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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 January 5, Zhang and his team had sequenced a virus from the sample and deposited its genome on GenBank, an international research database maintained by the United States National Center for Biotechnology Information.
By January 11, 2020, Edward C. Holmes of the University of Sydney had Zhang's permission to publicly release the genome.
=== Protein structures ===
With that information, structural biologists world-wide began examining its protein structures. Investigators from the Center for Structural Genomics of Infectious Diseases (CSGID) and other groups began working to characterize the 3D structure of the proteins, sharing their results via the Protein Data Bank (PDB).
Scientists were able to identify a key protein in the virus: 3C-like protease (Mpro).
Crucial early X-ray crystallography was done by Zihe Rao and Haitao Yang in Shanghai, China. On January 26, 2020, they submitted a structure of Mpro bound to an inhibitor to the Protein Data Bank. It was released as of February 5, 2020.
Rao began coordinating with David Stuart and Martin Walsh at Diamond Light Source, the United Kingdom's synchrotron facility. The Diamond group was able to develop and release a high-resolution crystal structure of unbound Mpro.
Approaches to accelerating drug development have been suggested, but identification of proteins and drug development commonly take years. It was possible to sequence the virus and characterize key proteins extremely quickly because the new virus was somewhat familiar. It had a 70–80% sequence similarity to the proteins in the SARS-CoV coronavirus that caused the SARS outbreak in 2002. Researchers could therefore build on what was already known about previous coronaviruses.
=== Possible targets ===
Identifying and recreating viral proteins in the lab is a first step to developing drugs to attack them and vaccines to protect against them. The COVID Moonshot initiative follows an approach to structure-based drug design in which researchers attempt to find a molecule that will bind tightly to a drug target and prevent it from carrying out its normal activities.
In the case of SARS-CoV-2, the coronavirus enters the body and then replicates its genomic RNA, building new copies that are incorporated into new, rapidly spreading viral particles. Protease enzymes or proteases are often desirable drug targets, because proteases are important in the formation and spreading of viral particles. Inhibition of viral proteases can inhibit the virus's ability to replicate itself and spread.
3C-like protease (Mpro), a coronavirus nonstructural protein, is one of the main proteins involved in the replication and transcription of SARS-CoV-2. By understanding Mpro's structure and the ways in which it functions, scientists can identify possible candidates to preemptively bind to Mpro and block its activity. Mpro is not the only possible target for drug design, but it is a highly interesting one.
=== Fragment screening ===
In collaboration with the University of Oxford and the Weizmann Institute of Science in Rehovot, Israel, the facilities at Diamond Light were used to develop fragment screens utilizing crystallography and mass spectrometry.
Nir London's laboratory at the Weizmann Institute contributed technology for identifying compounds that bind irreversibly to target proteins.
Frank von Delft and the Nuffield Department of Medicine at the University of Oxford provided technology for rapid crystallographic fragment screening.
Researchers examined thousands of possible fragments from diverse screening libraries and identified at least 71 possible protein–ligand crystal structures, chemical fragments which might have the potential to bind to Mpro.
These results were immediately made available online.
=== Designing candidates ===
The open release of the data and its announcement on Twitter on March 7, 2020, mark a critical point in the formation of COVID Moonshot. The scientists shared their information and challenged chemists worldwide to use that information to design potential openly available antiviral drug candidates. They expected a couple of hundred submissions. By May 2020 more than 4,600 design submissions for potential inhibitors were received. By January 2021, the number of unique compound designs had risen to 14,000. In response, those involved began to shift from a spontaneous virtual collaboration to a larger and more organized network of partners with specialized skills and well-articulated goals.

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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 as simple as possible. A drug shouldn't require special handling (like refrigeration) and it should be easy to administer (a pill rather than an injection).
In a matter of months, researchers were able to identify more than 200 promising crystal structure designs and to begin creating and testing them in the lab.
Chris Schofield at the University of Oxford synthesized and tested 4 of the most promising of the novel designed peptides to demonstrate their ability to block and inhibit Mpro.
Freely available data from COVID Moonshot has also been used to assess the predictive ability of docking scores in suggesting the potency of SARS-CoV-2 M-pro inhibitors.
To go beyond the design phase, possible drug candidates must be created and tested for both effectiveness and safety in animal and human trials. The Wellcome Trust has committed to key initial funding to support this process. Synthesis of candidates is being carried out in parallel, at sites including Ukraine (Enamine), India (Sai Life Sciences) and China (WuXi). Annette von Delft of the University of Oxford and the National Institute for Health Research (NIHR)'s Oxford Biomedical Research Centre (BRC) is leading pre-clinical small molecule research related to COVID Moonshot.
== Potential for antiviral treatments ==
COVID Moonshot anticipates that they will select three pre-clinical candidates by March 2022, to be followed by preclinical safety and toxicology testing and identification of needed chemistry, manufacturing and control (CMC) steps. Based on that data, the most promising candidate will be chosen. Phase-1 clinical trials, the first stage of testing in human subjects, are projected to begin by June 2023.
Unlike a vaccine, which increases immunity and protects against catching an infectious disease, an antiviral drug treats someone who is already sick by attacking the virus and countering its effects, potentially lessening both symptoms and further transmission.
Mpro is present in other coronaviruses that cause disease, so an antiviral drug that targets Mpro may also be effective against coronaviruses such as SARS and MERS and future pandemics.
Mpro does not mutate easily, so it is less likely that variants of the virus will adapt that can avoid the effects of such a drug.
== Open science ==
Among the many participants in the COVID Moonshot project are the
University of Oxford,
University of Cambridge,
Diamond Light Source,
Weizmann Institute of Science in Rehovot, Israel,
Temple University,
Memorial Sloan Kettering Cancer Center,
PostEra,
University of Johannesburg,
and the
Drugs for Neglected Diseases initiative (DNDi) in Switzerland.
Support for the project has come from a variety of philanthropic sources including the Wellcome Trust,
COVID-19 Therapeutics Accelerator (CTA),
Bill & Melinda Gates Foundation,
LifeArc,
and through crowdsourcing.
Because COVID Moonshot is based in open science and shared open data, any drug that the project develops can be manufactured and sold by whoever wishes to produce it, worldwide. Countries that are unable to buy or manufacture expensive licensed drugs would therefore have the opportunity to produce their own supplies, and competition between suppliers is likely to result in greater availability and reduced prices for consumers.
This would circumvent issues around the time needed to vaccinate people worldwide. As of July 2021, it was estimated that at current rates, this was likely to take several years. Inequities in distribution will increase both the spreading of the virus and the risk that new and more dangerous variants will emerge.
Supporters of the COVID Moonshot initiative have argued that open-science drug discovery is an essential model for combating both current and future pandemics, and that the prevention of the spread of pandemic diseases is an essential public service.
== References ==
== External links ==
Official website

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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 project in the reproducibility of psychology research, but has subsequently become multidisciplinary. The current reproducibility aspect of the project is a crowdsourced empirical investigation of the reproducibility of a variety of studies from psychological literature, sampling from three major journals: Journal of Personality and Social Psychology, Psychological Science, and Journal of Experimental Psychology: Learning, Memory, and Cognition. Scientists volunteer to replicate a study of their choosing from these journals, and follow a structured protocol for designing and conducting a high-powered replication of the key effect. The results were published in 2015.
=== Preprints ===
In 2016, OSF started three new preprint services: engrXiv, SocArXiv, and (with the Society for the Improvement of Psychological Science) PsyArXiv. It subsequently opened its own preprint server in 2017, OSF Preprints. Its unified search function includes preprints from OSF Preprints, alongside those from other servers such as Preprints.org, Thesis Commons, PeerJ, and multiple ArXiv repositories.
== See also ==
List of metascience research centers and organisations
List of preprint repositories
Metascience
Open science
Replication crisis
== References ==
== External links ==
Official website
Open Science Framework (OSF)

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Citizen science is research conducted with the participation of the general public, amateur or nonprofessional researchers, or participants from the fields of science, social science, and many other disciplines. The exact definition of "citizen science" varies, with different individuals and organizations having their own specific interpretations of its scope. Citizen science is employed in a wide range of areas of study, including ecology, biology, conservation, health and medical research, astronomy, media and communications, and information science.
The applications and functions of citizen science in research projects are multifaceted. Citizen science can be used as a methodology in which public volunteers help in data collection and classification, thereby improving the scientific community's capacity. Citizen science can also involve more direct involvement from the public, with communities initiating projects researching environment and health hazards within their own communities. Participation in citizen science projects also educates the public about the scientific process and increases awareness about different topics. Some schools incorporate citizen science projects as part of their teaching curricula for this very purpose.
== Background ==
The first use of the term "citizen science" appeared in a January 1989 issue of the MIT Technology Review, which featured three community-based labs studying environmental issues. In the 21st century, the number of citizen science projects, publications, and funding opportunities has increased. Citizen science has been used more over time, a trend helped by technological advancements. Digital citizen science platforms, such as Zooniverse and iNaturalist, store large amounts of data for many projects and are a place where volunteers can learn how to contribute to projects. For some projects, participants are instructed to collect and enter data, such as the species they observed, into large digital global databases. For other projects, participants help classify data on digital platforms. Citizen science data is also being used to develop machine learning algorithms. An example is using volunteer-classified images to train machine learning algorithms to identify species. While global participation and global databases are found on online platforms, the uniformity of data from contributors across different locations is not guaranteed. Concerns over potential data quality issues in citizen science projects, including measurement errors and biases, are recognized in the scientific community. However, statistical solutions and best practices are available to assist in addressing these concerns.
== Definition ==
The term "citizen science" has multiple origins, as well as differing concepts. "Citizen" is used in the general sense, as meaning in "citizen of the world", or the general public, rather than the legal term citizen of sovereign countries. It was first defined independently in the mid-1990s by Rick Bonney in the United States and Alan Irwin in the United Kingdom. Alan Irwin, a British sociologist, defines citizen science as "developing concepts of scientific citizenship which foregrounds the necessity of opening up science and science policy processes to the public". Irwin sought to reclaim two dimensions of the relationship between citizens and science: 1) that science should be responsive to citizens' concerns and needs; and 2) that citizens themselves could produce reliable scientific knowledge. The American ornithologist Rick Bonney, unaware of Irwin's work, defined citizen science as projects in which nonscientists, such as amateur birdwatchers, voluntarily contributed scientific data. This describes a more limited role for citizens in scientific research than Irwin's conception of the term.
The terms citizen science and citizen scientists entered the Oxford English Dictionary (OED) in June 2014. "Citizen science" is defined as "scientific work undertaken by members of the general public, often in collaboration with or under the direction of professional scientists and scientific institutions". "Citizen scientist" is defined as: (a) "a scientist whose work is characterized by a sense of responsibility to serve the best interests of the wider community (now rare)"; or (b) "a member of the general public who engages in scientific work, often in collaboration with or under the direction of professional scientists and scientific institutions; an amateur scientist". The first use of the term "citizen scientist" can be found in the magazine New Scientist in an article about ufology from October 1979.
Muki Haklay cites, from a policy report for the Wilson Center entitled "Citizen Science and Policy: A European Perspective", an alternate first use of the term "citizen science" by R. Kerson in the magazine MIT Technology Review from January 1989. Quoting from the Wilson Center report: "The new form of engagement in science received the name 'citizen science'. The first recorded example of the use of the term is from 1989, describing how 225 volunteers across the US collected rain samples to assist the Audubon Society in an acid-rain awareness raising campaign."

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A Green Paper on Citizen Science was published in 2013 by the European Commission's Digital Science Unit and Socientize.eu, which included a definition for citizen science, referring to "the general public engagement in scientific research activities when citizens actively contribute to science either with their intellectual effort or surrounding knowledge or with their tools and resources. Participants provide experimental data and facilities for researchers, raise new questions and co-create a new scientific culture."
Citizen science may be performed by individuals, teams, or networks of volunteers. Citizen scientists often partner with professional scientists to achieve common goals. Large volunteer networks often allow scientists to accomplish tasks that would be too expensive or time-consuming to accomplish through other means.
Many citizen-science projects serve education and outreach goals. These projects may be designed for a formal classroom environment or an informal education environment such as museums.
Citizen science has evolved over the past four decades. Recent projects place more emphasis on scientifically sound practices and measurable goals for public education. Modern citizen science differs from its historical forms primarily in the access for, and subsequent scale of, public participation; technology is credited as one of the main drivers of the recent explosion of citizen science activity.
In March 2015, the Office of Science and Technology Policy published a factsheet entitled "Empowering Students and Others through Citizen Science and Crowdsourcing". Quoting: "Citizen science and crowdsourcing projects are powerful tools for providing students with skills needed to excel in science, technology, engineering, and math (STEM). Volunteers in citizen science, for example, gain hands-on experience doing real science, and in many cases take that learning outside of the traditional classroom setting". The National Academies of Science cites SciStarter as a platform offering access to more than 2,700 citizen science projects and events, as well as helping interested parties access tools that facilitate project participation.
In May 2016, a new open-access journal was started by the Citizen Science Association along with Ubiquity Press called Citizen Science: Theory and Practice (CS:T&P). Quoting from the editorial article titled "The Theory and Practice of Citizen Science: Launching a New Journal", "CS:T&P provides the space to enhance the quality and impact of citizen science efforts by deeply exploring the citizen science concept in all its forms and across disciplines. By examining, critiquing, and sharing findings across a variety of citizen science endeavors, we can dig into the underpinnings and assumptions of citizen science and critically analyze its practice and outcomes."
In February 2020, Timber Press, an imprint of Workman Publishing Company, published The Field Guide to Citizen Science as a practical guide for anyone interested in getting started with citizen science.
=== Alternative definitions ===
Other definitions for citizen science have also been proposed. For example, Bruce Lewenstein of Cornell University's Communication and S&TS departments describes three possible definitions:
The participation of nonscientists in the process of gathering data according to specific scientific protocols and in the process of using and interpreting that data.
The engagement of nonscientists in true decision-making about policy issues that have technical or scientific components.
The engagement of research scientists in the democratic and policy process.
Scientists and scholars who have used other definitions include Frank N. von Hippel, Stephen Schneider, Neal Lane and Jon Beckwith. Other alternative terminologies proposed are "civic science" and "civic scientist".
A 2014 Mashable article defines a citizen scientist as: "Anybody who voluntarily contributes his or her time and resources toward scientific research in partnership with professional scientists."
In 2016, the Australian Citizen Science Association released their definition, which states "Citizen science involves public participation and collaboration in scientific research with the aim to increase scientific knowledge."
In 2020, a group of birders in the Pacific Northwest of North America, eBird Northwest, has sought to rename "citizen science" to the use of "community science", "largely to avoid using the word 'citizen' when we want to be inclusive and welcoming to any birder or person who wants to learn more about bird watching, regardless of their citizen status."
=== Typologies of citizen science ===
Citizen science initiatives are commonly categorized according to the level of involvement of the citizen scientists. Towards the lower end of involvement, terms such as crowdsourcing or contributory citizen science describe that citizen scientists contribute observations, collect data or merely offer computing power or install sensors to measure environmental variables. Towards the higher end of involvement, "extreme citizen science" and co-creation are terms used to describe initiatives in which citizen scientists are involved in decisions influencing the goal and research methods or even lead research initiatives.

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Not counting iNaturalist and eBird, the Zooniverse is home to the internet's largest, most popular and most successful citizen science projects. The Zooniverse and the suite of projects it contains is produced, maintained and developed by the Citizen Science Alliance (CSA). The member institutions of the CSA work with many academic and other partners around the world to produce projects that use the efforts and ability of volunteers to help scientists and researchers deal with the flood of data that confronts them. On 29 June 2015, the Zooniverse released a new software version with a project-building tool allowing any registered user to create a project. Project owners may optionally complete an approval process to have their projects listed on the Zooniverse site and promoted to the Zooniverse community. A NASA/JPL picture to the right gives an example from one of Zooniverse's projects The Milky Way Project.
The website CosmoQuest has as its goal "To create a community of people bent on together advancing our understanding of the universe; a community of people who are participating in doing science, who can explain why what they do matters, and what questions they are helping to answer."
CrowdCrafting enables its participants to create and run projects where volunteers help with image classification, transcription, geocoding and more. The platform is powered by PyBossa software, a free and open-source framework for crowdsourcing.
Project Soothe is a citizen science research project based at the University of Edinburgh. The aim of this research is to create a bank of soothing images, submitted by members of the public, which can be used to help others through psychotherapy and research in the future. Since 2015, Project Soothe has received over 600 soothing photographs from people in 23 countries. Anyone aged 12 years or over is eligible to participate in this research in two ways: (1) By submitting soothing photos that they have taken with a description of why the images make them feel soothed (2) By rating the photos that have been submitted by people worldwide for their soothability.
The internet has allowed for many individuals to share and upload massive amounts of data. Using the internet citizen observatories have been designed as a platform to both increase citizen participation and knowledge of their surrounding environment by collecting whatever relevant data is focused by the program. The idea is making it easier and more exciting for citizens to get and stay involved in local data collection.
The invention of social media has aided in providing massive amounts of information from the public to create citizen science programs. In a case study by Andrea Liberatore, Erin Bowkett, Catriona J. MacLeod, Eric Spurr, and Nancy Longnecker, the New Zealand Garden Bird Survey is conducted as one such project with the aid of social media. It examines the influence of utilizing a Facebook group to collect data from citizen scientists as the researchers work on the project over the span of a year. The authors claim that this use of social media greatly helps with the efficiency of this study and makes the atmosphere feel more communal.
=== Smartphone ===
The bandwidth and ubiquity afforded by smartphones has vastly expanded the opportunities for citizen science. Examples include iNaturalist, Chronolog, the San Francisco project, Mosquito Alert, the WildLab, Project Noah, and Aurorasurus. Due to their ubiquity, for example, Twitter, Facebook, and smartphones have been useful for citizen scientists, having enabled them to discover and propagate a new type of aurora dubbed STEVE in 2016.
There are also apps for monitoring birds, marine wildlife and other organisms, and the "Loss of the Night". Chronolog, another citizen science initiative, uses smartphone photography to crowdsource environmental monitoring through timelapses. By positioning their cameras at designated photo stations and submitting images, participants contribute to long-term ecological records at parks and conservation sites across 48 U.S. states and 10 countries. Restoration professionals and other land stewards use this data to measure ecosystem health and understand the effectiveness of conservation interventions like habitat restoration, controlled burns, removal of invasive species, planting of native species, and efforts to improve water quality.
"The Crowd and the Cloud" is a four-part series broadcast during April 2017, which examines citizen science. It shows how smartphones, computers and mobile technology enable regular citizens to become part of a 21st-century way of doing science. The programs also demonstrate how citizen scientists help professional scientists to advance knowledge, which helps speed up new discoveries and innovations. The Crowd & The Cloud is based upon work supported by the U.S. National Science Foundation.
=== Seismology ===
Since 1975, in order to improve earthquake detection and collect useful information, the European-Mediterranean Seismological Centre monitors the visits of earthquake eyewitnesses to its website and relies on Facebook and Twitter. More recently, they developed the LastQuake mobile application which notifies users about earthquakes occurring around the world, alerts people when earthquakes hit near them, gathers citizen seismologists' testimonies to estimate the felt ground shaking and possible damages.
=== Hydrology ===
Citizen science has been used to provide valuable data in hydrology (catchment science), notably flood risk, water quality, and water resource management. A growth in internet use and smartphone ownership has allowed users to collect and share real-time flood-risk information using, for example, social media and web-based forms. Although traditional data collection methods are well-established, citizen science is being used to fill the data gaps on a local level, and is therefore meaningful to individual communities. Data collected from citizen science can also compare well to professionally collected data. It has been demonstrated that citizen science is particularly advantageous during a flash flood because the public are more likely to witness these rarer hydrological events than scientists.
=== Plastics and pollution ===

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Citizen science includes projects that help monitor plastics and their associated pollution. These include The Ocean Cleanup, #OneLess, The Big Microplastic Survey, EXXpedition and Alliance to End Plastic Waste. Ellipsis seeks to map the distribution of litter using aerial data mapping by unmanned aerial vehicles and machine learning software. A Zooniverse project called The Plastic Tide (now finished) helped train an algorithm used by Ellipsis.
Examples of relevant articles (by date):
Citizen Science Promotes Environmental Engagement: (quote) "Citizen science projects are rapidly gaining popularity among the public, in which volunteers help gather data on species that can be used by scientists in research. And it's not just adults who are involved in these projects – even kids have collected high-quality data in the US."
Tackling Microplastics on Our Own: (quote) "Plastics, ranging from the circles of soda can rings to microbeads the size of pinheads, are starting to replace images of sewage for a leading cause of pollution – especially in the ocean". Further, "With recent backing from the Crowdsourcing and Citizen Science Act, citizen science is increasingly embraced as a tool by US Federal agencies."
Citizen Scientists Are Tracking Plastic Pollution Worldwide: (quote) "Scientists who are monitoring the spread of tiny pieces of plastic throughout the environment are getting help from a small army of citizen volunteers – and they're finding bits of polymer in some of the most remote parts of North America."
Artificial intelligence and citizen scientists: Powering the clean-up of Asia Pacific's beaches:(quote) "The main objective is to support citizen scientists cleaning up New Zealand beaches and get a better understanding of why litter is turning up, so preventive and proactive action can be taken."
Citizen science could help address Canada's plastic pollution problem: (quote) "But citizen engagement and participation in science goes beyond beach cleanups, and can be used as a tool to bridge gaps between communities and scientists. These partnerships between scientists and citizen scientists have produced real world data that have influenced policy changes."
Examples of relevant scientific studies or books include (by date):
Distribution and abundance of small plastic debris on beaches in the SE Pacific (Chile): a study supported by a citizen science project: (quote) "The citizen science project 'National Sampling of Small Plastic Debris' was supported by schoolchildren from all over Chile who documented the distribution and abundance of small plastic debris on Chilean beaches. Thirty-nine schools and nearly 1,000 students from continental Chile and Easter Island participated in the activity."
Incorporating citizen science to study plastics in the environment: (quote) "Taking advantage of public interest in the impact of plastic on the marine environment, successful Citizen Science (CS) programs incorporate members of the public to provide repeated sampling for time series as well as synoptic collections over wide geographic regions."
Marine anthropogenic litter on British beaches: A 10-year nationwide assessment using citizen science data: (quote) "Citizen science projects, whereby members of the public gather information, offer a low-cost method of collecting large volumes of data with considerable temporal and spatial coverage. Furthermore, such projects raise awareness of environmental issues and can lead to positive changes in behaviours and attitudes."
Determining Global Distribution of Microplastics by Combining Citizen Science and In-Depth Case Studies: (quote) "Our first project involves the general public through citizen science. Participants collect sand samples from beaches using a basic protocol, and we subsequently extract and quantify microplastics in a central laboratory using the standard operating procedure."
Risk Perception of Plastic Pollution: Importance of Stakeholder Involvement and Citizen Science: (quote) "The chapter finally discusses how risk perception can be improved by greater stakeholder involvement and utilization of citizen science and thereby improve the foundation for timely and efficient societal measures."
Assessing the citizen science approach as tool to increase awareness on the marine litter problem: (quote) "This paper provides a quantitative assessment of students' attitude and behaviors towards marine litter before and after their participation to SEACleaner, an educational and citizen science project devoted to monitor macro- and micro-litter in an Area belonging to Pelagos Sanctuary."
Spatial trends and drivers of marine debris accumulation on shorelines in South Eleuthera, The Bahamas using citizen science: (quote) "This study measured spatial distribution of marine debris stranded on beaches in South Eleuthera, The Bahamas. Citizen science, fetch modeling, relative exposure index and predictive mapping were used to determine marine debris source and abundance."
Making citizen science count: Best practices and challenges of citizen science projects on plastics in aquatic environments: (quote) "Citizen science is a cost-effective way to gather data over a large geographical range while simultaneously raising public awareness on the problem".
White and wonderful? Microplastics prevail in snow from the Alps to the Arctic: (quote) "In March 2018, five samples were taken at different locations on Svalbard (Fig. 1A and Table 1) by citizen scientists embarking on a land expedition by ski-doo (Aemalire project). The citizens were instructed on contamination prevention and equipped with protocol forms, prerinsed 2-liter stainless steel containers (Ecotanca), a porcelain mug, a steel spoon, and a soup ladle for sampling."
=== Citizen sensing ===
Citizen sensing can be a form of citizen science: (quote) "The work of citizen sensing, as a form of citizen science, then further transforms Stengers's notion of the work of science by moving the experimental facts and collectives where scientific work is undertaken out of the laboratory of experts and into the world of citizens." Similar sensing activities include Crowdsensing and participatory monitoring. While the idea of using mobile technology to aid this sensing is not new, creating devices and systems that can be used to aid regulation has not been straightforward. Some examples of projects that include citizen sensing are:

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Citizen Sense (2013–2018): (quote) "Practices of monitoring and sensing environments have migrated to everyday participatory applications, where users of smart phones and networked devices are able to engage with modes of environmental observation and data collection."
Breathe Project: (quote) "We use the best available science and technology to better understand the quality of the air we breathe and provide opportunities for citizens to engage and take action."
The Bristol Approach to Citizen Sensing: (quote) "Citizen Sensing is about empowering people and places to understand and use smart tech and data from sensors to tackle the issues they care about, connect with other people who can help, and take positive, practical action."
Luftdaten.info: (quote) "You and thousands of others around the world install self-built sensors on the outside their home. Luftdaten.info generates a continuously updated particular matter map from the transmitted data."
CitiSense: (quote) "CitiSense aims to co-develop a participatory risk management system (PRMS) with citizens, local authorities and organizations which enables them to contribute to advanced climate services and enhanced urban climate resilience as well as receive recommendations that support their security."
A group of citizen scientists in a community-led project targeting toxic smoke from wood burners in Bristol, has recorded 11 breaches of World Health Organization daily guidelines for ultra-fine particulate pollution over a period of six months.
In a £7M programme funded by water regulator Ofwat, citizen scientists are being trained to test for pollution and over-abstraction in 10 river catchment areas in the UK. Sensors will be used and the information gathered will be available in a central visualisation platform. The project is led by The Rivers Trust and United Utilities and includes volunteers such as anglers testing the rivers they use. The Angling Trust provides the pollution sensors, with Kristian Kent from the Trust saying: "Citizen science is a reality of the world in the future, so they're not going to be able to just sweep it under the carpet."
River water quality in the U.K. has been tested by a combined total of over 7,000 volunteers in so-called "blitzes" run over two weekends in 2024. The research by the NGO Earthwatch Europe gathered data from 4,000 freshwater sites and used standardised testing equipment provide by the NGO and Imperial College. The second blitz in October 2024 included testing for chemical pollutants, such as antibiotics, agricultural chemicals and pesticides. Results from 4,531 volunteers showed that over 61% of the freshwater sites "were in a poor state because of high levels of the nutrients phosphate and nitrate, the main source of which is sewage effluent and agricultural runoff". The data gathered through robust volunteer testing is analysed and put into a report helping provide the Environment Agency with information it does not have.
=== COVID-19 pandemic ===
Resources for computer science and scientific crowdsourcing projects concerning COVID-19 can be found on the internet or as apps. Some such projects are listed below:

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The distributed computing project Folding@home launched a program in March 2020 to assist researchers around the world who were working on finding a cure and learning more about the coronavirus pandemic. The initial wave of projects were meant to simulate potentially druggable protein targets from SARS-CoV-2 (and also its predecessor and close relation SARS-CoV, about which there is significantly more data available). In 2024, the project has been extended to look at other health issues including Alzheimer's and cancer. The project asks volunteers to download the app and donate computing power for simulations.
The distributed computing project Rosetta@home also joined the effort in March 2020. The project uses computers of volunteers to model SARS-CoV-2 virus proteins to discover possible drug targets or create new proteins to neutralize the virus. Researchers revealed that with the help of Rosetta@home, they had been able to "accurately predict the atomic-scale structure of an important coronavirus protein weeks before it could be measured in the lab." In 2022, the parent Boinc company thanked contributors for donating their computer power and helping work on the de novo protein design including vaccine development.
The OpenPandemics – COVID-19 project is a partnership between Scripps Research and IBM's World Community Grid for a distributed computing project that "will automatically run a simulated experiment in the background [of connected home PCs] which will help predict the effectiveness of a particular chemical compound as a possible treatment for COVID-19". The project asked volunteers to donate unused computing power. In 2024, the project was looking at targeting the DNA polymerase of the cytomegalovirus to identify binders.
The Eterna OpenVaccine project enables video game players to "design an mRNA encoding a potential vaccine against the novel coronavirus." In mid-2021, it was noted that the project had helped create a library of potential vaccine molecules to be tested at Stanford University; SU researchers also noted that importance of volunteers discussing the games and exchanging ideas.
In March 2020, the EU-Citizen.Science project had "a selection of resources related to the current COVID19 pandemic. It contains links to citizen science and crowdsourcing projects"
The COVID-19 Citizen Science project was "a new initiative by University of California, San Francisco physician-scientists" that "will allow anyone in the world age 18 or over to become a citizen scientist advancing understanding of the disease." By 2024, the Eureka platform had over 100,000 participants.
The CoronaReport digital journalism project was "a citizen science project which democratizes the reporting on the Coronavirus, and makes these reports accessible to other citizens." It was developed by the University of Edinburgh and asked people affected by Covid to share the social effects of the pandemic.
The COVID Symptom Tracker was a crowdsourced study of the symptoms of the virus. It was created in the UK by King's College London and Guy's and St Thomas' Hospitals. It had two million downloads by April 2020. Within three months, information from the app had helped identify six variations of Covid. Government funding ended in early 2022, but due to the large number of volunteers, Zoe decided to continue the work to study general health. By February 2023, over 75,000 people had downloaded the renamed Zoe Habit Tracker.
The Covid Near You epidemiology tool "uses crowdsourced data to visualize maps to help citizens and public health agencies identify current and potential hotspots for the recent pandemic coronavirus, COVID-19." The site was launched in Boston in March 2020; at the end of 2020 it was rebranded to Outbreaks Near Me and tracked both Covid and flu.
The We-Care project is a novel initiative by University of California, Davis researchers that uses anonymity and crowdsourced information to alert infected users and slow the spread of COVID-19.
COVID Radar was an app in the Netherlands, active between April 2020 and February 2022, with which users anonymously answered a short daily questionnaire asking about their symptoms, behavior, coronavirus test results, and vaccination status. Symptoms and behavior were visualized on a map and users received feedback on their individual risk and behaviors relative to the national mean. The app had over 250,000 users, who filled out the questionnaire over 8.5 million times. Research from this app continued to be used in 2024.
The Quantified Flu project is a co-designed citizen science effort for tracking symptoms and correlating them with physiological data from wearable devices that was launched in April 2020 and is still ongoing.
For coronavirus studies and information that can help enable citizen science, many online resources are available through open access and open science websites, including an intensive care medicine e-book chapter hosted by EMCrit and portals run by the Cambridge University Press, the Europe branch of the Scholarly Publishing and Academic Resources Coalition, The Lancet, John Wiley and Sons, and Springer Nature.
There have been suggestions that the pandemic and subsequent lockdown has boosted the public's awareness and interest in citizen science, with more people around the world having the motivation and the time to become involved in helping to investigate the illness and potentially move on to other areas of research.
== Around the world ==
The Citizen Science Global Partnership was created in 2022; the partnership brings together networks from Australia, Africa, Asia, Europe, South America and the USA.
=== Africa ===

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In South Africa (SA), citizen science projects include: the Stream Assessment Scoring System (miniSASS) which "encourages enhanced catchment management for water security in a climate stressed society."
The South African National Biodiversity Institute is partnered with iNaturalist as a platform for biodiversity observations using digital photography and geolocation technology to monitor biodiversity. Such partnerships can reduce duplication of effort, help standardise procedures and make the data more accessible.
Also in SA, "Members of the public, or 'citizen scientists' are helping researchers from the University of Pretoria to identify Phytophthora species present in the fynbos."
In June 2016, citizen science experts from across East Africa gathered in Nairobi, Kenya, for a symposium organised by the Tropical Biology Association (TBA) in partnership with the Centre for Ecology & Hydrology (CEH). The aim was "to harness the growing interest and expertise in East Africa to stimulate new ideas and collaborations in citizen science." Rosie Trevelyan of the TBA said: "We need to enhance our knowledge about the status of Africa's species and the threats facing them. And scientists can't do it all on their own. At the same time, citizen science is an extremely effective way of connecting people more closely to nature and enrolling more people in conservation action".
The website Zooniverse hosts several African citizen science projects, including: Snapshot Serengeti, Wildcam Gorongosa and Jungle Rhythms.
Nigeria has the Ibadan Bird Club whose to aim is to "exchange ideas and share knowledge about birds, and get actively involved in the conservation of birds and biodiversity."
In Namibia, Giraffe Spotter.org is "project that will provide people with an online citizen science platform for giraffes".
Within the Republic of the Congo, the territories of an indigenous people have been mapped so that "the Mbendjele tribe can protect treasured trees from being cut down by logging companies". An Android open-source app called Sapelli was used by the Mbendjele which helped them map "their tribal lands and highlighted trees that were important to them, usually for medicinal reasons or religious significance. Congolaise Industrielle des Bois then verified the trees that the tribe documented as valuable and removed them from its cutting schedule. The tribe also documented illegal logging and poaching activities."
In West Africa, the eradication of the recent outbreak of Ebola virus disease was partly helped by citizen science. "Communities learnt how to assess the risks posed by the disease independently of prior cultural assumptions, and local empiricism allowed cultural rules to be reviewed, suspended or changed as epidemiological facts emerged." "Citizen science is alive and well in all three Ebola-affected countries. And if only a fraction of the international aid directed at rebuilding health systems were to be redirected towards support for citizen science, that might be a fitting memorial to those who died in the epidemic."
The CitSci Africa Association held its International Conference in February 2024 in Nairobi.
=== Asia ===

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The Hong Kong Birdwatching Society was established in 1957, and is the only local civil society aiming at appreciating and conserving Hong Kong birds and their natural environment. Their bird surveys go back to 1958, and they carry out a number of Citizen Science events such as their yearly sparrow census.
The Bird Count India partnership consists of a large number of organizations and groups involved in birdwatching and bird surveys. They coordinate a number of Citizen Science projects such as the Kerala Bird Atlas and Mysore city Bird Atlas that map the distribution and abundance of birds of entire Indian states.
RAD@home Collaboratory is an Indian citizen science research programme in astronomy & astrophysics. Launched on 15 April 2013, by Dr Ananda Hota, this programme uses hybrid model, social media platforms and in-person training of the interested participants. In 2022, the Collaboratory, using GMRT observations and archival data from other telescopes, reported discovery of an active galactic nucleus, a radio galaxy named RAD12, spewing a large unipolar radio bubble on to its merging companion galaxy. Recently, on 2 October 2025 the Collaboratory reported discovery of the farthest and most powerful Odd Radio Circle (ORC), RAD J131346.9+500320, using the LOFAR radio telescope data.
The Taiwan Roadkill Observation Network was founded in 2011 and has more than 16,000 members as of 2019. It is a citizen science project where roadkill across Taiwan is photographed and sent to the Endemic Species Research Institute for study. Its primary goal has been to set up an eco-friendly path to mitigate roadkill challenges and popularize a national discourse on environmental issues and civil participation in scientific research. The members of the Taiwan Roadkill Observation Network volunteer to observe animals' corpses that are by caused by roadkill or by other reasons. Volunteers can then upload pictures and geographic locations of the roadkill to an internet database or send the corpses to the Endemic Species Research as specimens.Because members come from different areas of the island, the collection of data serves as an animal distribution map of the island. According to the geographical data and pictures of corpses collected by the members, the community itself and the sponsor, the Endemic Species Center could find out the hotspots and the reasons for the animals' deaths. One of the most renowned cases is that the community successfully detected rabies cases due to the huge collection of data. The corpses of Melogale moschata had accumulated for years and are thought to be carriers of rabies. Alarmed by this, the government authority took actions to prevent the prevalence of rabies in Taiwan.In another case in 2014, some citizen scientists discovered birds that had died from unknown causes near an agricultural area. The Taiwan Roadkill Observation Network cooperated with National Pingtung University of Science and Technology and engaged citizen scientists to collect bird corpses. The volunteers collected 250 bird corpses for laboratory tests, which confirmed that the bird deaths were attributable to pesticides used on crops. This prompted the Taiwanese government to restrict pesticides, and the Bill of Pesticide Management amendment was passed after the third reading in the Legislative Yuan, establishing a pesticide control system. The results indicated that Taiwan Roadkill Observation Network had developed a set of shared working methods and jointly completed certain actions. Furthermore, the community of the Taiwan Roadkill Observation Network had made real changes to road design to avoid roadkill, improved the management of usage of pesticide, epidemic prevention, as well as other examples. By mid-2024, volunteers had observed over 293,000 animals. The network, the largest citizen science project in Taiwan, noted that more than half of roadkill were amphibians (eg, frogs), while one third are reptiles and birds.
The AirBox Project was launched in Taiwan to create a participatory ecosystem with a focus on PM2.5 monitoring through AirBox devices. By the end of 2014, the public had paid more attention to the PM2.5 levels because the air pollution problem had become worse, especially in central and southern Taiwan. High PM2.5 levels are harmful to our health, with respiratory problems as an example. These pollution levels aroused public concern and led to an intensive debate about air pollution sources. Some experts suggested that air quality was affected by pollutants from mainland China, while some environmentalists believed that it was the result of industrialization, because of, for example, exhaust fumes from local power plants or factories. However, no one knew the answer because of insufficient data.Dr. Ling-Jyh Chen, a researcher of the Institute of Information Science, Academia Sinica, launched The AirBox Project. His original idea was inspired by a popular Taiwanese slogan "Save Your Environment by Yourself". As an expert in a Participatory Sensing system, he decided to take this ground-up approach to collect PM2.5 level data, and thus through open data and data analysis to have a better understanding of the possible air pollution sources. Using this ecosystem, huge amounts of data was collected from AirBox devices. This data was instantly available online, informing people of PM2.5 levels. They could then take the proper actions, such as wearing a mask or staying at home, preventing themselves from going out into the polluted environment.Data can also be analyzed to understand the possible sources of pollution and provide recommendations for improving the situation. There are four main steps to this project: i) Develop the AirBox device. Developing a device that could correctly collect the data of the PM2.5 level was time-consuming. It had taken more than three years to develop an AirBox that can be easily used, but with both high accuracy and low cost. ii) The widespread installation of AirBoxes. In the beginning, very few people were willing to install it at their homes because of their concerns about the possible harm to their health, power consumption and maintenance. Because of this, AirBoxes were only installed in a relatively small area. But with help from Taiwan's LASS (Location Aware Sensing System) community, AirBoxes appeared in all parts of Taiwan. As of February 2017, there are more than 1,600 AirBoxes installed in more than 27 countries. iii) Open Source and Data Analysis. All measurement results were released and visualized in real-time to the public through different media. Data can be analyzed to trace pollution sources. By December 2019, there were over 4,000 AirBoxes installed across the country.
Japan has a long history of citizen science involvement, the 1,200-year-old tradition of collecting records on cherry blossom flowering probably being the world's longest-running citizen science project. One of the most influential citizen science projects has also come out of Japan: Safecast. Dedicated to open citizen science for the environment, Safecast was established in the wake of the Fukushima nuclear disaster, and produces open hardware sensors for radiation and air-pollution mapping. Presenting this data via a global open data network and maps
As technology and public interest grew, the CitizenScience.Asia group was set up in 2022; it grew from an initial hackathon in Hong Kong which worked on the 2016 Zika scare. The network is part of Citizen Science Global Partnership.

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=== Europe ===
The English naturalist Charles Darwin (1809–1882) is widely regarded to have been one of the earliest citizen science contributors in Europe (see § History). A century later, citizen science was experienced by adolescents in Italy during the 1980s, working on urban energy usages and air pollution.
In his book "Citizen Science", Alan Irwin considers the role that scientific expertise can play in bringing the public and science together and building a more scientifically active citizenry, empowering individuals to contribute to scientific development. Since then a citizen science green paper was published in 2013, and European Commission policy directives have included citizen science as one of five strategic areas with funding allocated to support initiatives through the 'Science With and For Society (SwafS)', a strand of the Horizon 2020 programme. This includes significant awards such as the EU Citizen Science Project, which is creating a hub for knowledge sharing, coordination, and action. The European Citizen Science Association (ECSA) was set up in 2014 to encourage the growth of citizen science across Europe, to increase public participation in scientific processes, mainly by initiating and supporting citizen science projects as well as conducting research. ECSA has a membership of over 250 individual and organisational members from over 30 countries across the European Union and beyond.
Examples of citizen science organisations and associations based in Europe include the Biosphere Expeditions (Ireland), Bürger schaffen Wissen (Germany), Scivil (Belgium), Citizen Science Lab at Leiden University (Netherlands), Ibercivis (See External Links), Österreich forscht (Austria). Other organisations can be found here: EU Citizen Science.
The European Citizen Science Association was created in 2014, with some nations also having national bodies, such as Citizen Science Ireland.
In 2023, the European Union Prize for Citizen Science was established. Bestowed through Ars Electronica, the prize was designed to honor, present and support "outstanding projects whose social and political impact advances the further development of a pluralistic, inclusive and sustainable society in Europe".
==== Example projects ====
Garden birdwatches such as the Irish Garden Bird Survey by BirdWatch Ireland and the Big Garden Birdwatch by the Royal Society for the Protection of Birds invite members of the public to record the wild birds that they see in their garden. The species are then tracked over time.
Photographs of The Northern Lights or "Aurora Borealis" over the island of Ireland taken by the public were collected by scientists in Ireland, in a project called Aurora Éire.
Water Blitz is a citizen science project by Dublin City University, where citizen scientists help collect water samples and provide their perspectives on water quality and pollution.
The Irish Hedgehog Survey coordinated by scientists at the National University of Ireland at Galway encourages recording on the distribution and health of hedgehogs in Ireland
=== Latin America ===
In 2015, the Asháninka people from Apiwtxa, which crosses the border between Brazil and Peru, began using the Android app Sapelli to monitor their land. The Ashaninka have "faced historical pressures of disease, exploitation and displacement, and today still face the illegal invasion of their lands by loggers and hunters. This monitoring project shows how the Apiwtxa Ashaninka from the Kampa do Rio Amônia Indigenous Territory, Brazil, are beginning to use smartphones and technological tools to monitor these illegal activities more effectively."
In Argentina, two smartphone Android applications are available for citizen science. i) AppEAR has been developed at the Institute of Limnology and was launched in May 2016. Joaquín Cochero is a researcher who developed an "application that appeals to the collaboration of users of mobile devices in collecting data that allow the study of aquatic ecosystems" (translation). Cochero stated: "Not much of citizen science in Argentina, just a few more oriented to astronomy specific cases. As ours is the first. And I have volunteers from different parts of the country that are interested in joining together to centralize data. That's great because these types of things require many people participate actively and voluntarily" (translation). ii) eBird was launched in 2013, and has so far identified 965 species of birds. eBird in Argentina is "developed and managed by the Cornell Lab of Ornithology at Cornell University, one of the most important ornithological institutions in the world, and locally presented recently with the support of the Ministry of Science, Technology and Productive Innovation of the Nation (MINCyT)" (translation).
In Argentina, a citizen-led initiative known as Human Cognitive Engineering (HCE/IC-H), established in 2025, investigates biophysical pathways such as PIEZO1 and PIEZO2 mechanotransduction. This project utilizes open-source repositories to document Prior Art, aiming to maintain fundamental biological mechanisms as public knowledge in alignment with UNESCO 2026 Neuro-rights standards. The framework describes human physiology through General Systems Theory (GST), focusing on fascial signaling and the Grotthuss proton-jump mechanism for systemic homeostasis.

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Projects in Brazil include: i) Platform and mobile app 'Missions' has been developed by IBM in their São Paulo research lab with Brazil's Ministry for Environment and Innovation (BMEI). Sergio Borger, an IBM team lead in São Paulo, devised the crowdsourced approach when BMEI approached the company in 2010. They were looking for a way to create a central repository for the rainforest data. Users can upload photos of a plant species and its components, enter its characteristics (such as color and size), compare it against a catalog photo and classify it. The classification results are juried by crowdsourced ratings. ii) Exoss Citizen Science is a member of Astronomers Without Borders and seeks to explore the southern sky for new meteors and radiants. Users can report meteor fireballs through uploading pictures on to a webpage or by linking to YouTube. iii) The Information System on Brazilian Biodiversity (SiBBr) was launched in 2014 "aiming to encourage and facilitate the publication, integration, access and use of information about the biodiversity of the country." Their initial goal "was to gather 2.5 million occurrence records of species from biological collections in Brazil and abroad up to the end of 2016. It is now expected that SiBBr will reach nine million records in 2016." Andrea Portela said: "In 2016, we will begin with the citizen science. They are tools that enable anyone, without any technical knowledge, to participate. With this we will achieve greater engagement with society. People will be able to have more interaction with the platform, contribute and comment on what Brazil has." iv) The Brazilian Marine Megafauna Project (Iniciativa Pro Mar) is working with the European CSA towards its main goal, which is the "sensibilization of society for marine life issues" and concerns about pollution and the over-exploitation of natural resources. Having started as a project monitoring manta ray, it now extends to whale shark and educating schools and divers within the Santos area. Its social media activities include a live streaming of a citizen science course to help divers identify marine megafauna. v) A smartphone app called Plantix has been developed by the Leibniz Centre for Agricultural Landscape Research (ZALF) which helps Brazilian farmers discover crop diseases quicker and helps fight them more efficiently. Brazil is a very large agricultural exporter, but between 10 and 30% of crops fail because of disease. "The database currently includes 175 frequently occurring crop diseases and pests as well as 40,000 photos. The identification algorithm of the app improves with every image which records a success rate of over 90 per cent as of approximately 500 photos per crop disease." vi) In an Atlantic Ocean forest region in Brazil, an effort to map the genetic riches of soil is under way. The Drugs From Dirt initiative, based at the Rockefeller University, seeks to turn up bacteria that yield new types of antibiotics – the Brazilian region being particularly rich in potentially useful bacterial genes. Approximately a quarter of the 185 soil samples have been taken by Citizen Scientists without which the project could not run.
In Chile citizen science projects include (some websites in Spanish): i) Testing new cancer therapies with scientists from the Science Foundation for Life. ii) Monitoring the population of the Chilean bumblebee. iii) Monitoring the invasive ladybird Chinita arlequín. iv) Collecting rain water data. v) Monitoring various pollinating fly populations. vi) Providing information and field data on the abundance and distribution of various species of rockfish. vii) Investigating the environmental pollution by plastic litter.
Projects in Colombia include (some websites in Spanish): i) The Communications Project of the Humboldt Institute along with the Organization for Education and Environmental Protection initiated projects in the Bogotá wetlands of Cordoba and El Burro, which have a lot of biodiversity. ii) In the Model Forest of Risaralda, the Colombia 'proyecto de Ciencia Abierta y Colaborativa' promotes citizen participation in research related to how the local environment is adapting to climate change. The first meeting took place in the Flora and Fauna Sanctuary Otún Quimbaya. iii) The Citizen Network Environmental Monitoring (CLUSTER), based in the city of Bucaramanga, seeks to engage younger students in data science, who are trained in building weather stations with open repositories based on free software and open hardware data. iv) The Symposium on Biodiversity has adapted the CS tool iNaturalist for use in Colombia. v) The Sinchi Amazonic Institute of Scientific Research seeks to encourage the development and diffusion of knowledge, values and technologies on the management of natural resources for ethnic groups in the Amazon. This research should further the use of participatory action research schemes and promoting participation communities.
Since 2010, the Pacific Biodiversity Institute (PBI) seeks "volunteers to help identify, describe and protect wildland complexes and roadless areas in South America". The PBI "are engaged in an ambitious project with our Latin American conservation partners to map all the wildlands in South America, to evaluate their contribution to global biodiversity and to share and disseminate this information."
In Mexico, a citizen science project has monitored rainfall data that is linked to a hydrologic payment for ecosystem services project.

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== Conferences ==
The first Conference on Public Participation in Scientific Research was held in Portland, Oregon, in August 2012. Citizen science is now often a theme at large conferences, such as the annual meeting of the American Geophysical Union.
In 2010, 2012 and 2014 there were three Citizen Cyberscience summits, organised by the Citizen Cyberscience Centre in Geneva and University College London. The 2014 summit was hosted in London and attracted over 300 participants.
In November 2015, the ETH Zürich and University of Zürich hosted an international meeting on the "Challenges and Opportunities in Citizen Science".
The first citizen science conference hosted by the Citizen Science Association was in San Jose, California, in February 2015 in partnership with the AAAS conference. The Citizen Science Association conference, CitSci 2017, was held in Saint Paul, Minnesota, United States, between 17 and 20 May 2017. The conference had more than 600 attendees. The next CitSci was in March 2019 in Raleigh, North Carolina.
The platform "Österreich forscht" hosts the annual Austrian citizen science conference since 2015.
== In popular culture ==
Barbara Kingsolver's 2012 novel Flight Behaviour looks at the effects of citizen science on a housewife in Appalachia, when her interest in butterflies brings her into contact with scientists and academics.
== See also ==
== Notes ==
== References ==
== Further reading ==
Web, Cameron; Williams, Craig; Sousa, Larissa Braz; Doherty, Seamus; Fricker, Stephen Robert (11 December 2019). "As heat strikes, here's one way to help fight disease-carrying and nuisance mosquitoes". The Conversation. "The Mozzie Monitors program marks the first time formal mosquito trapping has been combined with citizen science." (Australian project)
Franzoni, Chiara; Sauermann, Henry (February 2014). "Crowd science: The organization of scientific research in open collaborative projects". Research Policy. 43 (1): 1–20. doi:10.1016/j.respol.2013.07.005. hdl:11311/754644. SSRN 2167538.
Dick Kasperowsik (interviewed by Ulrich Herb): Citizen Science as democratization of science? In: telepolis, 2016, 27 August
Ridley, Matt. (8 February 2012) "Following the Crowd to Citizen Science". The Wall Street Journal
Young, Jeffrey R. (28 May 2010). "Crowd Science Reaches New Heights", The Chronicle of Higher Education
Sauermann, Henry; Franzoni, Chiara (20 January 2015). "Crowd science user contribution patterns and their implications". Proceedings of the National Academy of Sciences. 112 (3): 679–684. Bibcode:2015PNAS..112..679S. doi:10.1073/pnas.1408907112. PMC 4311847. PMID 25561529. SSRN 2545945.
Bourjon, Philippe; Ducarme, Frédéric; Quod, Jean-Pascal; Sweet, Michael (2018). "Involving recreational snorkelers in inventory improvement or creation: a case study in the Indian Ocean". Cahiers de Biologie Marine. 59: 451–460. doi:10.21411/CBM.A.B05FC714.
Albagli, Sarita; Iwama, Allan Yu (2022). "Citizen science and the right to research: building local knowledge of climate change impacts". Humanities and Social Sciences Communications. 9 (1) 39: 1–13. doi:10.1057/s41599-022-01040-8.
Fritz, Steffen; See, Linda; Carlson, Tyler; Haklay, Mordechai (Muki); Oliver, Jessie L.; Fraisl, Dilek; Mondardini, Rosy; Brocklehurst, Martin; Shanley, Lea A.; Schade, Sven; Wehn, Uta; Abrate, Tommaso; Anstee, Janet; Arnold, Stephan; Billot, Matthew; Campbell, Jillian; Espey, Jessica; Gold, Margaret; Hager, Gerid; He, Shan; Hepburn, Libby; Hsu, Angel; Long, Deborah; Masó, Joan; McCallum, Ian; Muniafu, Maina; Moorthy, Inian; Obersteiner, Michael; Parker, Alison J.; Weisspflug, Maike; West, Sarah (2019). "Citizen science and the United Nations Sustainable Development Goals". Nature Sustainability. 2 (10): 922–930. Bibcode:2019NatSu...2..922F. doi:10.1038/s41893-019-0390-3.
== External links ==
Media related to Citizen science at Wikimedia Commons
"Controversy over the term 'citizen science'". CBC News. 13 August 2021. Retrieved 15 April 2023.

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=== Related fields ===
In a Smart City era, Citizen Science relies on various web-based tools, such as WebGIS, and becomes Cyber Citizen Science. Some projects, such as SETI@home, use the Internet to take advantage of distributed computing. These projects are generally passive. Computation tasks are performed by volunteers' computers and require little involvement beyond initial setup. There is disagreement as to whether these projects should be classified as citizen science.
The astrophysicist and Galaxy Zoo co-founder Kevin Schawinski stated: "We prefer to call this [Galaxy Zoo] citizen science because it's a better description of what you're doing; you're a regular citizen but you're doing science. Crowd sourcing sounds a bit like, well, you're just a member of the crowd and you're not; you're our collaborator. You're pro-actively involved in the process of science by participating."
Compared to SETI@home, "Galaxy Zoo volunteers do real work. They're not just passively running something on their computer and hoping that they'll be the first person to find aliens. They have a stake in science that comes out of it, which means that they are now interested in what we do with it, and what we find."
Citizen policy may be another result of citizen science initiatives. Bethany Brookshire (pen name SciCurious) writes: "If citizens are going to live with the benefits or potential consequences of science (as the vast majority of them will), it's incredibly important to make sure that they are not only well informed about changes and advances in science and technology, but that they also ... are able to ... influence the science policy decisions that could impact their lives." In "The Rightful Place of Science: Citizen Science", editors Darlene Cavalier and Eric Kennedy highlight emerging connections between citizen science, civic science, and participatory technology assessment.
== Benefits and limitations ==
The general public's involvement in scientific projects has become a means of encouraging curiosity and greater understanding of science while providing an unprecedented engagement between professional scientists and the general public. In a research report published by the U.S. National Park Service in 2008, Brett Amy Thelen and Rachel K. Thiet mention the following concerns, previously reported in the literature, about the validity of volunteer-generated data:
Some projects may not be suitable for volunteers, for instance, when they use complex research methods or require a great deal of (often repetitive) work.
If volunteers lack proper training in research and monitoring protocols, the data they collect might introduce bias into the dataset.
The question of data accuracy, in particular, remains open. John Losey, who created the Lost Ladybug citizen science project, has argued that the cost-effectiveness of citizen science data can outweigh data quality issues, if properly managed.
In December 2016, authors M. Kosmala, A. Wiggins, A. Swanson and B. Simmons published a study in the journal Frontiers in Ecology and the Environment called "Assessing Data Quality in Citizen Science". The abstract describes how ecological and environmental citizen science projects have enormous potential to advance science. Citizen science projects can influence policy and guide resource management by producing datasets that are otherwise not feasible to generate. In the section "In a Nutshell" (pg3), four condensed conclusions are stated. They are:

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They conclude that as citizen science continues to grow and mature, a key metric of project success they expect to see will be a growing awareness of data quality. They also conclude that citizen science will emerge as a general tool helping "to collect otherwise unobtainable high-quality data in support of policy and resource management, conservation monitoring, and basic science."
A study of Canadian lepidoptera datasets published in 2018 compared the use of a professionally curated dataset of butterfly specimen records with four years of data from a citizen science program, eButterfly. The eButterfly dataset was used as it was determined to be of high quality because of the expert vetting process used on site, and there already existed a dataset covering the same geographic area consisting of specimen data, much of it institutional. The authors note that, in this case, citizen science data provides both novel and complementary information to the specimen data. Five new species were reported from the citizen science data, and geographic distribution information was improved for over 80% of species in the combined dataset when citizen science data was included.
Several recent studies have begun to explore the accuracy of citizen science projects and how to predict accuracy based on variables like expertise of practitioners. One example is a 2021 study by Edgar Santos-Fernandez and Kerrie Mengersen of the British Ecological Society, who utilized a case study which used recent R and Stan programming software to offer ratings of the accuracy of species identifications performed by citizen scientists in Serengeti National Park, Tanzania. This provided insight into possible problems with processes like this which include, "discriminatory power and guessing behaviour". The researchers determined that methods for rating the citizen scientists themselves based on skill level and expertise might make studies they conduct more easy to analyze.
Studies that are simple in execution are where citizen science excels, particularly in the field of conservation biology and ecology. For example, in 2019, Sumner et al. compared the data of vespid wasp distributions collected by citizen scientists with the 4-decade, long-term dataset established by the BWARS. They set up the Big Wasp Survey from 26 August to 10 September 2017, inviting citizen scientists to trap wasps and send them for identification by experts where data was recorded. The results of this study showed that the campaign garnered over 2,000 citizen scientists participating in data collection, identifying over 6,600 wasps. This experiment provides strong evidence that citizen science can generate potentially high-quality data comparable to that of expert data collection, within a shorter time frame. Although the experiment was to originally test the strength of citizen science, the team also learned more about Vespidae biology and species distribution in the United Kingdom. With this study, the simple procedure enabled citizen science to be executed in a successful manner. A study by J. Cohn describes that volunteers can be trained to use equipment and process data, especially considering that a large proportion of citizen scientists are individuals who are already well-versed in the field of science.
The demographics of participants in citizen science projects are overwhelmingly White adults, of above-average income, having a university degree. Other groups of volunteers include conservationists, outdoor enthusiasts, and amateur scientists. As such, citizen scientists are generally individuals with a pre-understanding of the scientific method and how to conduct sensible and just scientific analysis.
== Ethics ==
Various studies have been published that explore the ethics of citizen science, including issues such as intellectual property and project design.(e.g.) The Citizen Science Association (CSA), based at the Cornell Lab of Ornithology, and the European Citizen Science Association (ECSA), based in the Museum für Naturkunde in Berlin, have working groups on ethics and principles.
In September 2015, ECSA published its Ten Principles of Citizen Science, which have been developed by the "Sharing best practice and building capacity" working group of ECSA, led by the Natural History Museum, London with input from many members of the association.
The medical ethics of internet crowdsourcing has been questioned by Graber & Graber in the Journal of Medical Ethics. In particular, they analyse the effect of games and the crowdsourcing project Foldit. They conclude: "games can have possible adverse effects, and that they manipulate the user into participation".
In March 2019, the online journal Citizen Science: Theory and Practice launched a collection of articles on the theme of Ethical Issues in Citizen Science. The articles are introduced with (quoting): "Citizen science can challenge existing ethical norms because it falls outside of customary methods of ensuring that research is conducted ethically. What ethical issues arise when engaging the public in research? How have these issues been addressed, and how should they be addressed in the future?"
In June 2019, East Asian Science, Technology and Society: An International Journal (EASTS) published an issue titled "Citizen Science: Practices and Problems" which contains 15 articles/studies on citizen science, including many relevant subjects of which ethics is one. Quoting from the introduction "Citizen, Science, and Citizen Science": "The term citizen science has become very popular among scholars as well as the general public, and, given its growing presence in East Asia, it is perhaps not a moment too soon to have a special issue of EASTS on the topic."
Use of citizen science volunteers as de facto unpaid laborers by some commercial ventures have been criticized as exploitative.
Ethics in citizen science in the health and welfare field, has been discussed in terms of protection versus participation. Public involvement researcher Kristin Liabo writes that health researcher might, in light of their ethics training, be inclined to exclude vulnerable individuals from participation, to protect them from harm. However, she argues these groups are already likely to be excluded from participation in other arenas, and that participation can be empowering and a possibility to gain life skills that these individuals need. Whether or not to become involved should be a decision these individuals should be involved in and not a researcher decision.

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=== Data governance, privacy and sovereignty ===
As citizen science becomes increasingly influenced by digital platforms and sensors, governance questions go beyond research ethics to include data protection law and community control over reuse. Under the General Data Protection Regulation (GDPR), participatory projects that involve personal data can complicate the usual separation between professional researchers ("controllers") and participants ("data subjects"): citizen scientists may be considered joint controllers when they share or shape project purposes, which could expose volunteers to compliance responsibilities and create risks for both participant protections and project legitimacy. Practical guidance for citizen science therefore increasingly requires early planning for lawful data handling, clear allocation of responsibilities, and transparency about data flows across collection, storage, and sharing.
A second governance challenge concerns power asymmetries in open data. Because volunteers often produce data while institutions handle and publish it, decisions about openness, attribution, and access restrictions can include unequal priorities and certain vulnerabilities. Ethical open-data practice in citizen science is therefore frequently framed as a matter of data governance, not only technical quality. These concerns also extend to environmental monitoring where data may be politically sensitive (e.g., pollution exposure, land use, biodiversity decline).
Finally, monitoring initiatives have highlighted data sovereignty: the principle that indigenous peoples and local communities should govern collection, ownership, access and use of data connected to territories and cultural knowledge; so that digital monitoring does not reproduce colonialist tendencies between knowledge holders and external institutions. Related international policy discussions on open science explicitly point out that openness should not overrule privacy, equity, or indigenous rights over traditional knowledge.
== Economic worth ==
In the research paper "Can citizen science enhance public understanding of science?" by Bonney et al. 2016, statistics which analyse the economic worth of citizen science are used, drawn from two papers: i) Sauermann and Franzoni 2015, and
ii) Theobald et al. 2015. In "Crowd science user contribution patterns and their implications" by Sauermann and Franzoni (2015), seven projects from the Zooniverse web portal are used to estimate the monetary value of the citizen science that had taken place. The seven projects are: Solar Stormwatch, Galaxy Zoo Supernovae, Galaxy Zoo Hubble, Moon Zoo, Old Weather, The Milky Way Project and Planet Hunters. Using data from 180 days in 2010, they find a total of 100,386 users participated, contributing 129,540 hours of unpaid work. Estimating at a rate of $12 an hour (an undergraduate research assistant's basic wage), the total contributions amount to $1,554,474, an average of $222,068 per project. The range over the seven projects was from $22,717 to $654,130.
In "Global change and local solutions: Tapping the unrealized potential of citizen science for biodiversity research" by Theobald et al. 2015, the authors surveyed 388 unique biodiversity-based projects. Quoting: "We estimate that between 1.36 million and 2.28 million people volunteer annually in the 388 projects we surveyed, though variation is great" and that "the range of in-kind contribution of the volunteerism in our 388 citizen science projects as between $667 million to $2.5 billion annually."
Worldwide participation in citizen science continues to grow. A list of the top five citizen science communities compiled by Marc Kuchner and Kristen Erickson in July 2018 shows a total of 3.75 million participants, although there is likely substantial overlap between the communities.

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== Relations with education and academia ==
There have been studies published which examine the place of citizen science within education.(e.g.) Teaching aids can include books and activity or lesson plans.(e.g.). Some examples of studies are:
From the Second International Handbook of Science Education, a chapter entitled: "Citizen Science, Ecojustice, and Science Education: Rethinking an Education from Nowhere", by Mueller and Tippins (2011), acknowledges in the abstract that: "There is an emerging emphasis in science education on engaging youth in citizen science." The authors also ask: "whether citizen science goes further with respect to citizen development." The abstract ends by stating that the "chapter takes account of the ways educators will collaborate with members of the community to effectively guide decisions, which offers promise for sharing a responsibility for democratizing science with others."
From the journal Democracy and Education, an article entitled: "Lessons Learned from Citizen Science in the Classroom" by authors Gray, Nicosia and Jordan (GNJ; 2012) gives a response to a study by Mueller, Tippins and Bryan (MTB) called "The Future of Citizen Science". GNJ begins by stating in the abstract that "The Future of Citizen Science": "provides an important theoretical perspective about the future of democratized science and K12 education." But GRB state: "However, the authors (MTB) fail to adequately address the existing barriers and constraints to moving community-based science into the classroom." They end the abstract by arguing: "that the resource constraints of scientists, teachers, and students likely pose problems to moving true democratized science into the classroom."
In 2014, a study was published called "Citizen Science and Lifelong Learning" by R. Edwards in the journal Studies in the Education of Adults. Edwards begins by writing in the abstract that citizen science projects have expanded over recent years and engaged citizen scientists and professionals in diverse ways. He continues: "Yet there has been little educational exploration of such projects to date." He describes that "there has been limited exploration of the educational backgrounds of adult contributors to citizen science". Edwards explains that citizen science contributors are referred to as volunteers, citizens or as amateurs. He ends the abstract: "The article will explore the nature and significance of these different characterisations and also suggest possibilities for further research."
In the journal Microbiology and Biology Education a study was published by Shah and Martinez (2015) called "Current Approaches in Implementing Citizen Science in the Classroom". They begin by writing in the abstract that citizen science is a partnership between inexperienced amateurs and trained scientists. The authors continue: "With recent studies showing a weakening in scientific competency of American students, incorporating citizen science initiatives in the curriculum provides a means to address deficiencies". They argue that combining traditional and innovative methods can help provide a practical experience of science. The abstract ends: "Citizen science can be used to emphasize the recognition and use of systematic approaches to solve problems affecting the community."
In November 2017, authors Mitchell, Triska and Liberatore published a study in PLOS One titled "Benefits and Challenges of Incorporating Citizen Science into University Education". The authors begin by stating in the abstract that citizen scientists contribute data with the expectation that it will be used. It reports that citizen science has been used for first year university students as a means to experience research. They continue: "Surveys of more than 1500 students showed that their environmental engagement increased significantly after participating in data collection and data analysis." However, only a third of students agreed that data collected by citizen scientists was reliable. A positive outcome of this was that the students were more careful of their own research. The abstract ends: "If true for citizen scientists in general, enabling participants as well as scientists to analyse data could enhance data quality, and so address a key constraint of broad-scale citizen science programs."
Citizen science has also been described as challenging the "traditional hierarchies and structures of knowledge creation".

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== History ==
While citizen science developed at the end of the 20th century, characteristics of citizen science are not new. Prior to the 20th century, science was often the pursuit of gentleman scientists, amateur or self-funded researchers such as Sir Isaac Newton, Benjamin Franklin, and Charles Darwin. Women citizen scientists from before the 20th century include Florence Nightingale who "perhaps better embodies the radical spirit of citizen science". Before the professionalization of science by the end of the 19th century, most pursued scientific projects as an activity rather than a profession itself, an example being amateur naturalists in the 18th and 19th centuries.
During the British colonization of North America, American Colonists recorded the weather, offering much of the information now used to estimate climate data and climate change during this time period. These people included John Campanius Holm, who recorded storms in the mid-1600s, as well as George Washington, Thomas Jefferson, and Benjamin Franklin who tracked weather patterns during America's founding. Their work focused on identifying patterns by amassing their data and that of their peers and predecessors, rather than specific professional knowledge in scientific fields. Some consider these individuals as the progenitors of the citizen scientist concept, while others ascribe this designation to prominent figures such as Leonardo da Vinci and Charles Darwin. However, there are also those who perceive citizen science as a distinct movement that developed later on, building on the preceding history of science.
However, by the mid-20th century, the scientific community was dominated by researchers employed by universities and government research laboratories. By the 1970s, this transformation was being called into question. Philosopher Paul Feyerabend called for a "democratization of science". Biochemist Erwin Chargaff advocated a return to science by nature-loving amateurs in the tradition of Descartes, Newton, Leibniz, Buffon, and Darwin. This approach would prioritize the contributions of "amateurship instead of money-biased technical bureaucrats".
A 2016 study indicates that the largest impact of citizen science is evident in research domains such as biology, conservation, and ecology. The primary utilization of citizen science is as a methodology for data collection and classification.
=== Amateur astronomy ===
Astronomy has long been a field where amateurs have contributed throughout time, all the way up to the present day.
Collectively, amateur astronomers observe a variety of celestial objects and phenomena sometimes with equipment that they build themselves. Common targets of amateur astronomers include the Moon, planets, stars, comets, meteor showers, and a variety of deep-sky objects such as star clusters, galaxies, and nebulae. Observations of comets and stars are also used to measure the local level of artificial skyglow. One branch of amateur astronomy, amateur astrophotography, involves the taking of photos of the night sky. Many amateurs like to specialize in the observation of particular objects, types of objects, or types of events that interest them.
The American Association of Variable Star Observers has gathered data on variable stars for educational and professional analysis since 1911 and promotes participation beyond its membership on its Citizen Sky website.
Project PoSSUM is a relatively new organization, started in March 2012, which trains citizen scientists of many ages to go on polar suborbital missions. On these missions, they study noctilucent clouds with remote sensing, which reveals interesting clues about changes in the upper atmosphere and the ozone due to climate change. This is a form of citizen science which trains younger generations to be ambitious, participating in intriguing astronomy and climate change science projects even without a professional degree.
=== Butterfly counts ===
Butterfly counts have a long tradition of involving individuals in the study of butterflies' range and their relative abundance. Two long-running programs are the UK Butterfly Monitoring Scheme (started in 1976) and the North American Butterfly Association's Butterfly Count Program (started in 1975). There are various protocols for monitoring butterflies and different organizations support one or more of transects, counts and/or opportunistic sightings. eButterfly is an example of a program designed to capture any of the three types of counts for observers in North America. Species-specific programs also exist, with monarchs the prominent example. Two examples of this involve the counting of monarch butterflies during the fall migration to overwintering sites in Mexico: (1) Monarch Watch is a continent-wide project, while (2) the Cape May Monarch Monitoring Project is an example of a local project.
=== Ornithology ===

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Citizen science projects have become increasingly focused on providing benefits to scientific research. The North American Bird Phenology Program (historically called the Bird Migration and Distribution records) may have been the earliest collective effort of citizens collecting ornithological information in the U.S. The program, dating back to 1883, was started by Wells Woodbridge Cooke. Cooke established a network of observers around North America to collect bird migration records. The Audubon Society's Christmas Bird Count, which began in 1900, is another example of a long-standing tradition of citizen science which has persisted to the present day, now containing a collection of six million handwritten migration observer cards that date back to the 19th century. Participants input this data into an online database for analysis. Citizen scientists help gather data that will be analyzed by professional researchers, and can be used to produce bird population and biodiversity indicators.
Raptor migration research relies on the data collected by the hawkwatching community. This mostly volunteer group counts migrating accipiters, buteos, falcons, harriers, kites, eagles, osprey, vultures and other raptors at hawk sites throughout North America during the spring and fall seasons. The daily data is uploaded to hawkcount.org where it can be viewed by professional scientists and the public.
Other programs in North America include Project FeederWatch, which is affiliated with the Cornell Lab of Ornithology.
Such indices can be useful tools to inform management, resource allocation, policy and planning. For example, European breeding bird survey data provide input for the Farmland Bird Index, adopted by the European Union as a structural indicator of sustainable development. This provides a cost-effective alternative to government monitoring.
Similarly, data collected by citizen scientists as part of BirdLife Australia's has been analysed to produce the first-ever Australian Terrestrial Bird Indices.
In the UK, the Royal Society for the Protection of Birds collaborated with a children's TV show to create a national birdwatching day in 1979; the campaign has continued for over 40 years and in 2024, over 600,000 people counted almost 10 million birds during the Big Garden Birdwatch weekend.
Most recently, more programs have sprung up worldwide, including NestWatch, a bird species monitoring program which tracks data on reproduction. This might include studies on when and how often nesting occurs, counting eggs laid and how many hatch successfully, and what proportion of hatchlings survive infancy. Participation in this program is extremely easy for the general public to join. Using the recently created nest watch app which is available on almost all devices, anyone can begin to observe their local species, recording results every 3 to 4 days within the app. This forms a continually-growing database which researchers can view and utilize to understand trends within specific bird populations.
=== Citizen oceanography ===
The concept of citizen science has been extended to the ocean environment for characterizing ocean dynamics and tracking marine debris. For example, the mobile app Marine Debris Tracker is a joint partnership of National Oceanic and Atmospheric Administration and the University of Georgia. Long term sampling efforts such as the continuous plankton recorder has been fitted on ships of opportunity since 1931. Plankton collection by sailors and subsequent genetic analysis was pioneered in 2013 by Indigo V Expeditions as a way to better understand marine microbial structure and function.
=== Coral reefs ===
Citizen science in coral reef studies developed in the 21st century.
Underwater photography has become more popular since the development of moderate priced digital cameras with waterproof housings in the early 2000s, resulting on millions of pictures posted every year on various websites and social media. This mass of documentation has great scientific potential, as millions of tourists possess a much superior coverage power than professional scientists, who cannot spend so much time in the field.
As a consequence, several participative sciences programs have been developed, supported by geotagging and identification web sites such as iNaturalist. The Monitoring through many eyes project collates thousands of underwater images of the Great Barrier Reef and provides an interface for elicitation of reef health indicators.
The National Oceanic and Atmospheric Administration (NOAA) also offers opportunities for volunteer participation. By taking measurements in The United States' National Marine Sanctuaries, citizens contribute data to marine biology projects. In 2016, NOAA benefited from 137,000 hours of research.
There also exist protocols for auto-organization and self-teaching aimed at biodiversity-interested snorkelers, in order for them to turn their observations into sound scientific data, available for research. This kind of approach has been successfully used in Réunion island, allowing for tens of new records and even new species.
=== Freshwater fish ===
Aquarium hobbyists and their respective organizations are very passionate about fish conservation and often more knowledgeable about specific fish species and groups than scientific researchers. They have played an important role in the conservation of freshwater fishes by discovering new species, maintaining extensive databases with ecological information on thousands of species (such as for catfish, Mexican freshwater fishes, killifishes, cichlids), and successfully keeping and providing endangered and extinct-in-the-wild species for conservation projects. The CARES (Conservation, Awareness, Recognition, Encouragement, and Support) preservation program is the largest hobbyist organization containing over 30 aquarium societies and international organizations, and encourages serious aquarium hobbyists to devote tank space to the most threatened or extinct-in-the-wild species to ensure their survival for future generations.
=== Amphibians ===
Citizen scientists also work to monitor and conserve amphibian populations. One recent project is FrogWatch USA, organized by the Association of Zoos and Aquariums. Participants are invited to educate themselves on their local wetlands and help to save amphibian populations by reporting the data on the calls of local frogs and toads. The project already has over 150,000 observations from more than 5000 contributors. Participants are trained by program coordinators to identify calls and utilize this training to report data they find between February and August of each "monitoring season". Data is used to monitor diversity, invasion, and long-term shifts in population health within these frog and toad communities.

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=== Rocky reefs ===
Reef Life Survey is a marine life monitoring programme based in Hobart, Tasmania. The project uses recreational divers that have been trained to make fish and invertebrate counts, using an approximate 50 m constant depth transect of tropical and temperate reefs, which might include coral reefs. Reef Life Survey is international in its scope, but the data collectors are predominantly from Australia. The database is available to marine ecology researchers, and is used by several marine protected area managements in Australia, New Zealand, American Samoa and the eastern Pacific. Its results have also been included in the Australian Ocean DATA Network.
=== Agriculture ===
Farmer participation in experiments has a long tradition in agricultural science. There are many opportunities for citizen engagement in different parts of food systems. Citizen science is actively used for crop variety selection for climate adaptation, involving thousands of farmers. Citizen science has also played a role in furthering sustainable agriculture.
=== Art history ===
Citizen science has a long tradition in natural science. Today, citizen science projects can also be found in various fields of science like art history. For example, the Zooniverse project AnnoTate is a transcription tool developed to enable volunteers to read and transcribe the personal papers of British-born and émigré artists. The papers are drawn from the Tate Archive. Another example of citizen science in art history is ARTigo. ARTigo collects semantic data on artworks from the footprints left by players of games featuring artwork images. From these footprints, ARTigo automatically builds a semantic search engine for artworks.
=== Biodiversity ===
Citizen science has made significant contributions to the analysis of biodiversity across the world. A majority of data collected has been focused primarily on species occurrence, abundance and phenology, with birds being primarily the most popular group observed. There is growing efforts to expand the use of citizen science across other fields. Past data on biodiversity has had limitations in the quantity of data to make any meaningful broad connections to losses in biodiversity. Recruiting citizens already out in the field opens a tremendous amount of new data. For example, thousands of farmers reporting the changes in biodiversity in their farms over many years has provided a large amount of relevant data concerning the effect of different farming methods on biodiversity. Another example is WomSAT, a citizen science project that collects data on wombat roadkill and sarcoptic mange incidence and distribution, to support conservation efforts for the species.
Citizen science can be used to great effect in addition to the usual scientific methods in biodiversity monitoring. The typical active method of species detection is able to collect data on the broad biodiversity of areas while citizen science approaches has shown to be more effective at identifying invasive species. In combination, this provides an effective strategy of monitoring the changes in biodiversity of ecosystems.
=== Health and welfare ===
In the research fields of health and welfare, citizen science is often discussed in other terms, such as "public involvement", "user engagement", or "community member involvement". However the meaning is similar to citizen science, with the exception that citizens are not often involved in collecting data but more often involved in prioritisation of research ideas and improving methodology, e.g. survey questions. In the last decades, researchers and funders have gained awareness of the benefits from involving citizens in the research work, but the involvement of citizens in a meaningful way is not a common practice. There is an ongoing discussion on how to evaluate citizen science in health and welfare research.
One aspect to consider in citizen science in health and welfare, that stands out compared to in other academic fields, is who to involve. When research concerns human experiences, representation of a group becomes important. While it is commonly acknowledged that the people involved need to have lived experience of the concerned topic, representation is still an issue, and researchers are debating whether this is a useful concept in citizen science.
Outside of the older patient and public involvement tradition, there are also efforts to bring the newer citizen science efforts to health and biomedical research. These efforts cover a broad spectrum of involvement and co-leadership of patients, including patient-led research, quantified self or personal science, as well as collaborative research efforts between researchers and patient-groups, often enabled by digital technology. A survey among European practitioners involved in health-related citizen science found that ethical challenges and achieving a balanced return on investment for patients and medical staff are common challenges.
== Modern technology ==
Newer technologies have increased the options for citizen science. Citizen scientists can build and operate their own instruments to gather data for their own experiments or as part of a larger project. Examples include amateur radio, amateur astronomy, Six Sigma Projects, and Maker activities. Scientist Joshua Pearce has advocated for the creation of open-source hardware based scientific equipment that both citizen scientists and professional scientists, which can be replicated by digital manufacturing techniques such as 3D printing. Multiple studies have shown this approach radically reduces scientific equipment costs. Examples of this approach include water testing, nitrate and other environmental testing, basic biology and optics. Groups such as Public Lab, which is a community where citizen scientists can learn how to investigate environmental concerns using inexpensive DIY techniques, embody this approach.

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Video technology is much used in scientific research. The Citizen Science Center in the Nature Research Center wing of the North Carolina Museum of Natural Sciences has exhibits on how to get involved in scientific research and become a citizen scientist. For example, visitors can observe birdfeeders at the Prairie Ridge Ecostation satellite facility via live video feed and record which species they see.
Since 2005, the Genographic Project has used the latest genetic technology to expand our knowledge of the human story, and its pioneering use of DNA testing to engage and involve the public in the research effort has helped to create a new breed of "citizen scientist". Geno 2.0 expands the scope for citizen science, harnessing the power of the crowd to discover new details of human population history. This includes supporting, organization and dissemination of personal DNA testing. Like amateur astronomy, citizen scientists encouraged by volunteer organizations like the International Society of Genetic Genealogy have provided valuable information and research to the professional scientific community.
With unmanned aerial vehicles, further citizen science is enabled. One example is the ESA's AstroDrone smartphone app for gathering robotic data with the Parrot AR.Drone.
Citizens in Space (CIS), a project of the United States Rocket Academy, seeks to combine citizen science with citizen space exploration. CIS is training citizen astronauts to fly as payload operators on suborbital reusable spacecraft that are now in development. CIS will also be developing, and encouraging others to develop, citizen-science payloads to fly on suborbital vehicles. CIS has already acquired a contract for 10 flights on the Lynx suborbital vehicle, being developed by XCOR Aerospace, and plans to acquire additional flights on XCOR Lynx and other suborbital vehicles in the future.
CIS believes that "The development of low-cost reusable suborbital spacecraft will be the next great enabler, allowing citizens to participate in space exploration and space science."
The website CitizenScience.gov was started by the U.S. government to "accelerate the use of crowdsourcing and citizen science" in the United States. Following the internet's rapid increase of citizen science projects, this site is one of the most prominent resource banks for citizen scientists and government supporters alike. It features three sections: a catalog of existing citizen science projects which are federally supported, a toolkit to help federal officials as they develop and maintain their future projects, and several other resources and projects. This was created as the result of a mandate within the Crowdsourcing and Citizen Science Act of 2016 (15 USC 3724).
=== Internet ===
The Internet has been a boon to citizen science, particularly through gamification. One of the first Internet-based citizen science experiments was NASA's Clickworkers, which enabled the general public to assist in the classification of images, greatly reducing the time to analyze large data sets. Another was the Citizen Science Toolbox, launched in 2003, of the Australian Coastal Collaborative Research Centre. Mozak is a game in which players create 3D reconstructions from images of actual human and mouse neurons, helping to advance understanding of the brain. One of the largest citizen science games is Eyewire, a brain-mapping puzzle game developed at the Massachusetts Institute of Technology that now has over 200,000 players. Another example is Quantum Moves, a game developed by the Center for Driven Community Research at Aarhus University, which uses online community efforts to solve quantum physics problems. The solutions found by players can then be used in the lab to feed computational algorithms used in building a scalable quantum computer.
More generally, Amazon's Mechanical Turk is frequently used in the creation, collection, and processing of data by paid citizens. There is controversy as to whether or not the data collected through such services is reliable, as it is subject to participants' desire for compensation. However, use of Mechanical Turk tends to quickly produce more diverse participant backgrounds, as well as comparably accurate data when compared to traditional collection methods.
The internet has also enabled citizen scientists to gather data to be analyzed by professional researchers. Citizen science networks are often involved in the observation of cyclic events of nature (phenology), such as effects of global warming on plant and animal life in different geographic areas, and in monitoring programs for natural-resource management. On BugGuide.Net, an online community of naturalists who share observations of arthropod, amateurs and professional researchers contribute to the analysis. By October 2022, BugGuide has over 1,886,513 images submitted by 47,732 contributors.

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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 claimed contributions are automatically passed back to Crossref, ensuring proper attribution and maintaining comprehensive records of scholarly contributions across the research ecosystem.
== Organizational structure ==
CASRAI operates under the governance of The Health Initiative, a 501(c)(3) organization that provides strategic oversight and administrative support. The organization maintains dual operational headquarters through Hospital.org.uk for administrative functions and Pango.Network for technical infrastructure. This structure enables CASRAI to leverage both healthcare sector expertise and advanced technical capabilities in serving the global research community.
The organization receives partial sponsorship from the University of Oxford and University of Edinburgh, which support its mission to advance research administration standards and contribute technical expertise to its various initiatives. This academic partnership ensures that CASRAI's standards remain aligned with the needs of research institutions while maintaining independence in its operations.
== Major initiatives ==
=== Contributor Roles Taxonomy (CRediT) ===
CASRAI develops and maintains the Contributor Roles Taxonomy (CRediT), which has become an ANSI/NISO standard. CRediT provides a standardized method for recognizing diverse contributions to scholarly published work, defining 14 distinct roles including conceptualization, methodology, and data curation.
CASRAI has developed and provides a free Open Journal Systems (OJS) plugin that integrates the CRediT taxonomy into the journal submission process. This plugin features an artificial intelligence server that is freely available to institutions, enabling automated Credit taxonomy metadata assignment directly within OJS PKP article submissions. The system modifies the journal submission process by automating contributor role assignments, standardizing metadata management, and streamlining workflows. It ensures compliance with CRediT standards, supports XML and PDF output formats, and integrates seamlessly with existing journal workflows.
The AI-powered plugin represents a significant advancement in making contribution data easily accessible for future research, automating the process of identifying and categorizing contributor roles while ensuring that metadata is properly structured and preserved. This initiative aligns with CASRAI's mission to reduce administrative burden while improving the quality and accessibility of research contribution data.
=== Digital infrastructure and services ===
CASRAI maintains a comprehensive digital infrastructure that supports the global research community. The organization's dictionary service (dictionary.casrai.org) provides standardized definitions and terminologies for research administration, serving as a central reference point for institutions implementing CASRAI standards. This online dictionary facilitates consistent communication across different research management systems and ensures interoperability between diverse institutional frameworks.
The organization's infrastructure includes advanced DOI management capabilities, hosting over 200 million DOIs as of 2025. This system enables seamless integration with Crossref and other scholarly communication platforms, ensuring that research outputs are properly identified, tracked, and attributed throughout their lifecycle.
=== Standards development ===
CASRAI works with the National Information Standards Organization (NISO) to develop and maintain standards for research administration. The collaboration focuses on aligning with international standards, supporting the development of research information frameworks, integrating with research management systems, and ensuring interoperability with global research infrastructure.
== Training ==
CASRAI organizes workshops, webinars, and training sessions to support the adoption of its standards. These educational programs focus on the best practices in research administration and data management for institutions.
== Geographic implementation ==
CASRAI standards are actively used in Canada, the European Union, and the United States. The organization's reach extends globally through its digital infrastructure, with institutions from multiple continents accessing its dictionary services and implementing its standards.
== Impact and reach ==
CASRAI's impact on the global research ecosystem is substantial, with the organization hosting over 200 million DOIs as of 2025, representing a significant portion of the world's scholarly output. The free availability of its OJS plugin with AI-powered metadata assignment capabilities has democratized access to advanced research administration tools, particularly benefiting smaller institutions and those in developing countries that may lack resources for proprietary solutions.
The integration with Crossref ensures that contribution data flows seamlessly through the scholarly communication ecosystem, improving the accuracy of research metrics and enabling more nuanced understanding of collaborative research efforts. This infrastructure supports the broader movement toward open science and transparent research practices by making contribution data more accessible and standardized.
== See also ==
Contributor Roles Taxonomy
Digital Object Identifier
Crossref
Open Journal Systems
ORCID
Research data management
== References ==
== External links ==
Official website
CRediT taxonomy information
CASRAI Dictionary

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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, and formerly by Unsplash, Pixabay, and Socratic.
== History ==
The organization was founded in 2001 by Lawrence Lessig, Hal Abelson, and Eric Eldred, with the support of Center for the Public Domain. The first article in a general interest publication about Creative Commons, written by Hal Plotkin, was published in February 2002. The first set of copyright licenses was released in December 2002 (original press release was dated 16th December, 2022). The founding management team that developed the licenses and built the Creative Commons infrastructure as it is known today included Molly Shaffer Van Houweling, Glenn Otis Brown, Neeru Paharia, and Ben Adida.
In 2002, Creative Commons was selected as the successor of the Open Content Project, a 1998 precursor project by David A. Wiley. Wiley subsequently joined Creative Commons as its director. The licenses published by the Open Content Project, the Open Content License and Open Publication License, were soon deprecated in favour of Creative Commons licenses. Aaron Swartz played a role in the early stages of Creative Commons, as did Matthew Haughey.
== Purpose and goal ==
Creative Commons has been an early participant in the copyleft movement, which seeks to provide alternative solutions to copyright, and has been dubbed "some rights reserved". Creative Commons has been credited with contributing to a re-thinking of the role of the "commons" in the Information Age. Their frameworks help individuals and groups distribute content more freely while still protecting themselves and their intellectual property rights legally.
According to its founder Lawrence Lessig, Creative Commons' goal is to counter the dominant and increasingly restrictive permission culture that limits artistic creation to existing or powerful creators. Lessig maintains that modern culture is dominated by traditional content distributors in order to maintain and strengthen their monopolies on cultural products such as popular music and popular cinema, and that Creative Commons can provide alternatives to these restrictions. In mid‑December 2020, Creative Commons released its strategy for the upcoming five years, which will focus more on three core of goals including advocacy, infrastructure innovation, and capacity building.
== Creative Commons network ==
Until April 2018, Creative Commons had over 100 affiliates working in over 75 jurisdictions to support and promote CC activities around the world. In 2018 this affiliate network has been restructured into a network organisation. The network no longer relies on affiliate organisation but on individual membership organised in Chapter.
=== Hungary ===
Creative Commons Hungary was the affiliated network of Creative Commons in Hungary. The non-profit organization was founded in Budapest, Hungary, in 2008 and was deleted from the official registry on February 6, 2017.
=== Japan ===
Creative Commons Japan (CC Japan/CCJP) is the affiliated network of Creative Commons in Japan. In 2003, the International University GLOCOM held a meeting for the CC Japan preparation. In March 2004, CC Japan was launched by GLOCOM University. CC Japan is the world's second CC affiliated network (the first is in America). In March 2006, CC Japan become the NPO and be in motion. In the same month, the CC founder Lawrence Lessig came to Japan to be one of the main holders of the open ceremony.
Within the same year, between May and June, different international events were held in Japan, including iSummit 06 and the first through third rounds of CCJP.
In February 2007, the ICC x ClipLife 15 second CM competition was held. In June, iSummit 07 was held. In July, the fourth CCJP was held. On July 25, Tokyo approved Nobuhiro Nakayama (中山信弘) to become the NGO chairman of CCJP. In 2008, Taipie ACIA joined CCJP. The main theme music which was chosen by CCJP was announced. In 2009, INTO INFINITY shown in Tokyo and Sapporo. iPhone held the shows with Audio Visual Mixer for INTO INFINITY. (Apple joint research and development with CCJP) In 2012, the 10th anniversary ceremony was held in Japan. In 2015, Creative Commons 4.0 and Creative Commons 0 were released in Japanese language.
=== South Korea ===
Creative Commons Korea (CC Korea) is the affiliated network of Creative Commons in South Korea. In March 2005, CC Korea was initiated by Jongsoo Yoon (in Korean: 윤종수), former Presiding Judge of Incheon District Court, as a project of Korea Association for Infomedia Law (KAFIL). The major Korean portal sites, including Daum and Naver, have been participating in the use of Creative Commons licences. In January 2009, the Creative Commons Korea Association was consequently founded as a non-profit incorporated association. Since then, CC Korea has been actively promoting the liberal and open culture of creation as well as leading the diffusion of Creative Common in the country.
Creative Commons Korea
Creative Commons Asia Conference 2010

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=== 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 Commons founder Lawrence Lessig countered that copyright laws have not always offered the strong and seemingly indefinite protection that today's law provides. Rather, the duration of copyright used to be limited to much shorter terms of years, and some works never gained protection because they did not follow the now-abandoned compulsory format. The maintainers of Debian, a Linux distribution known for its strict adherence to a particular definition of software freedom, rejected the Creative Commons Attribution License prior to version 3 as incompatible with the Debian Free Software Guidelines (DFSG) due to the license's anti-DRM provisions (which might, due to ambiguity, be covering more than DRM) and its requirement that downstream users remove an author's credit upon request from the author. Version 3.0 of the Creative Commons licenses addressed these concerns and, except for the non commercial and no-derivative variants, are considered to be compatible with the DFSG.
Kent Anderson, writing for The Scholarly Kitchen, a blog of the Society for Scholarly Publishing, criticized CC as being grounded on copyright principles and not really departing from it, and as being more complex and complicating than the latter – thus the public does not scrutinize CC, reflexively accepting it as one would a software license – while at the same time weakening the rights provided by copyright. Anderson ends up concluding that this is the point, and that "Creative Commons receives significant funding from large information companies like Google, Nature Publishing Group, and RedHat", and that Google money is especially linked to CC's history; for him, CC is "an organization designed to promulgate the interests of technology companies and Silicon Valley generally".
=== CC license proliferation ===
According to Mako Hill, Creative Commons has established a range of licenses tailored to meet the different protection interests of authors of creative works, rather than forcing a single forced standard as a "base level of freedom" that all Creative Commons licenses must meet, and with which all licensors and users must comply. "By failing to take any firm ethical position and draw any line in the sand, CC is a missed opportunity. ...CC has replaced what could have been a call for a world where 'essential rights are unreservable' with the relatively hollow call for 'some rights reserved.'" He also argued that Creative Commons enables license proliferation, by providing multiple licenses that are incompatible.
The Creative Commons website states, "Since each of the six CC licenses functions differently, resources placed under different licenses may not necessarily be combined with one another without violating the license terms." Works licensed under incompatible licenses may not be recombined in a derivative work without obtaining permission from the copyright owner. Richard Stallman of the Free Software Foundation stated in 2005 that he could not support Creative Commons as an activity because "it adopted some additional licenses which do not give everyone that minimum freedom", that freedom being "the freedom to share, noncommercially, any published work". Those licenses have since been retired by Creative Commons.
=== License uses ===
Creative Commons is only a service provider for standardized license text, not a party in any agreement. No central database of Creative Commons works is controlling all licensed works and the responsibility of the Creative Commons system rests entirely with those using the licences. This situation is, however, not specific to Creative Commons. All copyright owners must individually defend their rights and no central database of copyrighted works or existing license agreements exists. The United States Copyright Office does keep a database of all works registered with it, but absence of registration does not imply absence of copyright, and CC licensed works can be registered on the same terms as unlicensed works or works licensed under any other licences.
Although Creative Commons offers multiple licenses for different uses, some critics suggested that the licenses still do not address the differences among the media or among the various concerns that different authors have. Lessig wrote that the point of Creative Commons is to provide a middle ground between two extreme views of copyright protection – one demanding that all rights be controlled, and the other arguing that none should be controlled. Creative Commons provides a third option that allows authors to pick and choose which rights they want to control and which they want to grant to others. The multitude of licenses reflects the multitude of rights that can be passed on to subsequent creators.
=== Non-commercial use licenses ===

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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 depicted 15-year-old Alison Chang posing for a photo at her church's fund-raising carwash, with the superimposed, mocking slogan "Dump Your Pen Friend". Chang sued Virgin Mobile and Creative Commons. The photo was taken by Chang's church youth counsellor, Justin Ho-Wee Wong, who uploaded the image to Flickr under the Creative Commons license.
The case hinges on privacy, the right of people not to have their likeness used in an ad without permission. So, while Mr. Wong may have given away his rights as a photographer, he did not, and could not, give away Alison's rights. In the lawsuit, which Mr. Wong is also a party to, there is an argument that Virgin did not honor all the terms of the nonrestrictive license.
On November 27, 2007, Chang voluntarily dismissed the lawsuit against Creative Commons, focusing the lawsuit only against Virgin Mobile. The case was dismissed due to lack of jurisdiction and subsequently Virgin Mobile did not incur any damages towards the plaintiff.
== See also ==
Copyleft
Free content
Free-culture movement
List of major Creative Commons licensed works
Open-source license
Public-domain-equivalent license
== References ==
== Bibliography ==
== External links ==
Creative Commons
Creative Commons wiki
Short Flash animation describing Creative Commons
Creative Commonsː Copyright Week: What happened to the Brazilian Copyright Reform? (English)
Creative Commonsː Copyright Reform (English)
"Creative Commons". Internal Revenue Service filings. ProPublica Nonprofit Explorer.

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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 it had licensed a total of 21 dictionaries, in all 21 Indigenous languages that are spoken in the province, under CC BY (Creative Commons Attribution) 4.0 license. This meant that these works would be opened for "adaptation, distribution, and remixing by anyone".
Pratham Books, a nonprofit publisher with social goals, working since 1994 to secure primary education for every child in India and seeking to publish high-quality books for children at an affordable cost, has been releasing its books under Creative Commons licenses.
NROER, or the National Repository of Open Educational Resources, an initiative in Open Education efforts, (under the Creative Commons) which is intended to help "reach the unreached and empower all by providing resources in multiple languages and formats. As of April 2020, the NROER had some 14,527 files in different languages, comprising 401 collections, 2779 documents, 1345 interactive content pieces, 1,664 audio files, 2,586 images and 6,153 videos.
NCERT has taken the initiative of declaring that NROER will carry CC-BY-SA license, which can also be reused for commercial purposes.
== Issues raised ==
Among the issues raised by the Creative Commons (India Chapter), related groups and allies, have been
Wikimedia India Chapter raising the issue of there not enough information out in the public domain.
Appeal to remove copyright on Census of India.
Urging the Press Information Bureau to issue under Creative Commons licenses information available with it about Indian history and current issues.
Calling on the Indian Space Research Organisation to release its copyrighted information under Creative Commons licenses, as done by NASA in the United States.
Journals, text and multimedia produced by government departments like Prasar Bharti and AIR can be released under an appropriate Creative Commons license.
Access to learning materials is seen as a big issue in India.
== References ==
== External links ==
CC-India Chapter mailing list
CC India on CC.org site
IQAC Webinar on Web Content Licensing
The Relaunch of Creative Commons India

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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 to analyze and advance a public objective. Through these data transfers and data fellowships, access to and terms for use of data are highly controlled.
Prizes and Challenges: Organizations make data available to qualified applicants through competition for innovative use or platform design to add value to the firm. Open innovation competitions, like LinkedIn's Economic Graph Challenge, allow for open and broader use of data by many independent users, while selective innovation challenges give limited data access, narrowing the scope of its application to a specific situation. Oftentimes, competition members are bound to data responsibility guidelines.
Intelligence Generation: Companies use data to build shareable tools and release them for public use. Although no formal, direct cross-sector sharing occurs, it lays the foundation for knowledge transfer and a culture of open, data-driven analysis.
== Reasons for data collaboratives ==
The big data boom has demonstrated the power of data to inform and design public projects in an accountable and iterative manner. However, unequal access to certain data across sectors limits the ability of groups to find, access, or be made aware of valuable information, hindering social innovation. Data collaboratives create networks that bridge access and knowledge gaps by bringing different sectors together to share data to address social challenges.
The GovLab argues data collaboratives wherein a private sector data holder shares data with other groups tend to be motivated by a desire for:
Reciprocity: Sharing data with others can guide mutually beneficial business decisions.
Research and Insights: Sharing data can spark new and innovative approaches to issues.
Reputation and Public Relations: Sharing data, especially to advance public issues, can bolster the image and reputability of a firm, attracting new socially-conscious clients, talent, and followers.
Revenue Generation: Corporate data can be sold to data collaboratives, generating novel revenue streams.
Regulatory Compliance: Data collaboratives can help corporations advance transparency and trust by establishing and following data sharing protocols.
Responsibility and Corporate Philanthropy: Data collaboratives allow businesses to drive meaningful corporate social responsibility programs.
Data collaboratives can help respond to service delivery and emergency preparedness and disaster response problems. Robert Kirkpatrick, Director of UN Global Pulse noted that "the lack of innovation [in these sectors have] resulted in a failure to protect the public from what turns out to be preventable harms."
== Incentives for private sector participation ==
According to The GovLab, data collaboratives can provide five main benefits for public problems:
Situational awareness and response: recent, robust, and quality data from private or public sectors can help governments and civil society better mobilize in crisis and emergency situations. For instance, the Mobile Data, Environmental Extremes, and Population Project (MDEEP) is a collaboration between international organizations and telecommunications companies in Bangladesh to build "large-scale population displacement models to understand population movement related to natural disasters."
Public service design and delivery: Access to previously inaccessible datasets can enable more accurate modelling of public service design and guide service delivery in a targeted, evidence-based manner. For example, collaborative use of datasets by governments, international organizations, aid groups, and private telecommunications carriers during the 2014 Ebola outbreak helped track and trace the virus.
Knowledge creation and transfer: Utilizing a larger number of and more diverse datasets can fill knowledge gaps to better respond to the problem at hand. The All of Us Research Program, created by the Obama administration in 2015, allows participants to share their health data to a secure system, which is then aggregated and anonymized for researchers to study and advance medical science.
Prediction and forecasting: Data from the past allows for informed prediction in the future, allowing groups to identify problems and respond more quickly. Leveraging search engine query data, researchers identified search terms, times, demographics that correlated with suicidal ideation across Indian youth.
Impact assessment and evaluation: Access to additional datasets can help organizations monitor and evaluate the effectiveness of policies and iteratively adapt programs for better service delivery. For example, the US Food and Drug Administration's Sentinel Initiative used anonymized patient information sourced through the TriNetX Live USA Network to assess how many adults hospitalized for COVID-19 experienced or succumbed to thrombosis-related complications.
== Examples ==
From 2017 to 2019, the percentage of companies entering data-related partnerships rose from 21% to 40%. A growing share of business competitors are also deciding to connect their data—jumping from 7% to 17%. In a 2019 report, the World Economic Forum and McKinsey estimated that connecting data across institutional and geographic boundaries could create roughly $3 trillion annually in economic value by 2020.
The following is an illustrative (but not exhaustive) list of some data collaboratives:

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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 levels alongside country-owned strategies and plans for collecting, storing, analyzing, and using data to improve health outcomes, with specific focus on UN SDG targets and communities that are left behind.
International Network for Data on Impact and Government Outcomes (INDIGO): An initiative of the Government Outcomes Lab (GO Lab) at the Blavatnik School of Government at the University of Oxford that builds an interdisciplinary network of data stewards to address social problems collaboratively.
InfoSum: A UK based company that enables a decentralized and trusted data ecosystem to enable companies to do more with customer data without actually sharing the data.
The Mobility Data Collaborative: A partnership among mobility operators, data aggregators, public agencies, academia and others to provide solutions and common framework to ensure safe, equitable and livable streets for all.
Water Data Collaborative: Works towards their mission to grow and maintain an inclusive community of water scientist data generators to provide data that enable the protection and restoration of our nation's waterways.
== Risks, challenges, and ethical considerations ==
Data collaboratives have significant challenges related to data security, data privacy, commercial risk, reputational concerns and regulatory uncertainty. In addition, there exist concerns about the lack of trust among individuals, institutions and governments.
=== Risks ===
Commercial Risks: "Corporations are concerned about brand reputation, data rights and the disclosure of proprietary or commercially sensitive information."
Security Risks: Vulnerable data structures, lacking security expertise and processes can put all members of a data collaborative at risk.
Regulatory Risks: Fragmented legal and regulatory frameworks hinder data sharing across sectors and sovereign borders. Varying definitions of privacy and data holder rights exposes data holders to significant compliance risks and liabilities.
Privacy and Ethical Risks: Collaborative data use can expose individual identities, infringing on privacy and security. Additionally, protecting vulnerable populations from discrimination and human rights violations through the sharing of non-personal but demographically identifiable data is often a major issue.
=== Mitigating privacy protection issues ===
Privacy preserving computation (PPC) presents data in forms that can be shared, analyzed, and operated on by multiple stakeholders without the raw information. To do so, PPC seeks to control the environment within which the data is operated on (Trusted Execution Environment) and strips the data of identifying traits (Differential Privacy). Protecting the data via Homomorphic Encryption techniques, PPC allows users to execute operations and see their outcomes without exposing the source data. Through secure Multi-Party Computation, different groups can combine data to work in a decentralized and collaborative manner.
PPC techniques are already being leveraged by governments and large corporations. In 2015, the Estonian government worked with the private firm, Sharemind, to analyze tax and education records through Multi-Party Computation for the Private Statistics Project. An external audit by the European Commission PRACTICE project found that the Private Statistics Project did not expose any personal data.
In 2019, Google released its Private Join and Compute protocol to open-source, allowing users to use Homomorphic Encryption and Multi-Party Computation. In the same year, ten pharmaceutical companies formed the Melloddy consortium to use blockchain technology to train a drug discovery algorithm via shared data.
=== Mitigating power asymmetries ===
Power imbalances can occur when stronger parties manipulate, exclude, or pressure weaker members of the data collaborative. From a classical viewpoint, power refers to the influence a person or group has over another. Examining collaborative governance, Dave Egan, Evan E. Hjerpe, and Jesse Abrams suggest a three-phased approach to power: power over refers to the ability to control the behavior of others, power for looks at the ability to authorize the participation of stakeholders, and power to considers the ability to measure another entity's ability to realize its goals.
Power imbalances can arise from disparities in authority, resources, legitimacy or trust between parties. The more actors in the data collaborative or more incentives of data use, the increased likelihood for conflicting interests. Oftentimes, data is viewed as an organizational asset, and opening it up to new uses by others means relinquishing control over the data and ceding this autonomy to the collaborative, resulting in the "control and generativity challenge." Data stewards can help reduce the power imbalances by reducing bias influences, follow operating procedures, and provide issue resolution and remediation.
== See also ==
Big Data
Data sharing
Open collaboration
Dispersed knowledge
Digital collaboration
Mass collaboration
Open innovation
== References ==
== External links ==

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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 data paper about the dataset, which may be published as a preprint, in a regular journal, or in a data journal that is dedicated to supporting data papers. The data may be hosted by the journal or hosted separately in a data repository.
Publishing data allows researchers to both make their data available to others to use, and enables datasets to be cited similarly to other research publication types (such as articles or books), thereby enabling producers of datasets to gain academic credit for their work.
The motivations for publishing data may range for a desire to make research more accessible, to enable citability of datasets, or research funder or publisher mandates that require open data publishing. The UK Data Service is one key organisation working with others to raise the importance of citing data correctly and helping researchers to do so.
Solutions to preserve privacy within data publishing has been proposed, including privacy protection algorithms, data ”masking” methods, and regional privacy level calculation algorithm.
== Methods for publishing data ==
=== Data files as supplementary material ===
A large number of journals and publishers support supplementary material being attached to research articles, including datasets. Though historically such material might have been distributed only by request or on microform to libraries, journals today typically host such material online. Supplementary material is available to subscribers to the journal or, if the article or journal is open access, to everyone.
=== Data repositories ===
There are a large number of data repositories, on both general and specialized topics. Many repositories are disciplinary repositories, focused on a particular research discipline such as the UK Data Service which is a trusted digital repository of social, economic and humanities data. Repositories may be free for researchers to upload their data or may charge a one-time or ongoing fee for hosting the data. These repositories offer a publicly accessible web interface for searching and browsing hosted datasets, and may include additional features such as a digital object identifier, for permanent citation of the data, and linking to associated published papers and code.
Related to this, there are also data publishing services e.g. Open Context, a service for archaeology. Such services enable search, query, analysis and citation of each individual record of data. The granularity and integration allows for publication and public exhibition of data dynamically on the Web.
=== Data papers ===
Data papers or data articles are “scholarly publication of a searchable metadata document describing a particular on-line accessible dataset, or a group of datasets, published in accordance to the standard academic practices”. Their final aim is to provide “information on the what, where, why, how and who of the data”. The intent of a data paper is to offer descriptive information on the related dataset(s) focusing on data collection, distinguishing features, access and potential reuse rather than on data processing and analysis. Because data papers are considered academic publications no different than other types of papers, they allow scientists sharing data to receive credit in currency recognizable within the academic system, thus "making data sharing count". This provides not only an additional incentive to share data, but also through the peer review process, increases the quality of metadata and thus reusability of the shared data.
Thus data papers represent the scholarly communication approach to data sharing. Despite their potentiality, data papers are not the ultimate and complete solution for all the data sharing and reuse issues and, in some cases, they are considered to induce false expectations in the research community.
=== Data journals ===
Data papers are supported by a rich array of data journals, some of which are "pure", i.e. they are dedicated to publish data papers only, while others – the majority – are "mixed", i.e. they publish a number of articles types including data papers.
A comprehensive survey on data journals is available. A non-exhaustive list of data journals has been compiled by staff at the University of Edinburgh.
Examples of "pure" data journals are: Earth System Science Data, Journal of Open Archaeology Data, Open Health Data, Polar Data Journal, and Scientific Data.
Examples of "mixed" journals publishing data papers are: Biodiversity Data Journal, F1000Research, GigaScience, GigaByte, PLOS ONE, and SpringerPlus.
=== Data citation ===
Data citation is the provision of accurate, consistent and standardised referencing for datasets just as bibliographic citations are provided for other published sources like research articles or monographs. Typically the well established Digital Object Identifier (DOI) approach is used with DOIs taking users to a website that contains the metadata on the dataset and the dataset itself.
==== History of development ====
A 2011 paper reported an inability to determine how often data citation happened in social sciences.
2012-13 papers reported that data citation was becoming more common but the practice for it was not standard.
In 2014 FORCE 11 published the Joint Declaration of Data Citation Principles covering the purpose, function and attributes of data citation.
In October 2018 CrossRef expressed its support for cataloging datasets and recommending their citation.
A popular data-oriented journal reported in April 2019 that it would now use data citations.
A June 2019 paper suggested that increased data citation will make the practice more valuable for everyone by encouraging data sharing and also by increasing the prestige of people who share.
Data citation is an emerging topic in computer science and it has been defined as a computational problem. Indeed, citing data poses significant challenges to computer scientists and the main problems to address are related to:
the use of heterogeneous data models and formats – e.g., relational databases, Comma-Separated Values (CSV), Extensible Markup Language (XML), Resource Description Framework (RDF);
the transience of data;
the necessity to cite data at different levels of coarseness – i.e., deep citations;
the necessity to automatically generate citations to data with variable granularity.
== See also ==
Data archiving
Disciplinary repository
Open science data
Registry of Research Data Repositories
== References ==

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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 their expenditures such that they could consistently generate gross margins on revenue of over 33%.
=== Resignations of editorial boards ===
In 2006, the nine editorial board members of Oxford University's Elsevier-published mathematics journal Topology resigned because they agreed among themselves that Elsevier's publishing policies had "a significant and damaging effect on Topology's reputation in the mathematical research community." An Elsevier spokesperson disputed this, saying that "this still constitutes a pretty rare occurrence" and that the journal "is actually available today to more people than ever before". Journalists recognize this event as part of the precedent to The Cost of Knowledge campaign. In 2008, the Journal of Topology started independently of Elsevier, and Topology ended publication in 2009.
Similarly, in 2015 the entire editorial board of the Elsevier journal Lingua resigned and founded a new, open access journal called Glossa. Lingua continued to exist, albeit with a lower impact and much changed reputation.
== Website ==
A website called "The Cost of Knowledge" appeared, inviting researchers and scholars to declare their commitment to not submit papers to Elsevier journals, not referee articles for Elsevier's journals, and not participate in the editorial boards.
== Signatories ==
On 8 February 2012, 34 prominent mathematicians who had signed The Cost of Knowledge released a joint statement of purpose explaining their reasons for supporting the protest. In addition to Timothy Gowers, Ingrid Daubechies, Juan J. Manfredi,
Terence Tao, Wendelin Werner,
Scott Aaronson, László Lovász, and John Baez are among the signatories. Many signatories are researchers in the fields of mathematics, computer science, and biology.
On 1 February 2012, the declaration had a thousand signatories. By November 2018, over 17000 researchers had signed the petition. The success of the petition has been debated.
== Reaction from Elsevier ==
On 27 February 2012, Elsevier issued a statement on its website that declared that it has withdrawn support from the Research Works Act. Although the Cost of Knowledge movement was not mentioned, the statement indicated the hope that the move would "help create a less heated and more productive climate" for ongoing discussions with research funders. Hours after Elsevier's statement, Representatives Darrell Issa and Carolyn Maloney, who were sponsors of the bill, issued a joint statement saying that they would not push the bill in Congress. Earlier, Mike Taylor of the University of Bristol accused Issa and Maloney of being motivated by large donations that they received from Elsevier in 2011.
While participants in the boycott celebrated the dropping of support for the Research Works Act, Elsevier denied that their action was a result of the boycott and stated that they took this action at the request of those researchers who did not participate in the boycott.
On the same day, Elsevier released an open letter to the mathematics community, stating that its target is to reduce its prices to $11/article or less. Elsevier also opened the archives of 14 mathematics journals back to 1995 with a four-year moving wall. In late 2012, Elsevier made all of its "primary mathematics" journals open access up to 2008.
The boycott remains in effect.
=== Change from status quo ===
On 21 January 2012, the mathematician Timothy Gowers called for a boycott of Elsevier with a post on his personal blog. This blog post attracted enough attention that other media sources commented on it as being part of the start of a movement. The three reasons he cited for the boycott are high subscription prices for individual journals, bundling subscriptions to journals of different value and importance, and Elsevier's support for SOPA, the PROTECT IP Act, and the Research Works Act. The "Statement of Purpose" on the Cost of Knowledge website explains that Elsevier was chosen as an initial focus for discontent due to a "widespread feeling among mathematicians that they are the worst offender." The statement further mentions "scandals, lawsuits, lobbying, etc." as reasons for focusing on Elsevier.
Elsevier disputed the claims, arguing that their prices are below the industry average, and stating that bundling is only one of several different options available to buy access to Elsevier journals. The company also claimed that its considerable profit margins are "simply a consequence of the firm's efficient operation". Critics of Elsevier claim that in 2010, 36% of Elsevier's reported revenues of US$3.2 billion was profit. Elsevier claimed to have an operating margin of 25.7% in 2010.

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=== 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. It concludes "Few researchers have signed the petition in recent years, thus giving the impression the boycott has run its course." As of August 2025, there were 20,908 signatories.
Protests against high fees have rolled through into many institutional actions. As an example, in 2019, the University of California (UC) system announced that it was cancelling its Elsevier subscriptions, citing costs and lack of open access. Similar steps were taken by other universities, including MIT in 2020, SUNY in 2020, Florida State University in 2018, UNC Chapel Hill in 2020, and Louisiana State University in 2019. In 2021, the UC system negotiated a new 4-year "pilot" agreement with Elsevier that permits UC researchers to publish in Elsevier journals on an open-access basis and restores access to Elsevier journals for UC libraries, following similar open-access agreements with Carnegie Mellon University in 2019 (for 4 years) and the Norwegian university system in 2019 (for 2 years).
== See also ==
Serials crisis
== References ==
== External links ==
Official website
Gowers, Timothy (21 January 2012). "Elsevier – my part in its downfall". Gowers's Weblog. WordPress.com. – The blog post associated with the start of the campaign
Elsevier's open letter response
collection of media coverage of The Cost of Knowledge