-05T03:50:46.134380+00:00
instance: kb-cron
parent: virtual-scientific-community-20260505-0
summary:
A virtual scientific community is a group of people, often researchers and students, who share multiple resources related to the scientific field, and whose main medium of communication is the internet. Examples of such communities include the Computational Intelligence and Machine Learning Portal or the Biomedical Informatics Research Network. There are numerous scientific repositories and websites in existence that, while useful, do not meet the definition of a virtual scientific community. Examples of such are data and scientific literature repositories as well as open access journals. == Further reading == Jacek M. Zurada, Janusz Wojtusiak, Maciej A. Mazurowski, Devendra Mehta, Khalid Moidu, Steve Margolis, Toward Multidisciplinary Collaboration in the CIML Virtual Community, Proceedings of the 2008 Workshop on Building Computational Intelligence and Machine Learning Virtual Organizations, pp. 62–66 == See also == Science Community CIML community portal == External links == The Computational Intelligence and Machine Learning Virtual Community Archived 2009-10-04 at the Wayback Machine What is BIRN? == References ==


id: intrinsic-and-extrinsic-properties-20260505-0
file: data/en.wikipedia.org/wiki/Intrinsic_and_extrinsic_properties-0.md
category: reference
title: Intrinsic and extrinsic properties
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Intrinsic_and_extrinsic_properties
date_saved: 2026-05-05T03:50:49.612401+00:00
instance: kb-cron
parent: intrinsic-and-extrinsic-properties-20260505-0
summary:
In science and engineering, an intrinsic property is a property of a specified subject that exists itself or within the subject. An extrinsic property is not essential or inherent to the subject that is being characterized. For example, mass is an intrinsic property of any physical object, whereas weight is an extrinsic property that depends on the strength of the gravitational field in which the object is placed. == Applications == In materials science, an intrinsic property is independent of how much of a material is present and is independent of the form of the material, e.g., one large piece or a collection of small particles. Intrinsic properties are dependent mainly on the fundamental chemical composition and structure of the material. Extrinsic properties are differentiated as being dependent on the presence of avoidable chemical contaminants or structural defects. In biology, intrinsic effects originate from inside an organism or cell, such as an autoimmune disease or intrinsic immunity. In electronics and optics, intrinsic properties of devices (or systems of devices) are generally those that are free from the influence of various types of non-essential defects. Such defects may arise as a consequence of design imperfections, manufacturing errors, or operational extremes and


id: rayleigh-scattering-20260505-0
file: data/en.wikipedia.org/wiki/Rayleigh_scattering-0.md
category: reference
title: Rayleigh scattering
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Rayleigh_scattering
date_saved: 2026-05-05T03:50:50.823381+00:00
instance: kb-cron
parent: rayleigh-scattering-20260505-0
summary:
Rayleigh scattering ( RAY-lee) is the scattering or deflection of light, or other electromagnetic radiation, by particles with a size much smaller than the wavelength of the radiation. For light frequencies well below the resonance frequency of the scattering medium (normal dispersion regime), the amount of scattering is inversely proportional to the fourth power of the wavelength (e.g., a blue color is scattered much more than a red color as light propagates through air). The phenomenon is named after the 19th-century British physicist Lord Rayleigh (John William Strutt). Rayleigh scattering results from the electric polarizability of the particles. The oscillating electric field of a light wave acts on the charges within a particle, causing them to move at the same frequency. The particle, therefore, becomes a small radiating dipole whose radiation we see as scattered light. The particles may be individual atoms or molecules; it can occur when light travels through transparent solids and liquids, but is most prominently seen in gases. Rayleigh scattering of sunlight in Earth's atmosphere causes diffuse sky radiation. Since blue light wavelengths scatter more, the diffuse sky seen in daytime is blue. At twilight the sunlight on the horizon is missing the scattered blue light


id: rayleigh-scattering-20260505-1
file: data/en.wikipedia.org/wiki/Rayleigh_scattering-1.md
category: reference
title: Rayleigh scattering
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Rayleigh_scattering
date_saved: 2026-05-05T03:50:50.823381+00:00
instance: kb-cron
parent: rayleigh-scattering-20260505-0
summary:
I s = I 0 π 2 α 2 ε 0 2 λ 4 R 2 1 + cos 2 ⁡ θ 2 . {\displaystyle I_{s}=I_{0}{\frac {\pi ^{2}\alpha ^{2}}{{\varepsilon _{0}}^{2}\lambda ^{4}R^{2}}}{\frac {1+\cos ^{2}\theta }{2}}.} == Effect of fluctuations == When the dielectric constant ϵ {\displaystyle \epsilon } of a certain region of volume V {\displaystyle V} is different from the average dielectric constant of the medium ϵ ¯ {\displaystyle {\bar {\epsilon }}} , then any incident light will be scattered according to the following equation I = I 0 π 2 V 2 σ ϵ 2 2 λ 4 R 2 ( 1 + cos 2 ⁡ θ ) {\displaystyle I=I_{0}{\frac {\pi ^{2}V^{2}\sigma _{\epsilon }^{2}}{2\lambda ^{4}R^{2}}}{\left(1+\cos ^{2}\theta \right)}} where σ ϵ 2 {\displaystyle \sigma _{\epsilon }^{2}} represents the variance of the fluctuation in the dielectric constant ϵ {\displaystyle \epsilon } . == Cause of the blue color of the sky == The blue color of the sky is a consequence of three factors: the blackbody spectrum of sunlight coming into the Earth's atmosphere, Rayleigh scattering of that light off oxygen and nitrogen molecules, and the response of the human visual system. The strong wavelength dependence of the Rayleigh scattering (~λ−4)


id: recovery-effect-20260505-0
file: data/en.wikipedia.org/wiki/Recovery_effect-0.md
category: reference
title: Recovery effect
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Recovery_effect
date_saved: 2026-05-05T03:50:52.101449+00:00
instance: kb-cron
parent: recovery-effect-20260505-0
summary:
The recovery effect is a phenomenon observed in battery usage where the available energy is less than the difference between energy charged and energy consumed. == Mechanism == Intuitively, this is because the energy has been consumed from the edge of the battery and the charge has not yet diffused evenly around the battery. When power is extracted continuously voltage decreases in a smooth curve, but the recovery effect can result in the voltage partially increasing if the current is interrupted. == In non-lead-acid batteries == The KiBaM battery model describes the recovery effect for lead-acid batteries and is also a good approximation to the observed effects in Li-ion batteries. In some batteries, the gains from the recovery life can extend battery life by up to 45% by alternating discharging and inactive periods rather than constantly discharging. The size of the recovery effect depends on the battery load, recovery time and depth of discharge. Even though the recovery effect phenomenon is prominent in the lead acid battery chemistry, its existence in alkaline, Ni-MH and Li-Ion batteries is still questionable. For instance, a systematic experimental case study shows that an intermittent discharge current in case of alkaline, Ni-MH and Li-ion batteries


id: jos-miguel-camacho-gonz-lez-20260505-0
file: data/en.wikipedia.org/wiki/José_Miguel_Camacho_González-0.md
category: reference
title: José Miguel Camacho González
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/José_Miguel_Camacho_González
date_saved: 2026-05-05T03:50:55.160998+00:00
instance: kb-cron
parent: jos-miguel-camacho-gonz-lez-20260505-0
summary:
José Miguel Camacho González (born 17 January 1951) is a Spanish ophthalmologist, medical director, and pioneer on intraocular lens. He was born in Cúllar, Granada. He studied at Universidad de Granada, in 1976 he got a bachelor's degree in Medicine and in 1979 he specialized on Surgery. In 1970s he worked as ophthalmologist at Bola Azul and Hospital Torrecárdenas in Almería, and he cooperated with Instituto de Oftalmología Barraquer. He opened Vista Camacho, which works with the latest and innovated ophthalmological technologies, including VisX STAR S4 IR CustomVue laser with the Wave Scan aberrometer, and the Spectralis(R) platform, which is a tomograph to make micro-thousandth eye studies. He is one of the most rated ophthalmologist in the province of Almería by Doctoralia. Manuel Camacho Sampelayo, his son, who followed his steps and also studied at Universidad de Granada and Instituto de Oftalmología Barraquer, holds the eighth place in the ranking, and his brother José Miguel holds the ninth place. In 2010 he got the 3rd Videofestival Secoir Cádiz Award alongside Jaime Campello Lluch and José Miguel Camacho Sampelayo. In March 2022 he provided free services to Ukrainian refugees in Almería due to the Russian invasion of Ukraine, and he was


id: list-of-pioneers-in-computer-science-20260505-0
file: data/en.wikipedia.org/wiki/List_of_pioneers_in_computer_science-0.md
category: reference
title: List of pioneers in computer science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_pioneers_in_computer_science
date_saved: 2026-05-05T03:50:56.325384+00:00
instance: kb-cron
parent: list-of-pioneers-in-computer-science-20260505-0
summary:
This is a list of people who made transformative breakthroughs in the creation, development and imagining of what computers could do. == Pioneers == ~ Items marked with a tilde are circa dates. == See also == Computer Pioneer Award IEEE John von Neumann Medal Grace Murray Hopper Award History of computing History of computing hardware History of computing hardware (1960s–present) History of software List of computer science awards List of computer science journals List of computer scientists List of Internet pioneers List of pioneers in computer science List of people considered father or mother of a field § Computing The Man Who Invented the Computer (2010 book) List of Russian IT developers List of Women in Technology International Hall of Fame inductees Timeline of computing Turing Award Women in computing == References == === Sources === Hamming, Richard W. (1950). "Error detecting and error correcting codes" (PDF). Bell System Technical Journal. 29 (2): 147–160. Bibcode:1950BSTJ...29..147H. doi:10.1002/j.1538-7305.1950.tb00463.x. hdl:10945/46756. MR 0035935. S2CID 61141773. Archived from the original (PDF) on 2006-05-25. Ling, San; Xing, Chaoping (2004). Coding Theory: a First Course. Cambridge: Cambridge University Press. ISBN 978-0-521-82191-9. Pless, Vera (1982). Introduction to the Theory of Error-Correcting Codes. New York: Wiley. ISBN 978-0-471-08684-0.


id: birds-in-a-truck-riddle-20260505-0
file: data/en.wikipedia.org/wiki/Birds_in_a_truck_riddle-0.md
category: reference
title: Birds in a truck riddle
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Birds_in_a_truck_riddle
date_saved: 2026-05-05T03:50:57.867658+00:00
instance: kb-cron
parent: birds-in-a-truck-riddle-20260505-0
summary:
The birds in a truck riddle is a riddle that asks whether a container or a truck carrying birds changes in weight when the birds inside are flying. The television series MythBusters investigated the question in a 2007 episode, testing it both with a box of pigeons and again with a model helicopter. They concluded that the contents being in flight made no difference to the weight, and theorised that the downdraft of air from the wings or rotors pressed down against the base of the box with the same force as the resting bird or helicopter. A drone research team from Stanford University measured the forces involved in a bird's hovering and found that it created "double the lift during the downstroke [of the wings] so that the birds did not have to lift their weight during the upstroke", with the amount of lift on the upstroke being "almost none". They concluded that a truck containing a few birds would fluctuate in weight over time, but a larger flock flapping at random would cancel one another and leave the truck's weight unaffected. == References ==


id: list-of-unsolved-problems-in-chemistry-20260505-0
file: data/en.wikipedia.org/wiki/List_of_unsolved_problems_in_chemistry-0.md
category: reference
title: List of unsolved problems in chemistry
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_unsolved_problems_in_chemistry
date_saved: 2026-05-05T03:50:59.139871+00:00
instance: kb-cron
parent: list-of-unsolved-problems-in-chemistry-20260505-0
summary:
This is a list of unsolved problems in chemistry. Problems in chemistry are considered unsolved when an expert in the field considers it unsolved or when several experts in the field disagree about a solution to a problem. == Physical chemistry problems == Can the transition temperature of high-temperature superconductors be brought up to room temperature? How do the spin–orbit coupling, other relativistic corrections, and inter-electron effects modify the chemistry of the trans-actinides? Is it possible to create a practically useful lithium–air battery? == Organic chemistry problems == What is the origin of homochirality in biomolecules? Why are accelerated kinetics observed for some organic reactions at the water-organic interface? Do replacement reactions of aryl diazonium salts (dediazotizations) predominantly undergo SN1 or a radical mechanism? Can an electrochemical cell reliably perform organic redox reactions? Which "classic organic chemistry" reactions admit chiral catalysts? Is it possible to construct a quaternary carbon atom with arbitrary (distinguishable) substituents and stereochemistry? Can artificial enzymes replace the need for protecting groups when modifying sensitive compounds? == Inorganic chemistry problems == Are there any molecules that certainly contain a phi bond? Is there a less labor- or energy-intensive technique for titanium refinement than the Kroll process? Does


id: magmatic-water-20260505-0
file: data/en.wikipedia.org/wiki/Magmatic_water-0.md
category: reference
title: Magmatic water
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Magmatic_water
date_saved: 2026-05-05T03:51:04.106847+00:00
instance: kb-cron
parent: magmatic-water-20260505-0
summary:
Magmatic water, also known as juvenile water, is an aqueous phase in equilibrium with minerals that have been dissolved by magma deep within the Earth's crust and is released to the atmosphere during a volcanic eruption. It plays a key role in assessing the crystallization of igneous rocks, particularly silicates, as well as the rheology and evolution of magma chambers. Magma is composed of minerals, crystals and volatiles in varying relative natural abundance. Magmatic differentiation varies significantly based on various factors, most notably the presence of water. An abundance of volatiles within magma chambers decreases viscosity and leads to the formation of minerals bearing halogens, including chloride and hydroxide groups. In addition, the relative abundance of volatiles varies within basaltic, andesitic, and rhyolitic magma chambers, leading to some volcanoes being exceedingly more explosive than others. Magmatic water is practically insoluble in silicate melts but has demonstrated the highest solubility within rhyolitic melts. An abundance of magmatic water has been shown to lead to high-grade deformation, as a result of altering the composition of hydrogen isotope biogeochemistry (δ2H) and stable oxygen isotope ratios (δ18O) within host rocks. == Composition == Magma exists in three main forms that vary in composition. When


id: origin-of-water-on-earth-20260505-0
file: data/en.wikipedia.org/wiki/Origin_of_water_on_Earth-0.md
category: reference
title: Origin of water on Earth
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Origin_of_water_on_Earth
date_saved: 2026-05-05T03:51:05.225138+00:00
instance: kb-cron
parent: origin-of-water-on-earth-20260505-0
summary:
The origin of water on Earth is the subject of a body of research in the fields of planetary science, astronomy, and astrobiology. Earth is unique among known planets in having oceans of liquid water on its surface. Liquid water, which is necessary for all known forms of life, continues to exist on the surface of Earth because the planet is at a far enough distance (known as the habitable zone) from the Sun that it does not lose its water, but not so far that low temperatures cause all water on the planet to freeze. It was long thought that Earth's water did not originate from the planet's region of the protoplanetary disk. Instead, it was hypothesized water and other volatiles must have been delivered to Earth from the outer Solar System later in its history. Recent research, however, indicates that hydrogen inside the Earth played a role in the formation of the ocean. The two ideas are not mutually exclusive, as there is also evidence that water was delivered to Earth by impacts from icy planetesimals similar in composition to asteroids in the outer edges of the asteroid belt. == History of water on Earth == One factor


id: origin-of-water-on-earth-20260505-1
file: data/en.wikipedia.org/wiki/Origin_of_water_on_Earth-1.md
category: reference
title: Origin of water on Earth
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Origin_of_water_on_Earth
date_saved: 2026-05-05T03:51:05.225138+00:00
instance: kb-cron
parent: origin-of-water-on-earth-20260505-0
summary:
While the majority of Earth's surface is covered by oceans, those oceans make up just a small fraction of the mass of the planet. The mass of Earth's oceans is estimated to be 1.37 × 1021 kg, which is 0.023% of the total mass of Earth, 6.0 × 1024 kg. An additional 5.0 × 1020 kg of water is estimated to exist in ice, lakes, rivers, groundwater, and atmospheric water vapor. A significant amount of water is also stored in Earth's crust, mantle, and core. Unlike molecular H2O that is found on the surface, water in the interior exists primarily in hydrated minerals or as trace amounts of hydrogen bonded to oxygen atoms in anhydrous minerals. Hydrated silicates on the surface transport water into the mantle at convergent plate boundaries, where oceanic crust is subducted underneath continental crust. While it is difficult to estimate the total water content of the mantle due to limited samples, approximately three times the mass of the Earth's oceans could be stored there. Similarly, the Earth's core could contain four to five oceans' worth of hydrogen. While not considered to be one of the major sources of water on the planet, it should also be


id: origin-of-water-on-earth-20260505-2
file: data/en.wikipedia.org/wiki/Origin_of_water_on_Earth-2.md
category: reference
title: Origin of water on Earth
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Origin_of_water_on_Earth
date_saved: 2026-05-05T03:51:05.225138+00:00
instance: kb-cron
parent: origin-of-water-on-earth-20260505-0
summary:
One problem with this hypothesis is that the noble gas isotope ratios of Earth's atmosphere are different from those of its mantle, which suggests they were formed from different sources. To explain this observation, a so-called "late veneer" theory has been proposed in which water was delivered much later in Earth's history, after the Moon-forming impact. However, the current understanding of Earth's formation allows for less than 1% of Earth's material accreting after the Moon formed, implying that the material accreted later must have been very water-rich. Models of early Solar System dynamics have shown that icy asteroids could have been delivered to the inner Solar System (including Earth) during this period if Jupiter migrated closer to the Sun. Jupiter's relatively quick development, however, made it difficult for the inner solar system to receive matter from the outer solar system, limiting the accumulation of water on the terrestrial planets. This is in addition to other factors, such as the conditions for the goldilocks zone, where liquid water, and by extension life as we know it, can exist, as opposed to solid ice forming snowball planets or gaseous water vapor forming gas giants. Yet a third hypothesis, supported by evidence from


