# kb

id: perl-data-language-20260505-0
file: data/en.wikipedia.org/wiki/Perl_Data_Language-0.md
category: reference
title: Perl Data Language
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Perl_Data_Language
date_saved: 2026-05-05T10:13:06.697937+00:00
instance: kb-cron
parent: perl-data-language-20260505-0
summary:
Perl Data Language (abbreviated PDL) is a set of free software array programming extensions to the Perl programming language. PDL extends the data structures built into Perl, to include large multidimensional arrays, and adds functionality to manipulate those arrays as vector objects. It also provides tools for image processing, machine learning, computer modeling of physical systems, and graphical plotting and presentation. Simple operations are automatically vectorized across complete arrays, and higher-dimensional operations (such as matrix multiplication) are supported. == Language design == PDL is a vectorized array programming language: the expression syntax is a variation on standard mathematical vector notation, so that the user can combine and operate on large arrays with simple expressions. In this respect, PDL follows in the footsteps of the APL programming language, and it has been compared to commercial languages such as MATLAB and Interactive Data Language, and to other free languages such as NumPy and Octave. Unlike MATLAB and IDL, PDL allows great flexibility in indexing and vectorization: for example, if a subroutine normally operates on a 2-D matrix array, passing it a 3-D data cube will generally cause the same operation to happen to each 2-D layer of the cube. PDL borrows from


id: physics-analysis-workstation-20260505-0
file: data/en.wikipedia.org/wiki/Physics_Analysis_Workstation-0.md
category: reference
title: Physics Analysis Workstation
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Physics_Analysis_Workstation
date_saved: 2026-05-05T10:13:07.854449+00:00
instance: kb-cron
parent: physics-analysis-workstation-20260505-0
summary:
The Physics Analysis Workstation (PAW) is an interactive, scriptable computer software tool for data analysis and graphical presentation in high-energy physics. The development of this software tool started at CERN in 1986, it was optimized for the processing of very large amounts of data. It was based on and intended for inter-operation with components of CERNLIB, an extensive collection of Fortran libraries. PAW had been a standard tool in high energy physics for decades, yet was essentially unmaintained. Despite continuing popularity as of 2008, it has been losing ground to the C++-based ROOT package. Conversion tutorials exist. In 2014, development and support were stopped. == Sample script == PAW uses its own scripting language. Here is sample code (with its actual output), which can be used to plot data gathered in files. * read data vector/read X,Y input_file.dat * eps plot fort/file 55 gg_ggg_dsig_dphid_179181.eps meta 55 -113 opt linx | linear scale opt logy | logarithmic scale * here goes plot set plci 1 | line color set lwid 2 | line width set dmod 1 | line type (solid, dotted, etc.) graph 32 X Y AL | 32 stands for input data lines in input file * plot title


id: plotly-20260505-0
file: data/en.wikipedia.org/wiki/Plotly-0.md
category: reference
title: Plotly
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Plotly
date_saved: 2026-05-05T10:13:09.001016+00:00
instance: kb-cron
parent: plotly-20260505-0
summary:
Plotly is a technical computing company headquartered in Montreal, Quebec, that develops online data analytics and visualization tools. Plotly provides online graphing, analytics, and statistics tools for individuals and collaboration, as well as scientific graphing libraries for Python, R, MATLAB, Perl, Julia, Arduino, JavaScript and REST. == History == Plotly was founded by Alex Johnson, Jack Parmer, Chris Parmer, and Matthew Sundquist. The founders' backgrounds are in science, energy, and data analysis and visualization. Early employees include Christophe Viau, a Canadian software engineer and Ben Postlethwaite, a Canadian geophysicist. Plotly was named one of the Top 20 Hottest Innovative Companies in Canada by the Canadian Innovation Exchange. Plotly was featured in "startup row" at PyCon 2013, and sponsored the SciPy 2018 conference. Plotly raised $5.5 million during its Series A funding, led by MHS Capital, Siemens Venture Capital, Rho Ventures, Real Ventures, and Silicon Valley Bank. The Boston Globe and Washington Post newsrooms have produced data journalism using Plotly. In 2020, Plotly was named a Best Place to Work by the Canadian SME National Business Awards, and nominated as Business of the Year. == Products == Plotly offers open-source and enterprise products. Dash is an open-source Python, R, and Julia


id: poem-home-20260505-0
file: data/en.wikipedia.org/wiki/POEM@Home-0.md
category: reference
title: POEM@Home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/POEM@Home
date_saved: 2026-05-05T10:13:10.235604+00:00
instance: kb-cron
parent: poem-home-20260505-0
summary:
POEM@Home was a volunteer computing project hosted by the Karlsruhe Institute of Technology and running on the Berkeley Open Infrastructure for Network Computing (BOINC) software platform. It modeled protein folding using Anfinsen's dogma. POEM@Home was started in 2007 and, due to advances using GPUs that rendered the BOINC program redundant, concluded in October 2016. The POEM@home applications were proprietary. == Scientific objectives == The project studied how protein structure determined protein function, predict a protein's structure from its amino acid sequence, investigated how proteins interact with each other, and understand how malfunctioning proteins can cause functional disorders. The resulting knowledge could then be used in the development of medical treatments. == See also == List of volunteer computing projects == References == == External links == POEM@Home website Berkeley Open Infrastructure for Network Computing (BOINC)


id: predictor-home-20260505-0
file: data/en.wikipedia.org/wiki/Predictor@home-0.md
category: reference
title: Predictor@home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Predictor@home
date_saved: 2026-05-05T10:13:11.432786+00:00
instance: kb-cron
parent: predictor-home-20260505-0
summary:
Predictor@home was a volunteer computing project that used BOINC software to predict protein structure from protein sequence in the context of the 6th biannual CASP, or Critical Assessment of Techniques for Protein Structure Prediction. A major goal of the project was the testing and evaluating of new algorithms to predict both known and unknown protein structures. Predictor@home was complementary to Folding@home. Whereas the latter aims to study the dynamics of protein folding, Predictor@home aimed to specify what the final tertiary structure will be. Also, the two projects differ significantly in the infrastructure they use. The project used BOINC software, whereas Folding@home maintains its own software completely outside of BOINC. However, for a time, Predictor@home competed with other BOINC protein structure prediction projects, such as Rosetta@home. Each uses different methods of rapidly and reliably predicting the final tertiary structure. Predictor@home is currently inactive. == History == Predictor@home holds the distinction of being the first independent BOINC project to be launched. The project was set up and run by Michela Taufer at The Scripps Research Institute. On September 6, 2006, Predictor@home was temporarily taken off line, with no new work units being sent out. In May, 2008, the project reverted to Alpha


id: primegrid-20260505-0
file: data/en.wikipedia.org/wiki/PrimeGrid-0.md
category: reference
title: PrimeGrid
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/PrimeGrid
date_saved: 2026-05-05T10:13:12.640012+00:00
instance: kb-cron
parent: primegrid-20260505-0
summary:
PrimeGrid is a volunteer computing project that searches for very large (up to world-record size) prime numbers whilst also aiming to solve long-standing mathematical conjectures. It uses the Berkeley Open Infrastructure for Network Computing (BOINC) platform. PrimeGrid offers a number of subprojects for prime-number sieving and discovery. Some of these are available through the BOINC client, others through the PRPNet client. Some of the work is manual, i.e. it requires manually starting work units and uploading results. Different subprojects may run on different operating systems, and may have executables for CPUs, GPUs, or both; while running the Lucas–Lehmer–Riesel test, CPUs with Advanced Vector Extensions and Fused Multiply-Add instruction sets will yield the fastest results for non-GPU accelerated workloads. PrimeGrid awards badges to users in recognition of achieving certain defined levels of credit for work done. The badges have no intrinsic value but are valued by many as a sign of achievement. The issuing of badges should also benefit PrimeGrid by evening out the participation in the less popular sub projects. The easiest of the badges can often be obtained in less than a day by a single computer, whereas the most challenging badges will require far more time and computing


id: primegrid-20260505-1
file: data/en.wikipedia.org/wiki/PrimeGrid-1.md
category: reference
title: PrimeGrid
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/PrimeGrid
date_saved: 2026-05-05T10:13:12.640012+00:00
instance: kb-cron
parent: primegrid-20260505-0
summary:
=== Riesel Problem === As of 13 December 2022, PrimeGrid has eliminated 18 values of k from the Riesel problem and is continuing the search to eliminate the 43 remaining numbers. 3 values of k are found by independent searchers. === Twin prime search === Primegrid worked with the Twin Prime Search to search for a record-sized twin prime at approximately 58,700 digits. The new world's largest known twin prime 2003663613 × 2195000 ± 1 was eventually discovered on January 15, 2007 (sieved by Twin Prime Search and tested by PrimeGrid). The search continued for another record twin prime at just above 100,000 digits. It was completed in August 2009 when PrimeGrid found 65516468355 × 2333333 ± 1. Continued testing for twin primes in conjunction with the search for a Sophie Germain prime yielded a new record twin prime in September 2016 upon finding the number 2996863034895 × 21290000 ± 1 composed of 388,342 digits. === Woodall prime search === As of 22 April 2018, the project has discovered the four largest Woodall primes known to date. The largest of these is 17016602 × 217016602 − 1 and was found on 21 March 2018. The search continues for an even


id: proteins-home-20260505-0
file: data/en.wikipedia.org/wiki/Proteins@home-0.md
category: reference
title: Proteins@home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Proteins@home
date_saved: 2026-05-05T10:13:14.003094+00:00
instance: kb-cron
parent: proteins-home-20260505-0
summary:
proteins@home was a volunteer computing project that used the BOINC architecture. The project was run by the Department of Biology at École Polytechnique. The project began on December 28, 2006, and ended in June 2008. == Purpose == proteins@home was a large-scale non-profit protein structure prediction project utilizing volunteer computing to perform intensive computations in a small amount of time. From their website: The amino acid sequence of a protein determines its three-dimensional structure, or 'fold'. Conversely, the three-dimensional structure is compatible with a large, but limited set of amino acid sequences. Enumerating the allowed sequences for a given fold is known as the 'inverse protein folding problem'. We are working to solve this problem for a large number of known protein folds (a representative subset: about 1500 folds). The most expensive step is to build a database of energy functions that describe all these structures. For each structure, we consider all possible sequences of amino acids. Surprisingly, this is computationally tractable, because our energy functions are sums over pairs of interactions. Once this is done, we can explore the space of amino acid sequences in a fast and efficient way, and retain the most favorable sequences. This large-scale mapping


id: proteowizard-20260505-0
file: data/en.wikipedia.org/wiki/ProteoWizard-0.md
category: reference
title: ProteoWizard
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/ProteoWizard
date_saved: 2026-05-05T10:13:15.181942+00:00
instance: kb-cron
parent: proteowizard-20260505-0
summary:
ProteoWizard is a set of open-source, cross-platform tools and libraries for proteomics data analyses. It provides a framework for unified mass spectrometry data file access and performs standard chemistry and LCMS dataset computations. Specifically, it is able to read many of the vendor-specific, proprietary formats and converting the data into an open data format. On the application level, the software provides executables for data conversion (msConvert, msConvertGUI and idConvert), data visualization (msPicture and seeMS), data access (msAccess, msCat, idCat and msPicture), data analysis (peekaboo and msPrefix14) and basic proteomics utilities (chainsaw). In addition, the project also hosts the Skyline software which helps to create, acquire and analyze targeted proteomics experiments such as SRM experiments. The main contributors to the project are the Tabb, MacCoss and Mallick research labs as well as Insilicos. == See also == OpenMS Trans-Proteomic Pipeline Mass spectrometry software Skyline (software) == References == == External links == Project Homepage


id: psychtoolbox-for-matlab-20260505-0
file: data/en.wikipedia.org/wiki/Psychtoolbox_for_MATLAB-0.md
category: reference
title: Psychtoolbox for MATLAB
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Psychtoolbox_for_MATLAB
date_saved: 2026-05-05T10:13:16.339780+00:00
instance: kb-cron
parent: psychtoolbox-for-matlab-20260505-0
summary:
Psychophysics Toolbox Version 3 (PTB-3) is a collection of free functions for MATLAB or GNU Octave intended for use by neuroscience and vision researchers. It synthesizes and shows accurately controlled visual and auditory stimuli and interacts with the observer. It has at least twelve thousand active users, an active forum, and many citations. PTB-3 is based on the Psychophysics Toolbox Version 2 (PTB-2) but its MATLAB extensions (in C) were rewritten to be more modular and use OpenGL. Psychtoolbox is offered alongside many alternative toolboxes for programming Psychophysics and Psychology experiments, such as PsychoPy for Python or jsPsych for JavaScript. Psychophysics Toolbox Version 3 is free software. Most of it is released under the MIT License, but parts of it are licensed under other open source and free software licenses. == References == == External links == Official website Psychtoolbox Forum


id: ptolemy-project-20260505-0
file: data/en.wikipedia.org/wiki/Ptolemy_Project-0.md
category: reference
title: Ptolemy Project
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Ptolemy_Project
date_saved: 2026-05-05T10:13:17.482780+00:00
instance: kb-cron
parent: ptolemy-project-20260505-0
summary:
The Ptolemy Project is an ongoing project aimed at modeling, simulating, and designing concurrent, real-time, embedded systems. The focus of the Ptolemy Project is on assembling concurrent components. The principal product of the project is the Ptolemy II model based design and simulation tool. The Ptolemy Project is conducted in the Industrial Cyber-Physical Systems Center (iCyPhy) in the Department of Electrical Engineering and Computer Sciences of the University of California, Berkeley, and is directed by Prof. Edward A. Lee. The key underlying principle in the project is the use of well-defined models of computation that govern the interaction between components. A major problem area being addressed is the use of heterogeneous mixtures of models of computation. The project is named after Claudius Ptolemaeus, the 2nd century Greek astronomer, mathematician, and geographer. The Kepler Project, a community-driven collaboration among researchers at three other University of California campuses has created the Kepler scientific workflow system which is based on Ptolemy II. == References == == External links == Official website The Kepler Project


id: pwpaw-20260505-0
file: data/en.wikipedia.org/wiki/Pwpaw-0.md
category: reference
title: Pwpaw
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Pwpaw
date_saved: 2026-05-05T10:13:18.648838+00:00
instance: kb-cron
parent: pwpaw-20260505-0
summary:
PWPAW A Projector Augmented Wave (PAW) code for electronic structure calculation. It is a free software package, distributed under the copyleft GNU General Public License. It is a plane wave implementation of the projector augmented wave (PAW) method developed by Peter E. Blöchl for electronic structure calculations within the framework of density functional theory. In addition to the self-consistent calculation of the electronic structure of a periodic solid, the program has a number of other capabilities, including structural geometry optimization and molecular dynamics simulations within the Born–Oppenheimer approximation. == See also == Atompaw Software package for electron configuration calculations EXCITING Bloch's theorem == References ==


id: pytorch-20260505-0
file: data/en.wikipedia.org/wiki/PyTorch-0.md
category: reference
title: PyTorch
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/PyTorch
date_saved: 2026-05-05T10:13:19.861916+00:00
instance: kb-cron
parent: pytorch-20260505-0
summary:
PyTorch is an open-source deep learning library, originally developed by Meta Platforms and currently developed with support from the Linux Foundation. The successor to Torch, PyTorch provides a high-level API that builds upon optimised, low-level implementations of deep learning algorithms and architectures, such as the Transformer, or SGD. Notably, this API simplifies model training and inference to a few lines of code. PyTorch allows for automatic parallelization of training and, internally, implements CUDA bindings that speed training further by leveraging GPU resources. PyTorch utilises the tensor as a fundamental data type, similarly to NumPy. Training is facilitated by a reversed automatic differentiation system, Autograd, that constructs a directed acyclic graph of the operations (and their arguments) executed by a model during its forward pass. With a loss, backpropagation is then undertaken. As of 2025, PyTorch remains one of the most popular deep learning libraries, alongside others such as TensorFlow and Keras. It can be installed using Anaconda package managers. A number of commercial deep learning architectures are built on top of PyTorch, including ChatGPT, Tesla Autopilot, Uber's Pyro, and Hugging Face's Transformers. == History == In 2001, Torch was written and released under a GPL. It was a machine-learning library


id: qmc-home-20260505-0
file: data/en.wikipedia.org/wiki/QMC@Home-0.md
category: reference
title: QMC@Home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/QMC@Home
date_saved: 2026-05-05T10:13:21.032688+00:00
instance: kb-cron
parent: qmc-home-20260505-0
summary:
QMC@Home was a volunteer computing project for the BOINC client aimed at further developing and testing Quantum Monte Carlo (QMC) for use in quantum chemistry. It is hosted by the University of Münster with participation by the Cavendish Laboratory. QMC@Home allows volunteers from around the world to donate idle computer cycles to help calculate molecular geometry using Diffusion Monte Carlo. The project is developing a new application using density functional theory. The project began its Beta testing on 23 May 2006. As of February 2010, QMC@Home has about 7,500 active participants from 102 countries, contributing about 5 teraFLOPS of computation power. == Workunits == In order to get results from home computers the work is split into "workunits". The time it takes to complete a workunit depends on the size of the calculated system and the speed of the user's computer. The target time is between 4 and 48 hours on a 2.4 GHz system. This is a list of molecules recently tested: 1a Ammonia; 1 Ammonia dimer; 2a Water; 2 Water dimer; 3a Formic acid; 3 Formic acid dimer; 4a Formamide; 4 Formamide dimer; 5a Uracil; 5 Uracil dimer; 6a 2-pyridoxine; 6b 2-aminopyridine; 6 2-pyridoxine/2-aminopyridine; 7a Adenine; 7b Thymine;


id: quake-catcher-network-20260505-0
file: data/en.wikipedia.org/wiki/Quake-Catcher_Network-0.md
category: reference
title: Quake-Catcher Network
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quake-Catcher_Network
date_saved: 2026-05-05T10:13:22.263846+00:00
instance: kb-cron
parent: quake-catcher-network-20260505-0
summary:
The Quake-Catcher Network was an initiative run by the University of Southern California that aimed to use computer-based accelerometers to detect earthquakes. It used the BOINC volunteer computing platform (a form of distributed computing, similar to SETI@home). It supported mobile devices (smartphones and some tablets/laptops) that have a built-in accelerometer. It also supported three external USB devices - the codemercs.com JoyWarrior 24F8, the ONavi sensor, and the MotionNode Accel. In 2011, project scientist Elizabeth Cochran was awarded a Presidential Early Career Award from US President Barack Obama in large part due to her founding of the Quake-Catcher Network project. The Quake Catcher Network project started at Stanford University in 2008, then moved to Caltech, and joined the Southern California Earthquake Center (SCEC) and the Incorporated Research Institutions for Seismology (IRIS) in 2016. The Quake-Catcher Network was discontinued on June 1st 2023 == References == == External links == Interactive world map, showing recent earthquakes (day/week/month) Archived 2018-01-07 at the Wayback Machine – result of QCN


id: quantum-espresso-20260505-0
file: data/en.wikipedia.org/wiki/Quantum_ESPRESSO-0.md
category: reference
title: Quantum ESPRESSO
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quantum_ESPRESSO
date_saved: 2026-05-05T10:13:23.445932+00:00
instance: kb-cron
parent: quantum-espresso-20260505-0
summary:
Quantum ESPRESSO (Quantum Open-Source Package for Research in Electronic Structure, Simulation, and Optimization; QE) is a suite for first-principles electronic-structure calculations and materials modeling, distributed for free and as free software under the GNU General Public License. It is based on density functional theory (DFT), plane wave basis sets, and pseudopotentials (both norm-conserving and ultrasoft). The core plane wave DFT functions of QE are provided by the PWscf component (PWscf previously existed as an independent project). PWscf (Plane-Wave Self-Consistent Field) is a set of programs for electronic structure calculations within DFT and density functional perturbation theory, using plane wave basis sets and pseudopotentials. The software is released under the GNU General Public License. The latest stable version QE-7.4.1 was released on 14 March 2025. == Quantum ESPRESSO Project == Quantum ESPRESSO is an open initiative of the CNR-IOM DEMOCRITOS National Simulation Center in Trieste (Italy) and its partners, in collaboration with different centers worldwide such as MIT, Princeton University, the University of Minnesota and the École Polytechnique Fédérale de Lausanne. The project is coordinated by the QUANTUM ESPRESSO foundation, which was formed by many research centers and groups all over the world. The first version, called pw.1.0.0, was released on


id: quarto-software-20260505-0
file: data/en.wikipedia.org/wiki/Quarto_(software)-0.md
category: reference
title: Quarto (software)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Quarto_(software)
date_saved: 2026-05-05T10:13:24.596354+00:00
instance: kb-cron
parent: quarto-software-20260505-0
summary:
Quarto is a free and open-source scientific and technical publishing system developed by Posit PBC (formerly RStudio). It is a command-line tool built on Pandoc that converts plain text documents mixed with executable code including Python, R, Julia, and Observable JavaScript into static formats including PDF, HTML, MS Word, PowerPoint, ePub, RevealJS, and MediaWiki. Quarto is considered the successor to R Markdown, extending support beyond the R ecosystem to support a broader range of data science languages and environments. == History == Quarto was officially announced in July 2022 at the `rstudio::conf(2022)` conference. The release coincided with the corporate rebranding of the developer from RStudio to Posit. This rebranding and the launch of Quarto reflected a strategic shift to support language-agnostic data science workflows, specifically acknowledging the growing adoption of Python alongside R in scientific research. == Design and implementation == Quarto is implemented as a Command Line Interface (CLI), which allows it to function independently of any specific Integrated Development Environment (IDE). However, extensions are available for IDEs such as RStudio, Visual Studio Code, and Jupyter. === File formats === The native source format for Quarto uses the `.qmd` extension. These files are plain text files that combine Markdown


id: qutemol-20260505-0
file: data/en.wikipedia.org/wiki/QuteMol-0.md
category: reference
title: QuteMol
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/QuteMol
date_saved: 2026-05-05T10:13:25.744050+00:00
instance: kb-cron
parent: qutemol-20260505-0
summary:
QuteMol is an open-source, interactive, molecular visualization system that was based on advanced rendering techniques that make possible to have for the first time a set of innovative visualization modalities in an interactive real-time application. QuteMol was the first system to use the capabilities of GPUs through OpenGL shaders to offer an array of innovative visual effects. QuteMol visualization techniques are aimed at improving clarity and an easier understanding of the 3D shape and structure of large molecules or complex proteins. In 2021 the IEEE Visualization Conference awarded the paper introducing QuteMol with the Test of Time Award to testify that "contents are still vibrant and useful today and have had a major impact and influence within and beyond the visualization community." Features available in QuteMol include: Real Time ambient occlusion Depth Aware Silhouette Enhancement Ball and Sticks, space-filling and Liquorice visualization modes High resolution antialiased snapshots for creating publication quality renderings Interactive rendering of large molecules and protein (100k atoms) Standard Protein Data Bank input. Notably after many years since the last release QuteMol is still used in the molecular visualization community as can be testified by searching on google scholar for papers citing explicitly the tool or the


id: rasmol-20260505-0
file: data/en.wikipedia.org/wiki/RasMol-0.md
category: reference
title: RasMol
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/RasMol
date_saved: 2026-05-05T10:13:26.941484+00:00
instance: kb-cron
parent: rasmol-20260505-0
summary:
RasMol is a computer program written for molecular graphics visualization intended and used mainly to depict and explore biological macromolecule structures, such as those found in the Protein Data Bank (PDB). == History == It was originally developed by Roger Sayle in the early 1990s. Historically, it was an important tool for molecular biologists since the extremely optimized program allowed the software to run on (then) modestly powerful personal computers. Before RasMol, visualization software ran on graphics workstations that, due to their cost, were less accessible to scholars. RasMol continues to be important for research in structural biology, and has become important in education. RasMol has a complex licensing version history. Starting with the version 2.7 series, RasMol source code is dual-licensed under a GNU General Public License (GPL), or custom license RASLIC. Starting with version 2.7.5, a GPL is the only license valid for binary distributions. RasMol includes a scripting language, to perform many functions such as selecting certain protein chains, changing colors, etc. Jmol and Sirius software have incorporated this language into their commands. Protein Data Bank (PDB) files can be downloaded for visualization from members of the Worldwide Protein Data Bank (wwPDB). These have been uploaded by


id: rmetrics-20260505-0
file: data/en.wikipedia.org/wiki/Rmetrics-0.md
category: reference
title: Rmetrics
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Rmetrics
date_saved: 2026-05-05T10:13:28.611150+00:00
instance: kb-cron
parent: rmetrics-20260505-0
summary:
Rmetrics is a free and open-source software project designed for teaching computational finance. Rmetrics is based primarily on the statistical R programming language, but does contain contributions in other programming languages, such as Fortran, C, and C++. The project was started in 2001 by Diethelm Wuertz, based at the Swiss Federal Institute of Technology in Zurich. == Rmetrics packages == Most Rmetrics components are distributed as R packages, which are add-on modules for R. == Goals == The broad goals of the projects are: To provide widespread access to a broad range of powerful statistical and graphical methods for the analysis of market data and risk management in finance. To provide a common software platform that enables the rapid development and deployment of extensible, scalable, and interoperable software. To strengthen scientific understanding by producing high-quality documentation and reproducible research. To train researchers on computational and statistical methods for the analysis of financial data and for financial risk management. == R/Rmetrics project == Rmetrics provides a high-level interpreted language, as well as data and model visualization capabilities. It allows for research in parallel statistical computing with an object oriented framework for computational finance, and financial engineering. == Open source commitment ==


id: rnn-software-20260505-0
file: data/en.wikipedia.org/wiki/Rnn_(software)-0.md
category: reference
title: Rnn (software)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Rnn_(software)
date_saved: 2026-05-05T10:13:30.648216+00:00
instance: kb-cron
parent: rnn-software-20260505-0
summary:
rnn is an open-source machine learning framework that implements recurrent neural network architectures, such as LSTM and GRU, natively in the R programming language, that has been downloaded over 100,000 times (from the RStudio servers alone). The rnn package is distributed through the Comprehensive R Archive Network under the open-source GPL v3 license. == Workflow == The below example from the rnn documentation show how to train a recurrent neural network to solve the problem of bit-by-bit binary addition. == sigmoid == The sigmoid functions and derivatives used in the package were originally included in the package, from version 0.8.0 onwards, these were released in a separate R package sigmoid, with the intention to enable more general use. The sigmoid package is a dependency of the rnn package and therefore automatically installed with it. == Reception == With the release of version 0.3.0 in April 2016 the use in production and research environments became more widespread. The package was reviewed several months later on the R blog The Beginner Programmer as "R provides a simple and very user friendly package named rnn for working with recurrent neural networks.", which further increased usage. The book Neural Networks in R by Balaji


id: root-20260505-0
file: data/en.wikipedia.org/wiki/ROOT-0.md
category: reference
title: ROOT
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/ROOT
date_saved: 2026-05-05T10:13:31.807619+00:00
instance: kb-cron
parent: root-20260505-0
summary:
ROOT is an object-oriented computer program and library developed by CERN. It was originally designed for particle physics data analysis and contains several features specific to the field, but it is also used in other applications such as astronomy and data mining. The latest minor release is 6.34, as of 2025-04-08. == Description == CERN maintained the CERN Program Library written in FORTRAN for many years. Its development and maintenance were discontinued in 2003 in favour of ROOT, which is written in the C++ programming language. ROOT development was initiated by René Brun and Fons Rademakers in 1994. Some parts are published under the GNU Lesser General Public License (LGPL) and others are based on GNU General Public License (GPL) software, and are thus also published under the terms of the GPL. It provides platform independent access to a computer's graphics subsystem and operating system using abstract layers. Parts of the abstract platform are: a graphical user interface and a GUI builder, container classes, reflection, a C++ script and command line interpreter (CINT in version 5, cling in version 6), object serialization and persistence. The packages provided by ROOT include those for Histogramming and graphing to view and analyze distributions


id: rosetta-home-20260505-0
file: data/en.wikipedia.org/wiki/Rosetta@home-0.md
category: reference
title: Rosetta@home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Rosetta@home
date_saved: 2026-05-05T10:13:33.048042+00:00
instance: kb-cron
parent: rosetta-home-20260505-0
summary:
Rosetta@home is a volunteer computing project researching protein structure prediction on the Berkeley Open Infrastructure for Network Computing (BOINC) platform, run by the Baker lab. Rosetta@home aims to predict protein–protein docking and design new proteins with the help of about fifty-five thousand active volunteered computers processing at over 487,946 gigaFLOPS on average as of September 19, 2020. Foldit, a Rosetta@home videogame, aims to reach these goals with a crowdsourcing approach. Though much of the project is oriented toward basic research to improve the accuracy and robustness of proteomics methods, Rosetta@home also does applied research on malaria, Alzheimer's disease, and other pathologies. Like all BOINC projects, Rosetta@home uses idle computer processing resources from volunteers' computers to perform calculations on individual workunits. Completed results are sent to a central project server where they are validated and assimilated into project databases. The project is cross-platform, and runs on a wide variety of hardware configurations. Users can view the progress of their individual protein structure prediction on the Rosetta@home screensaver. In addition to disease-related research, the Rosetta@home network serves as a testing framework for new methods in structural bioinformatics. Such methods are then used in other Rosetta-based applications, like RosettaDock or the Human Proteome


id: rosetta-home-20260505-1
file: data/en.wikipedia.org/wiki/Rosetta@home-1.md
category: reference
title: Rosetta@home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Rosetta@home
date_saved: 2026-05-05T10:13:33.048042+00:00
instance: kb-cron
parent: rosetta-home-20260505-0
summary:
A primary feature of the Rosetta@home graphical user interface (GUI) is a screensaver which shows a current workunit's progress during the simulated protein folding process. In the upper-left of the current screensaver, the target protein is shown adopting different shapes (conformations) in its search for the lowest energy structure. Depicted immediately to the right is the structure of the most recently accepted. On the upper right the lowest energy conformation of the current decoy is shown; below that is the true, or native, structure of the protein if it has already been determined. Three graphs are included in the screensaver. Near the middle, a graph for the accepted model's thermodynamic free energy is displayed, which fluctuates as the accepted model changes. A graph of the accepted model's root-mean-square deviation (RMSD), which measures how structurally similar the accepted model is to the native model, is shown far right. On the right of the accepted energy graph and below the RMSD graph, the results from these two functions are used to produce an energy vs. RMSD plot as the model is progressively refined. Like all BOINC projects, Rosetta@home runs in the background of the user's computer, using idle computer power, either at


id: rosetta-home-20260505-2
file: data/en.wikipedia.org/wiki/Rosetta@home-2.md
category: reference
title: Rosetta@home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Rosetta@home
date_saved: 2026-05-05T10:13:33.048042+00:00
instance: kb-cron
parent: rosetta-home-20260505-0
summary:
== Disease-related research == In addition to basic research in predicting protein structure, docking and design, Rosetta@home is also used in immediate disease-related research. Numerous minor research projects are described in David Baker's Rosetta@home journal. As of February 2014, information on recent publications and a short description of the work are being updated on the forum. The forum thread is no longer used since 2016, and news on the research can be found on the general news section of the project. === Alzheimer's disease === A component of the Rosetta software suite, RosettaDesign, was used to accurately predict which regions of amyloidogenic proteins were most likely to make amyloid-like fibrils. By taking hexapeptides (six amino acid-long fragments) of a protein of interest and selecting the lowest energy match to a structure similar to that of a known fibril forming hexapeptide, RosettaDesign was able to identify peptides twice as likely to form fibrils as are random proteins. Rosetta@home was used in the same study to predict structures for amyloid beta, a fibril-forming protein that has been postulated to cause Alzheimer's disease. Preliminary but as yet unpublished results have been produced on Rosetta-designed proteins that may prevent fibrils from forming, although it


id: rosetta-home-20260505-3
file: data/en.wikipedia.org/wiki/Rosetta@home-3.md
category: reference
title: Rosetta@home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Rosetta@home
date_saved: 2026-05-05T10:13:33.048042+00:00
instance: kb-cron
parent: rosetta-home-20260505-0
summary:
== Rosetta software == Rosetta is the software responsible for performing structure prediction in Rosetta@home. Besides a BOINC cluster, Rosetta can run on a single local computer, or on a local supercomputer. Similar to other bioinformatic programs, there are online public servers offering to run Rosetta from a web interface. The software is freely licensed to the academic community and available to pharmaceutical companies for a fee. Originally introduced by the Baker laboratory at the University of Washington in 1998 as an ab initio approach to structure prediction, Rosetta has since branched into several development streams and distinct services, providing features such as macromolecular docking and protein design. Many of the graduate students and other researchers involved in Rosetta's initial development have since moved to other universities and research institutions, and subsequently enhanced different parts of the Rosetta project. The Rosetta platform derives its name from the Rosetta Stone, as it attempts to decipher the structural "meaning" of proteins' amino acid sequences. Development of the Rosetta code is done by Rosetta Commons. Rosetta participates in CASP and CAPRI. Rosetta was rewritten in C++ to allow easier development than that allowed by its original version, which was written in Fortran. This


id: rosetta-home-20260505-4
file: data/en.wikipedia.org/wiki/Rosetta@home-4.md
category: reference
title: Rosetta@home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Rosetta@home
date_saved: 2026-05-05T10:13:33.048042+00:00
instance: kb-cron
parent: rosetta-home-20260505-0
summary:
=== Robetta === The Robetta (Rosetta Beta) server is an automated protein structure prediction service offered by the Baker laboratory for non-commercial ab initio and comparative modeling. It has participated as an automated prediction server in the biannual CASP experiments since CASP5 in 2002, performing among the best in the automated server prediction category. Robetta has since competed in CASP6 and 7, where it did better than average among both automated server and human predictor groups. It also participates in the CAMEO3D continuous evaluation. Robetta tasks run on Baker lab servers, Janelia Research Campus machines, and Rosetta@home participant computers. In modeling protein structure as of CASP6, Robetta first searches for structural homologs using BLAST, PSI-BLAST, and 3D-Jury, then parses the target sequence into its individual domains, or independently folding units of proteins, by matching the sequence to structural families in the Pfam database. Domains with structural homologs then follow a "template-based model" (i.e., homology modeling) protocol. Here, the Baker laboratory's in-house alignment program, K*sync, produces a group of sequence homologs, and each of these is modeled by the Rosetta de novo method to produce a decoy (possible structure). The final structure prediction is selected by taking the lowest energy model


id: rosetta-home-20260505-5
file: data/en.wikipedia.org/wiki/Rosetta@home-5.md
category: reference
title: Rosetta@home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Rosetta@home
date_saved: 2026-05-05T10:13:33.048042+00:00
instance: kb-cron
parent: rosetta-home-20260505-0
summary:
== Volunteer contributions == Rosetta@home depends on computing power donated by individual project members for its research. As of March 28, 2020, about 53,000 users from 150 countries were active members of Rosetta@home, together contributing idle processor time from about 54,800 computers for a combined average performance of over 1.7 PetaFLOPS. Users are granted BOINC credits as a measure of their contribution. The credit granted for each workunit is the number of decoys produced for that workunit multiplied by the average claimed credit for the decoys submitted by all computer hosts for that workunit. This custom system was designed to address significant differences between credit granted to users with the standard BOINC client and an optimized BOINC client, and credit differences between users running Rosetta@home on Windows and Linux operating systems. The amount of credit granted per second of CPU work is lower for Rosetta@home than most other BOINC projects. Rosetta@home is thirteenth out of over 40 BOINC projects in terms of total credit. Rosetta@home users who predict protein structures submitted for the CASP experiment are acknowledged in scientific publications regarding their results. Users who predict the lowest energy structure for a given workunit are featured on the Rosetta@home homepage


id: rule-based-modeling-20260505-0
file: data/en.wikipedia.org/wiki/Rule-based_modeling-0.md
category: reference
title: Rule-based modeling
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Rule-based_modeling
date_saved: 2026-05-05T10:13:34.226929+00:00
instance: kb-cron
parent: rule-based-modeling-20260505-0
summary:
Rule-based modeling is a modeling approach that uses a set of rules that indirectly specifies a mathematical model. The rule-set can either be translated into a model such as Markov chains or differential equations, or be treated using tools that directly work on the rule-set in place of a translated model, as the latter is typically much bigger. Rule-based modeling is especially effective in cases where the rule-set is significantly simpler than the model it implies, meaning that the model is a repeated manifestation of a limited number of patterns. An important domain where this is often the case is biochemical models of living organisms. Groups of mutually corresponding substances are subject to mutually corresponding interactions. BioNetGen is a suite of software tools used to generate mathematical models consisting of ordinary differential equations without generating the equations directly. For example below is an example rule in the BioNetGen format: A ( a , a ) + B ( b ) − > A ( a ! 1 ) . B ( b ! 1 ) {\displaystyle A(a,a)+B(b)->A(a!1).B(b!1)} Where: A(a,a): Represents a model species A with two free binding sites a B(b): Represents a model species B with one free binding


id: scipy-20260505-0
file: data/en.wikipedia.org/wiki/SciPy-0.md
category: reference
title: SciPy
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/SciPy
date_saved: 2026-05-05T10:13:35.400057+00:00
instance: kb-cron
parent: scipy-20260505-0
summary:
SciPy (pronounced "sigh pie") is a free and open-source Python library used for scientific computing and technical computing. SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, fast Fourier transform, signal and image processing, ordinary differential equation solvers and other tasks common in science and engineering. SciPy is also a family of conferences for users and developers of these tools: SciPy (in the United States), EuroSciPy (in Europe) and SciPy.in (in India). Enthought originated the SciPy conference in the United States and continues to sponsor many of the international conferences as well as host the SciPy website. The SciPy library is currently distributed under the BSD license, and its development is sponsored and supported by an open community of developers. It is also supported by NumFOCUS, a community foundation for supporting reproducible and accessible science. == Components == The SciPy package is at the core of Python's scientific computing capabilities. Available sub-packages include: cluster: hierarchical clustering, vector quantization, K-means constants: physical constants and conversion factors datasets: various example datasets for demonstrating image and data processing differentiate: numerical differentiation for first and second derivatives fft: Discrete Fourier Transform algorithms fftpack: Legacy interface for Discrete Fourier Transforms integrate: numerical integration


id: seasonal-attribution-project-20260505-0
file: data/en.wikipedia.org/wiki/Seasonal_Attribution_Project-0.md
category: reference
title: Seasonal Attribution Project
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Seasonal_Attribution_Project
date_saved: 2026-05-05T10:13:36.622040+00:00
instance: kb-cron
parent: seasonal-attribution-project-20260505-0
summary:
The Seasonal Attribution Project is a climate'prediction.net sub-project, with support from the WWF. It runs a high resolution model in order to try to determine the extent to which extreme weather events are attributable to human-induced global warming. The project did cease giving out more work, however there has been a project extension to try a fourth sea surface temperature pattern. Current work will still be accepted and used for collaborations and possibly revisions of papers during the review process. A further extension will start soon. == The experiments == United Kingdom floods of Autumn 2000 – Current project. Mountain snowpack decline in western North America Developed in collaboration with the Climate Impacts Group at the University of Washington. Heatwave occurrence in South Africa and India The latter two will use the same models. Information has been uploaded but analysis of information generated has not yet started. == See also == Effects of global warming == References == == External links == Seasonal Attribution Website Archived 2011-02-20 at the Wayback Machine


id: seismic-unix-20260505-0
file: data/en.wikipedia.org/wiki/Seismic_Unix-0.md
category: reference
title: Seismic Unix
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Seismic_Unix
date_saved: 2026-05-05T10:13:37.762608+00:00
instance: kb-cron
parent: seismic-unix-20260505-0
summary:
Seismic Unix is an open source seismic utilities package which was supported by the Center for Wave Phenomena (CWP) at the Colorado School of Mines (CSM). Currently it is supported by John Stockwell. == History == Einar Kjartansson began writing what is now called SU (the SY package) in the late 1970s while still a graduate student at Jon Claerbout's Stanford Exploration Project (SEP). He continued to expand the package while he was a professor at the University of Utah in the early eighties. In 1984, during an extended visit to SEP Kjartansson introduced SY to Shuki Ronen, then a graduate student at Stanford. Ronen further developed SY from 1984 to 1986. Other students at SEP started to use it and contributed code and ideas. SY was inspired by much other software developed at SEP and benefited from the foundations laid by Claerbout and many of his students; Rob Clayton, Stew Levin, Dave Hale, Jeff Thorson, Chuck Sword, and others who pioneered seismic processing on Unix in the seventies and early eighties. In 1986, Shuki Ronen brought this work to the CWP at Colorado School of Mines during his one-year postdoctoral appointment there, Ronen aided Cohen in turning SU into


id: seti-home-20260505-0
file: data/en.wikipedia.org/wiki/SETI@home-0.md
category: reference
title: SETI@home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/SETI@home
date_saved: 2026-05-05T10:13:38.996090+00:00
instance: kb-cron
parent: seti-home-20260505-0
summary:
SETI@home ("SETI at home") is a project of the Berkeley SETI Research Center to analyze radio signals with the aim of searching for signs of extraterrestrial intelligence. Until March 2020, it was run as an Internet-based public volunteer computing project that employed the BOINC software platform. It is hosted by the Space Sciences Laboratory at the University of California, Berkeley, and is one of many activities undertaken as part of the worldwide SETI effort. SETI@home software was released to the public on May 17, 1999, making it the third large-scale use of volunteer computing over the Internet for research purposes, after Great Internet Mersenne Prime Search (GIMPS) was launched in 1996 and distributed.net in 1997. Along with MilkyWay@home and Einstein@home, it has the investigation of phenomena in interstellar space as its primary purpose. In March 2020, the project stopped sending out new work to SETI@home users, bringing the crowdsourced computing aspect of the project to a stop. At the time, the team intended to shift focus onto the analysis and interpretation of the 20 years' worth of accumulated data. However, the team left open the possibility of eventually resuming volunteer computing using data from other radio telescopes, such as MeerKAT


id: seti-home-20260505-1
file: data/en.wikipedia.org/wiki/SETI@home-1.md
category: reference
title: SETI@home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/SETI@home
date_saved: 2026-05-05T10:13:38.996090+00:00
instance: kb-cron
parent: seti-home-20260505-0
summary:
== Technology == Anybody with an at least intermittently Internet-connected computer was able to participate in SETI@home by running a free program that downloaded and analyzed radio telescope data. Observational data were recorded on 2-terabyte SATA hard disk drives fed from the Arecibo Telescope in Puerto Rico, each holding about 2.5 days of observations, which were then sent to Berkeley. Arecibo does not have a broadband Internet connection, so data must go by postal mail to Berkeley. Once there, it is divided in both time and frequency domains work units of 107 seconds of data, or approximately 0.35 megabytes (350 kilobytes or 350,000 bytes), which overlap in time but not in frequency. These work units are then sent from the SETI@home server over the Internet to personal computers around the world to analyze. Data was merged into a database using SETI@home computers in Berkeley. Interference was rejected, and various pattern-detection algorithms were applied to search for the most interesting signals. The project used CUDA for GPU processing starting in 2015. In 2016 SETI@home began processing data from the Breakthrough Listen project. === Software === The SETI@home volunteer computing software ran either as a screensaver or continuously while a user worked,


id: seti-home-20260505-2
file: data/en.wikipedia.org/wiki/SETI@home-2.md
category: reference
title: SETI@home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/SETI@home
date_saved: 2026-05-05T10:13:38.996090+00:00
instance: kb-cron
parent: seti-home-20260505-0
summary:
== Competitive aspect == SETI@home users quickly started to compete with one another to process the maximum number of work units. Teams were formed to combine the efforts of individual users. The competition continued and grew larger with the introduction of BOINC. As with any competition, attempts have been made to "cheat" the system and claim credit for work that has not been performed. To combat cheats, the SETI@home system sends every work unit to multiple computers, a value known as "initial replication" (currently 2). Credit is only granted for each returned work unit once a minimum number of results have been returned and the results agree, a value known as "minimum quorum" (currently 2). If, due to computation errors or cheating by submitting false data, not enough results agree, more identical work units are sent out until the minimum quorum can be reached. The final credit granted to all machines which returned the correct result is the same and is the lowest of the values claimed by each machine. Some users have installed and run SETI@home on computers at their workplaces; an act known as "Borging", after the assimilation-driven Borg of Star Trek. In some cases, SETI@home users have


id: seti-home-20260505-3
file: data/en.wikipedia.org/wiki/SETI@home-3.md
category: reference
title: SETI@home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/SETI@home
date_saved: 2026-05-05T10:13:38.996090+00:00
instance: kb-cron
parent: seti-home-20260505-0
summary:
SETI@home is a test bed for further development not only of BOINC but of other hardware and software (database) technology. Under SETI@home processing loads, these experimental technologies can be more challenging than expected, as SETI databases do not have typical accounting and business data or relational structures. The non-traditional database uses often do incur greater processing overheads and risk of database corruption and outright database failure. Hardware, software and database failures can (and do) cause dips in project participation. The project has had to shut down several times to change over to new databases capable of handling more massive datasets. Hardware failure has proven to be a substantial source of project shutdowns, as hardware failure is often coupled with database corruption. == See also == == References == == Further reading == Carrigan, Richard A. Jr. (2003). "The Ultimate Hacker: SETI Signals May Need to Be Decontaminated". Bioastronomy 2002: Life Among the Stars. 213. Astronomical Society of the Pacific: 519. Bibcode:2004IAUS..213..519C. Sample, Ian (November 25, 2005). "Scientists be on guard..." The Guardian. London. Retrieved November 25, 2005. Scoles, Sarah (May 23, 2017). "A Brief History of SETI@Home". The Atlantic. == External links == Official website SETI@home screensaver video on YouTube


id: seti-home-beta-20260505-0
file: data/en.wikipedia.org/wiki/SETI@home_beta-0.md
category: reference
title: SETI@home beta
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/SETI@home_beta
date_saved: 2026-05-05T10:13:40.213482+00:00
instance: kb-cron
parent: seti-home-beta-20260505-0
summary:
SETI@home beta, is a hibernating volunteer computing project using the Berkeley Open Infrastructure for Network Computing (BOINC) platform, as a test environment for future SETI@home projects: AstroPulse is a volunteer computing project searching for primordial black holes, pulsars, and ETI. AstroPulse clients have been tested by this project for nearly 6 years. It is already running on SETI@home, testing new GPU/CPU optimized apps and performing other tasks. SETI Southern Hemisphere Search, which is another SETI@home project that was due to join BOINC. It was expected that this project would use a slightly modified version of the SETI enhanced client, as the Parkes Observatory has a feedhorn with more beams than the Arecibo Observatory. == Applications Testing == 11 Dec 2008, CUDA applications test 3 Jun 2013, SETI@home v7 test 01 Dec 2015 SETI@home v8 test == External links == Official website SETI@home beta screensaver video on YouTube == References ==


id: shelxle-20260505-0
file: data/en.wikipedia.org/wiki/ShelXle-0.md
category: reference
title: ShelXle
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/ShelXle
date_saved: 2026-05-05T10:13:41.339494+00:00
instance: kb-cron
parent: shelxle-20260505-0
summary:
The program ShelXle is a graphical user interface for the structure refinement program SHELXL. ShelXle combines an editor with syntax highlighting for the SHELXL-associated .ins (input) and .res (output) files with an interactive graphical display for visualization of a three-dimensional structure including the electron density (Fo) and difference density (Fo-Fc) maps. == Overview == ShelXle can display electron density maps like the macromolecular program Coot but is more intended for smaller molecules. A number of excellent graphical user interfaces (GUIs) exist for small molecule crystal structure refinement with SHELX (e.g., WINGX, Olex2, XSEED, PLATON and SYSTEM-S, and the Bruker programs XP and XSHELL) ShelXle is free software, distributed under the GNU LGPL. It is available from the ShelXle website or from SourceForge. Binaries are available for Windows, macOS and the Linux distributions SuSE, Debian and Ubuntu as well as Arch via the AUR. The Windows binary is distributed with the NSIS Installer. == Features == Editor featuring syntax highlighting and code completion for the SHELX instructions. Clicking on an atom in the structure view sets the text cursor to the line that contains this atom. Locating atoms in structure view from the editor. Rename mode with support of residues and


id: shogun-toolbox-20260505-0
file: data/en.wikipedia.org/wiki/Shogun_(toolbox)-0.md
category: reference
title: Shogun (toolbox)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Shogun_(toolbox)
date_saved: 2026-05-05T10:13:42.507319+00:00
instance: kb-cron
parent: shogun-toolbox-20260505-0
summary:
Shogun is a free, open-source machine learning software library written in C++. It offers numerous algorithms and data structures for machine learning problems. It offers interfaces for Octave, Python, R, Java, Lua, Ruby and C# using SWIG. It is licensed under the terms of the GNU General Public License version 3 or later. == Description == The focus of Shogun is on kernel machines such as support vector machines for regression and classification problems. Shogun also offers a full implementation of Hidden Markov models. The core of Shogun is written in C++ and offers interfaces for MATLAB, Octave, Python, R, Java, Lua, Ruby and C#. Shogun has been under active development since 1999. Today there is a rich user community across the world using Shogun as a base for research and education, and contributing to the core package. == Supported algorithms == Currently Shogun supports the following algorithms: Support vector machines Dimensionality reduction algorithms, such as PCA, Kernel PCA, Locally Linear Embedding, Hessian Locally Linear Embedding, Local Tangent Space Alignment, Linear Local Tangent Space Alignment, Kernel Locally Linear Embedding, Kernel Local Tangent Space Alignment, Multidimensional Scaling, Isomap, Diffusion Maps, Laplacian Eigenmaps Online learning algorithms such as SGD-QN, Vowpal Wabbit Clustering


id: siconos-20260505-0
file: data/en.wikipedia.org/wiki/Siconos-0.md
category: reference
title: Siconos
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Siconos
date_saved: 2026-05-05T10:13:43.796765+00:00
instance: kb-cron
parent: siconos-20260505-0
summary:
SICONOS is an open source scientific software primarily targeted at modeling and simulating non-smooth dynamical systems (NSDS): Mechanical systems (Rigid body or solid) with Unilateral contact and Coulomb friction as we find in Non-smooth mechanics, Contact dynamics or Granular material. Switched Electrical Circuit such as Power converter, Rectifier, Phase-locked loop (PLL) or Analog-to-digital converter Sliding mode control systems Other applications are found in Systems and Control (hybrid systems, differential inclusions, optimal control with state constraints), Optimization (Complementarity problem and Variational inequality) Biology Gene regulatory network, Fluid Mechanics and Computer graphics, etc. == Components == The software is based on 3 main components Siconos/Numerics (C API). Collection of low-level algorithms for solving basic Algebra and optimization problems arising in the simulation of nonsmooth dynamical systems Linear complementarity problem (LCP) Mixed linear complementarity problem (MLCP) Nonlinear complementarity problem (NCP) Quadratic programming problems (QP) Friction-contact problems (2D or 3D) (Second-order cone programming (SOCP)) Primal or Dual Relay problems Siconos/Kernel. API C++ that allows one to model and simulate the nonsmooth dynamical systems. It contains Dynamical systems classes : first order one, Lagrangian systems, Newton-Euler systems Nonsmooth laws : complementarity, Relay, Friction, Contact, impact Siconos/Front-end (API Python) Mainly an auto-generated SWIG interface of the


id: sim-js-20260505-0
file: data/en.wikipedia.org/wiki/SIM.JS-0.md
category: reference
title: SIM.JS
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/SIM.JS
date_saved: 2026-05-05T10:13:45.220630+00:00
instance: kb-cron
parent: sim-js-20260505-0
summary:
SIM.JS is an event-based discrete-event simulation library based on standard JavaScript. The library has been written in order to enable simulation within standard browsers by utilizing web technology. SIM.JS supports entities, resources (Facility, Buffers and Stores), communication (via Timers, Events and Messages) and statistics (with Data Series, Time Series and Population statistics). The SIM.JS distribution contains tutorials, in-depth documentation, and a large number of examples. SIM.JS is released as open source software under the LGPL license. The first version was released in January 2011. == Example == There are several examples bundled with the library download. Trafficlight simulation is a standard simulation problem, which may be simulated as within this example: == External links == Analysis of the potential role of open source discrete event simulation software in the manufacturing sector issued by Proceedings of the Operational Research Society Simulation Workshop 2012 comparing SIM.JS among other open source simulation solutions Bachelor thesis on Web-Based Single-Player Project Simulation Game reviewing SIM.JS Interactive Model-Centric Systems Engineering report by Systems Engineering Research Center managed by Stevens Institute of Technology mentioning SIM.JS "Just-In-Time parallel simulation" compares simulation programmed in JIT languages versus AOT languages referencing SIM.JS Modeling and Simulation of Tape Libraries for Hierarchical


id: similarity-matrix-of-proteins-20260505-0
file: data/en.wikipedia.org/wiki/Similarity_Matrix_of_Proteins-0.md
category: reference
title: Similarity Matrix of Proteins
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Similarity_Matrix_of_Proteins
date_saved: 2026-05-05T10:13:46.428893+00:00
instance: kb-cron
parent: similarity-matrix-of-proteins-20260505-0
summary:
Similarity Matrix of Proteins (SIMAP) is a database of protein similarities created using volunteer computing. It is freely accessible for scientific purposes. SIMAP uses the FASTA algorithm to precalculate protein similarity, while another application uses hidden Markov models to search for protein domains. SIMAP is a joint project of the Technical University of Munich, the Helmholtz Zentrum München, and the University of Vienna. == Project == The project usually got new work units at the beginning of each month. More recently, (2010), inclusion of environmental sequences into the database has required longer periods of activity, several months of continuous work for example. Typically, these updates occurred twice each year. In the fourth quarter of 2010, the project relocated to the University of Vienna due to the failing electrical infrastructure at the Technical University of Munich. Part of this exercise involved the creation of a project specific URL requiring existing volunteers and users to detach/reattach to the project. On May 30, 2014, it was announced by project administrators that after a 10-year history, SIMAP would be leaving BOINC by the end of 2014. SIMAP research, however, will go forward with the use of local hardware consisting of "ordinary multi-core CPUs (some


id: simpy-20260505-0
file: data/en.wikipedia.org/wiki/SimPy-0.md
category: reference
title: SimPy
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/SimPy
date_saved: 2026-05-05T10:13:47.593139+00:00
instance: kb-cron
parent: simpy-20260505-0
summary:
SimPy stands for “Simulation in Python”, is a process-based discrete-event simulation framework based on standard Python. It enables users to model active components such as customers, vehicles, or agents as simple Python generator functions. SimPy is released as open source software under the MIT License. The first version was released in December 2002. == Overview == Its event dispatcher is based on Python's generators and can be used for asynchronous networking or to implement multi-agent systems (with both, simulated and real communication). Simulations can be performed “as fast as possible”, in real time (wall clock time) or by manually stepping through the events. Though it is theoretically possible to do continuous simulations with SimPy, it lacks features to support them. However, for simulations with a fixed step size where processes don't interact with each other or with shared resources, a simple while loop is sufficient. Additionally, SimPy provides different types of shared resources to simulate congestion points that have limited capacity, such as servers, checkout counters, and tunnels. In version 3.1 and above, SimPy offers monitoring capabilities to assist in collecting statistics about processes and resources. SimPy 3.0 requires Python 3., while SimPy 4.0 requires Python 3.6+. SimPy distribution contains


id: simthyr-20260505-0
file: data/en.wikipedia.org/wiki/SimThyr-0.md
category: reference
title: SimThyr
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/SimThyr
date_saved: 2026-05-05T10:13:48.776319+00:00
instance: kb-cron
parent: simthyr-20260505-0
summary:
SimThyr is a free continuous dynamic simulation program for the pituitary-thyroid feedback control system. The open-source program is based on a nonlinear model of thyroid homeostasis. In addition to simulations in the time domain the software supports various methods of sensitivity analysis. Its simulation engine is multi-threaded and supports multiple processor cores. SimThyr provides a GUI, which allows for visualising time series, modifying constant structure parameters of the feedback loop (e.g. for simulation of certain diseases), storing parameter sets as XML files (referred to as "scenarios" in the software) and exporting results of simulations in various formats that are suitable for statistical software. SimThyr is intended for both educational purposes and in-silico research. == Mathematical model == The underlying model of thyroid homeostasis is based on fundamental biochemical, physiological and pharmacological principles, e.g. Michaelis-Menten kinetics, non-competitive inhibition and empirically justified kinetic parameters. The model has been validated in healthy controls and in cohorts of patients with hypothyroidism and thyrotoxicosis. == Scientific uses == Multiple studies have employed SimThyr for in silico research on the control of thyroid function. The original version was developed to check hypotheses about the generation of pulsatile TSH release. Later and expanded versions of the software


id: skyline-software-20260505-0
file: data/en.wikipedia.org/wiki/Skyline_(software)-0.md
category: reference
title: Skyline (software)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Skyline_(software)
date_saved: 2026-05-05T10:13:49.893321+00:00
instance: kb-cron
parent: skyline-software-20260505-0
summary:
Skyline is an open source software for targeted proteomics and metabolomics data analysis. It runs on Microsoft Windows and supports the raw data formats from multiple mass spectrometric vendors. It contains a graphical user interface to display chromatographic data for individual peptide or small molecule analytes. Skyline supports multiple workflows including selected reaction monitoring (SRM) / multiple reaction monitoring (MRM), parallel reaction monitoring (PRM), data-independent acquisition (DIA/SWATH) and targeted data-dependent acquisition. == See also == ProteoWizard OpenMS Trans-Proteomic Pipeline Mass spectrometry software == References == == External links == Skyline Homepage


id: slinca-home-20260505-0
file: data/en.wikipedia.org/wiki/SLinCA@Home-0.md
category: reference
title: SLinCA@Home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/SLinCA@Home
date_saved: 2026-05-05T10:13:51.082867+00:00
instance: kb-cron
parent: slinca-home-20260505-0
summary:
SLinCA@Home (Scaling Laws in Cluster Aggregation) was a research project that uses Internet-connected computers to do research in fields such as physics and materials science. == Introduction == SLinCA@Home was based at the G. V. Kurdyumov Institute for Metal Physics (IMP) of the National Academy of Sciences of Ukraine (NASU) in Kyiv, Ukraine's capital city. It ran on the Berkeley Open Infrastructure for Network Computing (BOINC) software platform, the SZTAKI Desktop Grid platform, and the Distributed Computing API (DC-API) by SZTAKI. SLinCA@Home hosts several scientific applications dedicated to research into scale-invariant dependencies in experimental data in physics and materials science. Statistics at the BOINCstats site (as of 16 March 2011), show over 2,000 volunteers in 39 countries have participated in the project; it is the second most popular BOINC project in Ukraine (after the Magnetism@Home project, which is now inactive). About 700 active users contribute about 0.5–1.5 teraFLOPS of computational power, which would rank SLinCA@Home among the top 20 on the TOP500 list of supercomputers in June 2005. == History == The SLinCA@Home project was previously launched in January 2009 as part of the EGEE project in the European Union's Seventh Framework Programme (FP7) for the funding of research and


id: spacy-20260505-0
file: data/en.wikipedia.org/wiki/SpaCy-0.md
category: reference
title: SpaCy
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/SpaCy
date_saved: 2026-05-05T10:13:52.274523+00:00
instance: kb-cron
parent: spacy-20260505-0
summary:
spaCy ( spay-SEE) is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython. The library is published under the MIT license and its main developers are Matthew Honnibal and Ines Montani, the founders of the software company Explosion. Unlike NLTK, which is widely used for teaching and research, spaCy focuses on providing software for production usage. spaCy also supports deep learning workflows that allow connecting statistical models trained by popular machine learning libraries like TensorFlow, PyTorch or MXNet through its own machine learning library Thinc. Using Thinc as its backend, spaCy features convolutional neural network models for part-of-speech tagging, dependency parsing, text categorization and named entity recognition (NER). Prebuilt statistical neural network models to perform these tasks are available for 23 languages, including English, Portuguese, Spanish, Russian and Chinese, and there is also a multi-language NER model. Additional support for tokenization for more than 65 languages allows users to train custom models on their own datasets as well. == History == Version 1.0 was released on October 19, 2016, and included preliminary support for deep learning workflows by supporting custom processing pipelines. It further included a rule matcher that supported entity annotations,


id: spatiotemporal-epidemiological-modeler-20260505-0
file: data/en.wikipedia.org/wiki/Spatiotemporal_Epidemiological_Modeler-0.md
category: reference
title: Spatiotemporal Epidemiological Modeler
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Spatiotemporal_Epidemiological_Modeler
date_saved: 2026-05-05T10:13:53.464871+00:00
instance: kb-cron
parent: spatiotemporal-epidemiological-modeler-20260505-0
summary:
The Spatiotemporal Epidemiological Modeler (STEM) is free software available through the Eclipse Foundation. Originally developed by IBM Research, STEM is a framework and development tool designed to help scientists create and use spatial and temporal models of infectious disease. STEM uses a component software architecture based on the OSGi standard. The Eclipse Equinox platform is a reference implementation of that standard. By using a component software architecture, all of the components or elements required for a disease model, including the code and the data are available as software building blocks that can be independently exchanged, extended, reused, or replaced. These building blocks or plug-ins are called eclipse "plug-ins" or "extensions". STEM plug-ins contain denominator data for administrative regions of interest. The regions are indexed by standard (ISO3166) codes. STEM currently includes a large number of plug-ins for the 244 countries and dependent areas defined by the Geographic Coding Standard maintained by the International Organization for Standardization. These plug-ins contain global data including geographic data, population data, demographics, and basic models of disease. The disease models distributed with STEM include epidemiological compartment models. Other plug-ins describe relationships between regions including nearest-neighbor or adjacency relationships as well as information about transportation, such


id: spinhenge-home-20260505-0
file: data/en.wikipedia.org/wiki/Spinhenge@Home-0.md
category: reference
title: Spinhenge@Home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Spinhenge@Home
date_saved: 2026-05-05T10:13:54.660926+00:00
instance: kb-cron
parent: spinhenge-home-20260505-0
summary:
Spinhenge@home was a volunteer computing project on the BOINC platform, which performs extensive numerical simulations concerning the physical characteristics of magnetic molecules. It is a project of the Bielefeld University of Applied Sciences, Department of Electrical Engineering and Computer Science, in cooperation with the University of Osnabrück and Ames Laboratory. The project began beta testing on September 1, 2006, and used the Metropolis Monte Carlo algorithm to calculate and simulate spin dynamics in nanoscale molecular magnets. On September 28, 2011, a hiatus was announced while the project team reviewed results and upgraded hardware. As of July 10, 2022 the hiatus continues and it is likely that the project has been closed down permanently. == See also == Spintronics BOINC List of volunteer computing projects == References == == External links == Project Website Spinhenge@home screensaver video on YouTube More Information about Spinhenge@Home Project Statistics at BOINCStats


id: spyder-software-20260505-0
file: data/en.wikipedia.org/wiki/Spyder_(software)-0.md
category: reference
title: Spyder (software)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Spyder_(software)
date_saved: 2026-05-05T10:13:55.867629+00:00
instance: kb-cron
parent: spyder-software-20260505-0
summary:
Spyder is an open-source cross-platform integrated development environment (IDE) for scientific programming in the Python language. Spyder integrates with a number of prominent packages in the scientific Python stack, as well as other open-source software. Created by Pierre Raybaut and released in 2009 under the MIT license, since 2012 Spyder has been maintained and continuously improved by Python developers and the community. Spyder is extensible with first-party and third-party plugins, and includes support for interactive tools for data inspection and embeds Python-specific code quality assurance and introspection instruments, such as Pyflakes, Pylint and Rope. Spyder uses Qt for its GUI and is designed to use either of the PyQt or PySide Python bindings. QtPy, a thin abstraction layer developed by the Spyder project and later adopted by multiple other packages, provides the flexibility to use either backend. == History == Initially created and developed by Pierre Raybaut, it was published on October 18, 2009 under the MIT license. Since 2012 Spyder has been maintained and continuously improved by a team of scientific Python developers and the community. As of 2024, the Spyder website lists the Chan Zuckerberg Initiative and NumFOCUS as their two major sponsors, also noting donations received from


id: su2-code-20260505-0
file: data/en.wikipedia.org/wiki/SU2_code-0.md
category: reference
title: SU2 code
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/SU2_code
date_saved: 2026-05-05T10:13:57.043776+00:00
instance: kb-cron
parent: su2-code-20260505-0
summary:
SU2 (formerly Stanford University Unstructured) is a suite of open-source software tools written in C++ and Python for the numerical solution of partial differential equations (PDE) and performing PDE-constrained optimization. While initially developed for aerodynamics and compressible flow, it has evolved into a general-purpose multiphysics framework capable of simulating incompressible and compressible flows across all Mach regimes, species transport, conjugate heat transfer and combustion. The framework is specialized for gradient-based design optimization using integrated continuous and discrete adjoint solvers. A distinguishing feature for researchers is its use of algorithmic differentiation (AD) to provide exact discrete adjoint sensitivities for complex multiphysics chains, including fluid-structure interaction (FSI) and conjugate heat transfer. It supports unstructured meshes and offers extensibility through User Defined Functions (UDFs) and high-level Python wrappers. To stimulate development and use of the software, the SU2 Foundation was established as a non-profit organization to coordinate the global community of users and developers. SU2 is released under the GNU Lesser General Public License (LGPL) version 2.1. == Developers == SU2 is being developed by individuals and organized teams around the world. The original SU2 Lead Developers are: Dr. Francisco Palacios and Dr. Thomas D. Economon. The most active groups developing SU2 are:


id: tanagra-machine-learning-20260505-0
file: data/en.wikipedia.org/wiki/Tanagra_(machine_learning)-0.md
category: reference
title: Tanagra (machine learning)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Tanagra_(machine_learning)
date_saved: 2026-05-05T10:13:58.200299+00:00
instance: kb-cron
parent: tanagra-machine-learning-20260505-0
summary:
Tanagra is a free suite of machine learning software for research and academic purposes developed by Ricco Rakotomalala at the Lumière University Lyon 2, France. Tanagra supports several standard data mining tasks such as: Visualization, Descriptive statistics, Instance selection, feature selection, feature construction, regression, factor analysis, clustering, classification and association rule learning. Tanagra is an academic project. It is widely used in French-speaking universities. Tanagra is frequently used in real studies and in software comparison papers. == History == The development of Tanagra was started in June 2003. The first version was distributed in December 2003. Tanagra is the successor of Sipina, another free data mining tool which is intended only for supervised learning tasks (classification), especially the interactive and visual construction of decision trees. Sipina is still available online and is maintained. Tanagra is an "open source project" as every researcher can access the source code and add their own algorithms, as long as they agree and conform to the software distribution license. The main purpose of the Tanagra project is to give researchers and students a user-friendly data mining software, conforming to the present norms of the software development in this domain (especially in the design of its


id: theano-software-20260505-0
file: data/en.wikipedia.org/wiki/Theano_(software)-0.md
category: reference
title: Theano (software)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Theano_(software)
date_saved: 2026-05-05T10:14:00.110578+00:00
instance: kb-cron
parent: theano-software-20260505-0
summary:
Theano is a Python library and optimizing compiler for manipulating and evaluating mathematical expressions, especially matrix-valued ones. In Theano, computations are expressed using a NumPy-esque syntax and compiled to run efficiently on either CPU or GPU architectures. == History == Theano is an open source project primarily developed by the Montreal Institute for Learning Algorithms (MILA) at the Université de Montréal. The name of the software references the ancient philosopher Theano, long associated with the development of the golden mean. On 28 September 2017, Pascal Lamblin posted a message from Yoshua Bengio, Head of MILA: major development would cease after the 1.0 release due to competing offerings by strong industrial players. Theano 1.0.0 was then released on 15 November 2017. On 17 May 2018, Chris Fonnesbeck wrote on behalf of the PyMC development team that the PyMC developers will officially assume control of Theano maintenance once the MILA development team steps down. On 29 January 2021, they started using the name Aesara for their fork of Theano. On 29 Nov 2022, the PyMC development team announced that the PyMC developers will fork the Aesara project under the name PyTensor. == Sample code == The following code is the original Theano's


id: theskynet-20260505-0
file: data/en.wikipedia.org/wiki/TheSkyNet-0.md
category: reference
title: TheSkyNet
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/TheSkyNet
date_saved: 2026-05-05T10:14:01.318409+00:00
instance: kb-cron
parent: theskynet-20260505-0
summary:
theSkyNet was a research project that used volunteer Internet-connected computers to carry out research in astronomy. It was an initiative of the International Centre for Radio Astronomy Research (ICRAR), a joint venture of Curtin University and the University of Western Australia. theSkyNet had two projects, Sourcefinder and POGS. Both projects have been completed. theSkyNet Sourcefinder aimed to test and refine automatic radio sourcefinding algorithms in preparation for radio galaxy surveys using the Australian Square Kilometre Array Pathfinder and the Square Kilometre Array. theSkyNet POGS used Spectral Energy Distribution fitting to calculate characteristics of many galaxies using images taken by the Pan-STARRS PS1 optical telescope in Hawaii. == History == theSkyNet Sourcefinder project was introduced publicly on 13 September 2011, operating on a Java-based user platform, processing data using new distributed computing software called Nereus. One year later, theSkyNet celebrated its first birthday and at the same time theSkyNet POGS project became the first public Australian based project to participate in the well established volunteer computing platform BOINC. The acronym POGS is a reference to a game played with discs that originated on Maui, Hawaii, in the 1920s, and the fact that the Pan-STARRS PS1 telescope, is situated on Mount Haleakala,


id: tomopy-20260505-0
file: data/en.wikipedia.org/wiki/TomoPy-0.md
category: reference
title: TomoPy
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/TomoPy
date_saved: 2026-05-05T10:14:02.467149+00:00
instance: kb-cron
parent: tomopy-20260505-0
summary:
TomoPy is an open-sourced Python toolbox to perform tomographic data processing and image reconstruction. == Overview == Tomographic reconstruction creates three-dimensional views of an object by combining two-dimensional images taken from multiple directions, for example in how a computer-aided tomography scanner allows 3D views of the heart or brain. Data collection can be rapid, but the required computations are massive. Further, many common experimental perturbations can degrade the quality of tomographs, unless corrections are applied. Unless automated tools make these corrections, beamline staff can be overwhelmed by data that can be collected far faster than corrections and reconstruction can be performed. To address the needs for image correction and tomographic reconstruction in an instrument independent manner, the TomoPy code was developed, which is a parallelizable high performance tomography library. == References ==


id: trans-proteomic-pipeline-20260505-0
file: data/en.wikipedia.org/wiki/Trans-Proteomic_Pipeline-0.md
category: reference
title: Trans-Proteomic Pipeline
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Trans-Proteomic_Pipeline
date_saved: 2026-05-05T10:14:04.020283+00:00
instance: kb-cron
parent: trans-proteomic-pipeline-20260505-0
summary:
The Trans-Proteomic Pipeline (TPP) is an open-source data analysis software for proteomics developed at the Institute for Systems Biology (ISB) by the Ruedi Aebersold group under the Seattle Proteome Center. The TPP includes PeptideProphet, ProteinProphet, ASAPRatio, XPRESS and Libra. == Software Components == === Probability Assignment and Validation === PeptideProphet performs statistical validation of peptide-spectra-matches (PSM) using the results of search engines by estimating a false discovery rate (FDR) on PSM level. The initial PeptideProphet used a fit of a Gaussian distribution for the correct identifications and a fit of a gamma distribution for the incorrect identification. A later modification of the program allowed the usage of a target-decoy approach, using either a variable component mixture model or a semi-parametric mixture model. In the PeptideProphet, specifying a decoy tag will use the variable component mixture model while selecting a non-parametric model will use the semi-parametric mixture model. ProteinProphet identifies proteins based on the results of PeptideProphet. Mayu performs statistical validation of protein identification by estimating a false discovery rate (FDR) on protein level. === Spectral library handling === The SpectraST tool is able to generate spectral libraries and search datasets using these libraries. == See also == OpenMS ProteoWizard Mass


id: ugene-20260505-0
file: data/en.wikipedia.org/wiki/UGENE-0.md
category: reference
title: UGENE
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/UGENE
date_saved: 2026-05-05T10:14:05.861173+00:00
instance: kb-cron
parent: ugene-20260505-0
summary:
UGENE is computer software for bioinformatics. It helps biologists to analyze various biological genetics data, such as sequences, annotations, multiple alignments, phylogenetic trees, NGS assemblies, and others. UGENE integrates dozens of well-known biological tools, algorithms, and original tools in the context of genomics, evolutionary biology, virology, and other branches of life science. UGENE works on personal computer operating systems such as Windows, macOS, or Linux. It is released as free and open-source software, under a GNU General Public License (GPL) version 2. The data can be stored both locally and on shared/networked storage. The graphical user interface (GUI) provides access to pre-built tools so users with no computer programming experience can access those tools easily. UGENE also has a command-line interface to execute Workflows. Using UGENE Workflow Designer, it is possible to streamline a multi-step analysis. The workflow consists of blocks such as data readers, blocks executing embedded tools and algorithms, and data writers. Blocks can be created with command line tools or a script. A set of sample workflows is available in the Workflow Designer, to annotate sequences, convert data formats, analyze NGS data, etc. To improve performance, UGENE uses multi-core processors (CPUs) and graphics processing units (GPUs) to


id: vcell-20260505-0
file: data/en.wikipedia.org/wiki/VCell-0.md
category: reference
title: VCell
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/VCell
date_saved: 2026-05-05T10:14:07.768630+00:00
instance: kb-cron
parent: vcell-20260505-0
summary:
VCell (Virtual Cell) is an open-source software platform for modeling and simulation of living organisms, primarily cells. It has been designed to be a tool for a wide range of scientists, from experimental cell biologists to theoretical biophysicists. == Concept == VCell is an advanced software platform for modeling and simulating reaction kinetics, membrane transport and diffusion in the complex geometries of cells and multicellular tissues. VCell models have a hierarchical tree structure. The trunk level is the "Physiology" consisting of compartments, species and chemical reactions, and reaction rates that are functions of concentrations. Given initial concentrations of species, VCell can calculate how these concentrations change over time. How these numerical simulations are performed, is determined through a number of "Applications", which specify whether simulations will be deterministic or stochastic, and spatial or compartmental; multiple "Applications" can also specify initial concentrations, diffusion coefficients, flow rates and a variety of modeling assumptions. Thus "Applications" can be viewed as computational experiments to test ideas about the physiological system. Each "Application" corresponds to a mathematical description, which is automatically translated into the VCell Math Description Language. Multiple "Simulations", including parameter scans and changes in solver specifications, can be run within each "Application". Models


id: vtk-20260505-0
file: data/en.wikipedia.org/wiki/VTK-0.md
category: reference
title: VTK
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/VTK
date_saved: 2026-05-05T10:14:08.973454+00:00
instance: kb-cron
parent: vtk-20260505-0
summary:
The Visualization Toolkit (VTK) is a free software system for 3D computer graphics, image processing and scientific visualization. VTK is distributed under the GNU-approved and FSF-approved BSD 3-clause License. == Functionality == VTK consists of a C++ class library and several interpreted interface layers including Tcl/Tk, Java, and Python. The toolkit is created and supported by the Kitware team. VTK supports various visualization algorithms including: scalar, vector, tensor, texture, and volumetric methods; and advanced modeling techniques such as: implicit modeling, polygon reduction, mesh smoothing, cutting, contouring, and Delaunay triangulation. VTK has an information visualization framework, has a suite of 3D interaction widgets, supports parallel processing, and integrates with various databases and GUI toolkits such as Qt and Tk. VTK is cross-platform and runs on Linux, Windows, Mac and Unix platforms. The core of VTK is implemented as a C++ toolkit, requiring users to build applications by combining various objects into an application. The system also supports automated wrapping of the C++ core into Python, Java and Tcl, so that VTK applications may also be written using these programming languages. == History == VTK was initially created in 1993 as companion software to the book The Visualization Toolkit: An Object-Oriented Approach


id: waffles-machine-learning-20260505-0
file: data/en.wikipedia.org/wiki/Waffles_(machine_learning)-0.md
category: reference
title: Waffles (machine learning)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Waffles_(machine_learning)
date_saved: 2026-05-05T10:14:10.119311+00:00
instance: kb-cron
parent: waffles-machine-learning-20260505-0
summary:
Waffles is a collection of command-line tools for performing machine learning operations developed at Brigham Young University. These tools are written in C++, and are available under the GNU Lesser General Public License. == Description == The Waffles machine learning toolkit contains command-line tools for performing various operations related to machine learning, data mining, and predictive modeling. The primary focus of Waffles is to provide tools that are simple to use in scripted experiments or processes. For example, the supervised learning algorithms included in Waffles are all designed to support multi-dimensional labels, classification and regression, automatically impute missing values, and automatically apply necessary filters to transform the data to a type that the algorithm can support, such that arbitrary learning algorithms can be used with arbitrary data sets. Many other machine learning toolkits provide similar functionality, but require the user to explicitly configure data filters and transformations to make it compatible with a particular learning algorithm. The algorithms provided in Waffles also have the ability to automatically tune their own parameters (with the cost of additional computational overhead). Because Waffles is designed for script-ability, it deliberately avoids presenting its tools in a graphical environment. It does, however, include a graphical


id: weka-software-20260505-0
file: data/en.wikipedia.org/wiki/Weka_(software)-0.md
category: reference
title: Weka (software)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Weka_(software)
date_saved: 2026-05-05T10:14:11.287524+00:00
instance: kb-cron
parent: weka-software-20260505-0
summary:
Waikato Environment for Knowledge Analysis (Weka) is a collection of machine learning and data analysis free software licensed under the GNU General Public License. It was developed at the University of Waikato, New Zealand and is the companion software to the book "Data Mining: Practical Machine Learning Tools and Techniques". == Description == Weka contains a collection of visualization tools and algorithms for data analysis and predictive modeling, together with graphical user interfaces for easy access to these functions. The original non-Java version of Weka was a Tcl/Tk front-end to (mostly third-party) modeling algorithms implemented in other programming languages, plus data preprocessing utilities in C, and a makefile-based system for running machine learning experiments. This original version was primarily designed as a tool for analyzing data from agricultural domains, but the more recent fully Java-based version (Weka 3), for which development started in 1997, is now used in many different application areas, in particular for educational purposes and research. Advantages of Weka include: Free availability under the GNU General Public License. Portability, since it is fully implemented in the Java programming language and thus runs on almost any modern computing platform. A comprehensive collection of data preprocessing and modeling techniques.


id: word2vec-20260505-0
file: data/en.wikipedia.org/wiki/Word2vec-0.md
category: reference
title: Word2vec
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Word2vec
date_saved: 2026-05-05T10:14:12.458984+00:00
instance: kb-cron
parent: word2vec-20260505-0
summary:
Word2vec is a technique in natural language processing for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus. Once trained, such a model can detect synonymous words or suggest additional words for a partial sentence. Word2vec was developed by Tomáš Mikolov, Kai Chen, Greg Corrado, Ilya Sutskever and Jeff Dean at Google, and published in 2013. Word2vec represents a word as a high-dimension vector of numbers which capture relationships between words. In particular, words which appear in similar contexts are mapped to vectors which are nearby as measured by cosine similarity. This indicates the level of semantic similarity between the words, so for example the vectors for walk and ran are nearby, as are those for "but" and "however", and "Berlin" and "Germany". == Approach == Word2vec is a group of related models that are used to produce word embeddings. These models are shallow, two-layer neural networks that are trained to reconstruct linguistic contexts of words. Word2vec takes as its input a large corpus of text and produces a mapping of the set of words to


id: word2vec-20260505-1
file: data/en.wikipedia.org/wiki/Word2vec-1.md
category: reference
title: Word2vec
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Word2vec
date_saved: 2026-05-05T10:14:12.458984+00:00
instance: kb-cron
parent: word2vec-20260505-0
summary:
The idea of CBOW is to represent each word with a vector, such that it is possible to predict a word using the sum of the vectors of its neighbors. Specifically, for each word w i {\displaystyle w_{i}} in the corpus, the one-hot encoding of the word is used as the input to the neural network. The output of the neural network is a probability distribution over the dictionary, representing a prediction of individual words in the neighborhood of w i {\displaystyle w_{i}} . The objective of training is to maximize ∑ i ln ⁡ Pr ( w i ∣ w i + j : j ∈ N ) {\displaystyle \sum _{i}\ln \Pr(w_{i}\mid w_{i+j}\colon j\in N)} where N {\displaystyle N} is a set of (non-zero) indices representing the relative locations of nearby words considered to be in w i {\displaystyle w_{i}} 's neighborhood. For example, if we want each word in the corpus to be predicted by every other word in a small span of 4 words. The set of relative indexes of neighbor words will be: N = { − 2 , − 1 , + 1 , + 2 } {\displaystyle N=\{-2,-1,+1,+2\}} , and the objective is to


id: word2vec-20260505-2
file: data/en.wikipedia.org/wiki/Word2vec-2.md
category: reference
title: Word2vec
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Word2vec
date_saved: 2026-05-05T10:14:12.458984+00:00
instance: kb-cron
parent: word2vec-20260505-0
summary:
== History == During the 1980s, there were some early attempts at using neural networks to represent words and concepts as vectors. In 2010, Tomáš Mikolov (then at Brno University of Technology) with co-authors applied a simple recurrent neural network with a single hidden layer to language modelling. Word2vec was created, patented, and published in 2013 by a team of researchers led by Mikolov at Google over two papers. The original paper was rejected by reviewers for ICLR conference 2013. It also took months for the code to be approved for open-sourcing. Other researchers helped analyse and explain the algorithm. Embedding vectors created using the Word2vec algorithm have some advantages compared to earlier algorithms such as those using n-grams and latent semantic analysis. GloVe was developed by a team at Stanford specifically as a competitor, and the original paper noted multiple improvements of GloVe over word2vec. Mikolov argued that the comparison was unfair as GloVe was trained on more data, and that the fastText project showed that word2vec is superior when trained on the same data. As of 2022, the straight Word2vec approach was described as "dated". Transformer-based models, such as ELMo and BERT, which add multiple neural-network attention layers


id: word2vec-20260505-3
file: data/en.wikipedia.org/wiki/Word2vec-3.md
category: reference
title: Word2vec
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Word2vec
date_saved: 2026-05-05T10:14:12.458984+00:00
instance: kb-cron
parent: word2vec-20260505-0
summary:
=== Radiology and intelligent word embeddings (IWE) === An extension of word vectors for creating a dense vector representation of unstructured radiology reports has been proposed by Banerjee et al. One of the biggest challenges with Word2vec is how to handle unknown or out-of-vocabulary (OOV) words and morphologically similar words. If the Word2vec model has not encountered a particular word before, it will be forced to use a random vector, which is generally far from its ideal representation. This can particularly be an issue in domains like medicine where synonyms and related words can be used depending on the preferred style of radiologist, and words may have been used infrequently in a large corpus. IWE combines Word2vec with a semantic dictionary mapping technique to tackle the major challenges of information extraction from clinical texts, which include ambiguity of free text narrative style, lexical variations, use of ungrammatical and telegraphic phases, arbitrary ordering of words, and frequent appearance of abbreviations and acronyms. Of particular interest, the IWE model (trained on the one institutional dataset) successfully translated to a different institutional dataset which demonstrates good generalizability of the approach across institutions. == Analysis == The reasons for successful word embedding learning in


id: world-community-grid-20260505-0
file: data/en.wikipedia.org/wiki/World_Community_Grid-0.md
category: reference
title: World Community Grid
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/World_Community_Grid
date_saved: 2026-05-05T10:14:13.754375+00:00
instance: kb-cron
parent: world-community-grid-20260505-0
summary:
World Community Grid (WCG) is an effort to create the world's largest volunteer computing platform to perform scientific research that benefits humanity. Launched on November 16, 2004, with proprietary Grid MP client from United Devices and adding support for Berkeley Open Infrastructure for Network Computing (BOINC) in 2005, World Community Grid eventually discontinued the Grid MP client and consolidated on the BOINC platform in 2008. In September 2021, it was announced that IBM transferred ownership to the Krembil Research Institute of University Health Network in Toronto, Ontario. World Community Grid uses unused processing power of consumer devices (PCs, Laptops, Android Smartphones, etc.) to analyse data created by the research groups that participate in the grid. WCG projects have analysed data related to the human genome, the human microbiome, HIV, dengue, muscular dystrophy, cancer, influenza, Ebola, Zika virus, virtual screening, rice crop yields, clean energy, water purification and COVID-19, among other research areas. There are currently four active projects and 28 completed projects. Several of these projects have published peer-reviewed papers based on the analysis of the data generated by WCG. These include an OpenZika project paper on the discovery of a compound (FAM 3) that inhibits the NS3 Helicase protein


id: world-community-grid-20260505-1
file: data/en.wikipedia.org/wiki/World_Community_Grid-1.md
category: reference
title: World Community Grid
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/World_Community_Grid
date_saved: 2026-05-05T10:14:13.754375+00:00
instance: kb-cron
parent: world-community-grid-20260505-0
summary:
== Statistics and competition == The contributions of each user are recorded and user contribution statistics are publicly available. Due to the fact that the processing time of each workunit varies from computer to computer, depending on the difficulty of the workunit, the speed of the computer, and the amount of idle resources available, contributions are usually measured in terms of points. Points are awarded for each workunit depending on the effort required to process it. Upon completing a workunit, the BOINC client will request the number of points it thinks it deserves based on software benchmarks (see BOINC Credit System#Cobblestones). Since multiple computers process the same workunit to ensure accuracy, the World Community Grid servers can look at the points claimed by each of those computers. The WCG servers disregard statistical outliers, average the remaining values and award the resulting number of points to each computer. Within the grid, users may join teams that have been created by organizations, groups, or individuals. Teams allow for a heightened sense of community identity and can also inspire competition. As teams compete against each other, more work is done for the grid overall. == Outreach == World Community Grid recognizes companies and


id: world-community-grid-20260505-2
file: data/en.wikipedia.org/wiki/World_Community_Grid-2.md
category: reference
title: World Community Grid
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/World_Community_Grid
date_saved: 2026-05-05T10:14:13.754375+00:00
instance: kb-cron
parent: world-community-grid-20260505-0
summary:
In February 2014, the Help Fight Childhood Cancer project scientists announced the discovery of 7 compounds that destroy neuroblastoma cancer cells without any apparent side effects. This discovery, made with the support of the WCG volunteers, is a positive step towards a new treatment. The project has announced that it is seeking a collaboration with a pharmaceutical company in order to develop the compounds into treatments. Given the success of the project, the scientists have stated that they are already planning a follow-up project which will focus on other pediatric cancers, possibly in collaboration with a newly formed Pan-Asian oncology group, of which they are a founding member. As of July 2012, the Human Proteome Folding Project has published several papers using data from WCG. These include a paper on validation methods and a new database of protein structure and function predictions; a paper on the identification of proteins that regulate human processes; a paper on the analysis of the genomes from five plant families and their proteomes, for which WCG was used in the creation of over 29,000 protein structures; a paper on the proteome of Saccharomyces cerevisiae. The GO Fight Against Malaria project reported the discovery of several


id: world-community-grid-20260505-3
file: data/en.wikipedia.org/wiki/World_Community_Grid-3.md
category: reference
title: World Community Grid
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/World_Community_Grid
date_saved: 2026-05-05T10:14:13.754375+00:00
instance: kb-cron
parent: world-community-grid-20260505-0
summary:
=== OpenPandemics - COVID-19 === On April 1, 2020, IBM announced OpenPandemics - COVID-19. The project aims to identify possible treatments for the Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which is responsible for the COVID-19 pandemic. WCG will partner with Scripps Research, with whom it has partnered in the past, notably in FightAIDS@Home projects. The project runs on CPUs and GPUs and will also serve to create a "fast-response, open source tool that will help all scientists quickly search for treatments for future pandemics." The project launched on May 14, 2020. === Mapping Cancer Markers === Mapping Cancer Markers (launched November 8, 2013). The project aims to identify the markers associated with various types of cancer, and is analyzing millions of data points collected from thousands of healthy and cancerous patient tissue samples. These include tissues with lung, ovarian, prostate, pancreatic and breast cancers. By comparing these different data points, researchers aim to identify patterns of markers for different cancers and correlate them with different outcomes, including responsiveness to various treatment options. The project is focusing on 4 types of cancer, with the first focus being on lung cancer, and will move on to ovarian cancer, prostate cancer and


id: world-community-grid-20260505-4
file: data/en.wikipedia.org/wiki/World_Community_Grid-4.md
category: reference
title: World Community Grid
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/World_Community_Grid
date_saved: 2026-05-05T10:14:13.754375+00:00
instance: kb-cron
parent: world-community-grid-20260505-0
summary:
=== AfricanClimate@Home === The mission of AfricanClimate@Home was to develop more accurate climate models of specific regions in Africa. It was intended to serve as a basis for understanding how the climate will change in the future so that measures designed to alleviate the adverse effects of climate change could be implemented. World Community Grid's tremendous computing power was used to understand and reduce the uncertainty with which climate processes were simulated over Africa. Phase 1 of African Climate@Home launched on September 3, 2007, and ended in July 2008. === Help Conquer Cancer === Help Conquer Cancer project (launched November 1, 2007) is sponsored by the Ontario Cancer Institute (OCI), Princess Margaret Hospital and University Health Network of Toronto, Canada. The project involves X-ray crystallography. The mission of Help Conquer Cancer is to improve the results of protein X-ray crystallography, which helps researchers not only annotate unknown parts of the human proteome, but importantly improves their understanding of cancer initiation, progression and treatment. The HCC project was the first WCG project benefiting from graphics processing units (GPU)s which helped finish it a lot earlier than initially projected due to the massive power of GPUs. In the April 2013 status report


id: world-community-grid-20260505-5
file: data/en.wikipedia.org/wiki/World_Community_Grid-5.md
category: reference
title: World Community Grid
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/World_Community_Grid
date_saved: 2026-05-05T10:14:13.754375+00:00
instance: kb-cron
parent: world-community-grid-20260505-0
summary:
World Community Grid and researchers supported by Decrypthon, a partnership between AFM (French Muscular Dystrophy Association), CNRS (French National Center for Scientific Research), Universite Pierre et Marie Curie, and IBM were investigating protein–protein interactions for more than 2,200 proteins whose structures are known, with particular focus on those proteins that play a role in neuromuscular diseases. Phase 2 was launched on May 12, 2009, and completed on September 26, 2012. The database of information produced will help researchers design molecules to inhibit or enhance binding of particular macromolecules, hopefully leading to better treatments for muscular dystrophy and other neuromuscular diseases. Phase 2 of the Help Cure Muscular Dystrophy project began once the results from the first phase had been analyzed. Phase 2 ran on the BOINC platform. === Discovering Dengue Drugs – Together – Phase 2 === Discovering Dengue Drugs – Together – Phase 2 (launched February 17, 2010) is sponsored by The University of Texas Medical Branch (UTMB) in Galveston, Texas, United States and the University of Chicago in Illinois, USA. The mission is to identify promising drug candidates to combat the Dengue, Hepatitis C, West Nile, Yellow Fever, and other related viruses. The extensive computing power of World


id: world-community-grid-20260505-6
file: data/en.wikipedia.org/wiki/World_Community_Grid-6.md
category: reference
title: World Community Grid
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/World_Community_Grid
date_saved: 2026-05-05T10:14:13.754375+00:00
instance: kb-cron
parent: world-community-grid-20260505-0
summary:
FightAIDS@Home (launched November 19, 2005) was World Community Grid's second project and its first to target a single disease. Each individual computer processes one potential drug molecule and tests how well it would dock with HIV protease, acting as a protease inhibitor. Scripps Research Institute published its first peer-reviewed scientific paper about the results of FightAIDS@Home on April 21, 2007. This paper explains that the results up to that point will primarily be used to improve the efficiency of future FightAIDS@Home calculations. === FightAIDS@Home Phase 2 === FightAIDS@Home Phase 2 (launched September 30, 2015) is looking more closely at the results of Phase 1. The project has two goals in the early experiments; the simulation architecture is functioning correctly and giving reliable results, and using BEDAM and AutoDock together provides better results than using just BEDAM or AutoDock. === Microbiome Immunity Project === Microbiome Immunity Project (launched August 2017) is a study of proteins in bacteria located in and on the human body; the human microbiome, which comprises around 3 million separate bacterial genes. By studying bacterial genes, researchers can determine their individual shapes, which in turn dictate the function of the bacteria. Collaborative institutions includes the University of California


id: xdrawchem-20260505-0
file: data/en.wikipedia.org/wiki/XDrawChem-0.md
category: reference
title: XDrawChem
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/XDrawChem
date_saved: 2026-05-05T10:14:29.287450+00:00
instance: kb-cron
parent: xdrawchem-20260505-0
summary:
XDrawChem is a free software program for drawing chemical structural formulas, available for Unix and macOS. It is distributed under the GNU GPL. In Microsoft Windows this program is called WinDrawChem. == Major features == Fixed length and fixed angle drawing Automatic alignment of figures Detection of structures, text, and arrows, and their automatic placement Can automatically draw rings and other structures - has all standard amino acids and nucleic acids in a built-in library Retrieval of structures from a network database based on CAS number, formula, or name Retrieval of information on a molecule based on a drawing Symbols such as partial charge and radicals Reading MDL Molfiles, CML (Chemical Markup Language), ChemDraw binary format, ChemDraw XML text format Writing MDL Molfiles, CML, ChemDraw XML text format Integration with OpenBabel, allowing XDrawChem to read and write over 20 different chemical file formats. Image export in Portable Network Graphics (PNG), Windows bitmap, Encapsulated PostScript (EPS), and Scalable Vector Graphics (SVG) 3D structure generation with the help of the external program BUILD3D Simple spectra predictions, including 13C-NMR, 1H-NMR (based on additive rules and functional group lookup methods), and IR Simple property estimation, including pKa, octanol-water partition coefficient, and gas-phase enthalpy change.


id: xmd-20260505-0
file: data/en.wikipedia.org/wiki/XMD-0.md
category: reference
title: XMD
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/XMD
date_saved: 2026-05-05T10:14:30.458640+00:00
instance: kb-cron
parent: xmd-20260505-0
summary:
XMD is a classical molecular dynamics software designed to simulate problems related to materials science. The code was developed by Jon Rifkin of University of Connecticut and is being distributed under GNU General Public License. Source code is available in C and can be compiled using POSIX thread functions to take advantage of multi-CPU computers. == See also == Molecular design software == External links == XMD Homepage


id: xplanet-20260505-0
file: data/en.wikipedia.org/wiki/Xplanet-0.md
category: reference
title: Xplanet
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Xplanet
date_saved: 2026-05-05T10:14:31.609791+00:00
instance: kb-cron
parent: xplanet-20260505-0
summary:
Xplanet is a renderer for planetary and Solar System images, capable of producing various types of graphics depicting the Solar System. It is normally used to create computer wallpapers, which may be updated with the latest cloud maps or the regions of Earth which are in sunlight. Xplanet is free software released under the GNU GPL. == Flat maps == Xplanet can be used to produce projected maps of any planet (but typically Earth), for example Mollweide projections which show the whole Earth at once, or Mercator projections with a rectangular appearance suitable for filling the screen. It is possible to overlay clouds or text (such as the location of recent events) onto these maps; a popular option is shading areas currently experiencing night. == Planetary images == Xplanet can also be used to render more general views of objects in the Solar System, such as a view of the Earth from the Moon. In more recent versions, Xplanet depicts eclipses, and some of its images show Jupiter's moons casting an eclipse onto the planet. == Technical == Xplanet runs on Linux, Mac OS X and other Unix operating systems and also on Microsoft Windows, and was derived from an


id: yooreeka-20260505-0
file: data/en.wikipedia.org/wiki/Yooreeka-0.md
category: reference
title: Yooreeka
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Yooreeka
date_saved: 2026-05-05T10:14:32.751714+00:00
instance: kb-cron
parent: yooreeka-20260505-0
summary:
Yooreeka is a library for data mining, machine learning, soft computing, and mathematical analysis. The project started with the code of the book "Algorithms of the Intelligent Web". Although the term "Web" prevailed in the title, in essence, the algorithms are valuable in any software application. It covers all major algorithms and provides many examples. Yooreeka 2.x is licensed under the Apache License rather than the somewhat more restrictive LGPL (which was the license of v1.x). The library is written 100% in the Java language. == Algorithms == The following algorithms are covered: Clustering Hierarchical—Agglomerative (e.g. MST single link; ROCK) and Divisive Partitional (e.g. k-means) Classification Bayesian Decision trees Neural Networks Rule based (via Drools) Recommendations Collaborative filtering Content based Search PageRank DocRank Personalization == References == == External links == Baynoo Website Yooreeka on GitHub Yooreeka on Google Code (old repository)


id: ufluids-home-20260505-0
file: data/en.wikipedia.org/wiki/UFluids@Home-0.md
category: reference
title: UFluids@Home
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/UFluids@Home
date_saved: 2026-05-05T10:14:33.980869+00:00
instance: kb-cron
parent: ufluids-home-20260505-0
summary:
μFluids@Home is a computer simulation of two-phase flow behavior in microgravity and microfluidics problems at Purdue University, using the Surface Evolver program. == About == The project's purpose is to develop better methods for the management of liquid rocket propellants in microgravity, and to investigate two-phase flow in microelectromechanical systems, taking into account factors like surface tension. Systems using electrowetting, channel geometry, and hydrophobic or hydrophilic coatings to allow the smooth passage of fluids can then be designed. Such systems include compact medical devices, biosensors, and fuel cells. == Computing platform == μFluids@Home uses the BOINC volunteer computing platform. Application notes There is no screensaver. Work unit CPU times are generally less than 20 hours. Work units average in size around 500 kB. You must run many work units to get levels of credit comparable to SETI@home or climateprediction.net BOINC projects. == References == == External links == Website archive


id: history-of-open-access-20260505-0
file: data/en.wikipedia.org/wiki/History_of_open_access-0.md
category: reference
title: History of open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/History_of_open_access
date_saved: 2026-05-05T10:14:35.524738+00:00
instance: kb-cron
parent: history-of-open-access-20260505-0
summary:
The history of open access can be traced back to at least the 1950's, with an explosion of interest following the advent of the internet. The idea and practise of providing free online access to journal articles began at least a decade before the term "open access" was formally coined. Computer scientists had been self-archiving in anonymous ftp archives since the 1970s and physicists had been self-archiving in arXiv since the 1990s. The Subversive Proposal to generalize the practice was posted in 1994. The term "open access" itself was first formulated in three public statements in the 2000s: the Budapest Open Access Initiative in February 2002, the Bethesda Statement on Open Access Publishing in June 2003, and the Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities in October 2003, and the initial concept of open access refers to an unrestricted online access to scholarly research primarily intended for scholarly journal articles. == Efforts before the Internet == One early proponent of the publisher-pays model was the physicist Leó Szilárd. To help stem the flood of low-quality publications, he jokingly suggested in the 1940s that at the beginning of his career each scientist should be issued with


id: history-of-open-access-20260505-1
file: data/en.wikipedia.org/wiki/History_of_open_access-1.md
category: reference
title: History of open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/History_of_open_access
date_saved: 2026-05-05T10:14:35.524738+00:00
instance: kb-cron
parent: history-of-open-access-20260505-0
summary:
== Early years of online open access == An explosion of interest and activity in open-access journals has occurred since the 1990s, largely due to the widespread availability of Internet access. It is now possible to publish a scholarly article and also make it instantly accessible anywhere in the world where there are computers and Internet connections. The fixed cost of producing the article is separable from the minimal marginal cost of the online distribution. These new possibilities emerged at a time when the traditional, print-based scholarly journals system was in a crisis. The number of journals and articles produced had been increasing at a steady rate; however the average cost per journal had been rising at a rate far above inflation for decades, and budgets at academic libraries have remained fairly static. The result was decreased access – ironically, just when technology has made almost unlimited access a very real possibility, for the first time. Libraries and librarians have played an important part in the open-access movement, initially by alerting faculty and administrators to the serials crisis. The Association of Research Libraries developed the Scholarly Publishing and Academic Resources Coalition (SPARC), in 1997, an alliance of academic and research


id: history-of-open-access-20260505-2
file: data/en.wikipedia.org/wiki/History_of_open_access-2.md
category: reference
title: History of open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/History_of_open_access
date_saved: 2026-05-05T10:14:35.524738+00:00
instance: kb-cron
parent: history-of-open-access-20260505-0
summary:
== 2000s == The number of open-access journals increased by an estimated 500% during the 2000s. Also, the average number of articles that were published per open-access journal per year increased from approximately 20 to 40 during the same period, resulting in that the number of open-access articles increased by 900% during that decade. In 2000 BioMed Central, a for-profit open access publisher with now dozens of open-access journals, was launched by what was then the Current Science Group (the founder of the Current Opinion series, and now known as the Science Navigation Group). In some ways, BioMed Central resembles Harold Varmus' original E-biomed proposal more closely than does PubMed Central. As of October 2013 BioMed Central publishes over 250 journals. In 2001, 34,000 scholars around the world signed "An Open Letter to Scientific Publishers", calling for "the establishment of an online public library that would provide the full contents of the published record of research and scholarly discourse in medicine and the life sciences in a freely accessible, fully searchable, interlinked form". Scientists signing the letter also pledged not to publish in or peer-review for non-open-access journals. This led to the establishment of the Public Library of Science, an


id: history-of-open-access-20260505-3
file: data/en.wikipedia.org/wiki/History_of_open_access-3.md
category: reference
title: History of open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/History_of_open_access
date_saved: 2026-05-05T10:14:35.524738+00:00
instance: kb-cron
parent: history-of-open-access-20260505-0
summary:
== 2010s == In 2013 John Holdren, Barack Obama's director of the Office of Science and Technology Policy, issued a memorandum directing United States' Federal Agencies with more than $100 million in annual R&D expenditures to develop plans within six months to make the published results of federally funded research freely available to the public within one year of publication. As of March 2015, two agencies had made their plans public: the Department of Energy and the National Science Foundation. In 2013 the UK Higher Education Funding Council for England (HEFCE) proposed adopting a mandate that to be eligible for submission to the UK Research Excellence Framework (REF) all peer-reviewed journal articles submitted after 2014 must be deposited in the author's institutional repository immediately upon acceptance for publication, regardless of whether the article is published in a subscription journal or in an open access journal. HEFCE expresses no journal preference, places no restriction on authors' choice and requires the deposit itself to be immediate, irrespective of whether the publisher imposes an embargo (for an allowable embargo period that remains to be decided) on the date at which access to the deposit can be made open. The HEFCE/REF mandate proposal complements


id: timeline-of-the-open-access-movement-20260505-0
file: data/en.wikipedia.org/wiki/Timeline_of_the_open-access_movement-0.md
category: reference
title: Timeline of the open-access movement
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Timeline_of_the_open-access_movement
date_saved: 2026-05-05T10:14:36.706613+00:00
instance: kb-cron
parent: timeline-of-the-open-access-movement-20260505-0
summary:
The following is a timeline of the international movement for open access to scholarly communication. == 1940s-1990s == 1942 American sociologist Robert King Merton declares: "Each researcher must contribute to the 'common pot' and give up intellectual property rights to allow knowledge to move forward." 1971 "World's first online digital library is launched, Project Gutenberg." 1987 Syracuse University in the US issues one of the world's first open access journals, New Horizons in Adult Education (ISSN 1062-3183). 1991 14 August: ArXiv repository of physics research papers established at Los Alamos National Laboratory in the US. 1994 27 June: Stevan Harnad posts a "Subversive Proposal" for authors to archive their articles for free for everyone online. July 1994. Electronic Green Journal (EGJ) was launched by the University of Idaho Library. Since 2009 it is published by the University of California eScholarship. The EGJ is a peer-reviewed publication devoted to information about international sources on environmental protection, conservation, management of natural resources, and sustainability. 1998 Brazil-based SciELO (Scientific Electronic Library Online) launched. Public Knowledge Project founded in Canada. Scholarly Publishing and Academic Resources Coalition founded in North America. 1999 October: Open Archives Initiative on interoperability standards holds its first meeting, in New


id: diamond-open-access-20260505-0
file: data/en.wikipedia.org/wiki/Diamond_open_access-0.md
category: reference
title: Diamond open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Diamond_open_access
date_saved: 2026-05-05T10:14:37.993676+00:00
instance: kb-cron
parent: diamond-open-access-20260505-0
summary:
Diamond open access refers to academic texts (such as monographs, edited collections, and journal articles) published/distributed/preserved with no fees to either reader or author. Alternative labels include platinum open access, non-commercial open access, cooperative open access or, more recently, open access commons. While these terms were first coined in the 2000s and the 2010s, they have been retroactively applied to a variety of structures and forms of publishing, from subsidized university publishers to volunteer-run cooperatives that existed in prior decades. In 2021, it is estimated that between 17,000 and 29,000 scientific journals rely on a diamond open access model. They make up 73% of the journals registered in the Directory of Open Access Journals and 44% of the articles, as their mean output is smaller than commercial journals. The diamond model has been especially successful in Latin America-based journals (95% of OA journals) following the emergence of large publicly supported platforms, such as SciELO and Redalyc. However, Diamond OA journals are under-represented in the major scholarly databases, such as Web of Science and Scopus. It is also noteworthy, that high-income countries "have the highest share of authorship in every domain and type of journal, except for diamond journals in the


id: diamond-open-access-20260505-1
file: data/en.wikipedia.org/wiki/Diamond_open_access-1.md
category: reference
title: Diamond open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Diamond_open_access
date_saved: 2026-05-05T10:14:37.993676+00:00
instance: kb-cron
parent: diamond-open-access-20260505-0
summary:
=== Debates over the identity of the open access commons (2003–2012) === In the early debates over open access, the distinctions between commercial and non-commercial forms of scientific publishing and community-driven or corporate-owned structures seldom appear, possibly due to the lack of viable business model for open access. Open access publications were rather increasingly categorized into two different editorial forms: open access articles made immediately available by the publisher and pre-published articles hosted on an online archive (either as a pre-print or post-print). Starting in 2003, the ROMEO project started to devise a color-code system to better identify the policy of scientific publishers in regard to open sharing of scientific articles, from "yellow" (pre-print only) to "green" (no restriction in place): "the 'greenest' publishers are those that allow self-archiving not only of the author's accepted manuscript, but of the fully formatted and paginated publisher PDF". In 2004, Harnad et al. repurposed this classification scheme into a highly influential binary scale: articles directly made available by the publisher belong to "gold" open access (instead of "yellow") and online archives are defined as "green" open access. With this breakdown of open access into "green" and "gold", there is no distinction between commercial


id: diamond-open-access-20260505-2
file: data/en.wikipedia.org/wiki/Diamond_open_access-2.md
category: reference
title: Diamond open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Diamond_open_access
date_saved: 2026-05-05T10:14:37.993676+00:00
instance: kb-cron
parent: diamond-open-access-20260505-0
summary:
The number of Diamond OA journals is very large (>29,000), but only ~a third are registered in DOAJ, and only ~5% are indexed in either Scopus or Web of Science. Over half of these Diamond OA journals publish 25 or fewer articles per year. Between 2017 and 2019, paid-access journals published ~80% of all articles, paid-OA journals published ~11%, and Diamond OA journals published ~9%. The share of Diamond OA publications among all OA journal articles peaked in 2018 and has been declining since. Only 4.3% of Diamond OA journals are fully compliant with all Plan S criteria. Only 55% of Diamond OA journals provide DOI numbers for their articles. Only 25% of Diamond OA journals provide their content as XML or HTML (in addition to pdf). Only ~ half of Diamond OA journals provide download statistics for their content. 2/3 of Diamond OA journals use double-blind peer review, higher than subscription journals, which prefer single-blind peer review. 25% of Diamond OA journals operated at a loss, and just over 40% reported breaking even. The rest did not know their financial status. Although all Diamond OA journals rely heavily on volunteer work, they have some revenue sources, such as grants,


id: diamond-open-access-20260505-3
file: data/en.wikipedia.org/wiki/Diamond_open_access-3.md
category: reference
title: Diamond open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Diamond_open_access
date_saved: 2026-05-05T10:14:37.993676+00:00
instance: kb-cron
parent: diamond-open-access-20260505-0
summary:
=== Disciplines === While diamond OA journals are available for most disciplines, they are more prevalent in the humanities and social science. The OA Diamond Study finds that, among the journals registered on the DOAJ, humanities and social science publications make up 60% of diamond open access journals and only 23.9% of APC-based journals. This distribution may be due to the differentiated evolution of scientific publishing during the 20th century, as "small HSS journals are often owned by universities and societies who often prefer OA diamond models, while many big science and medicine journals are owned by commercial publishers, more inclined to use APC models." However, the diamond model is still present in many disciplines, with 22.2% of diamond journals in STEM and 17.1% in Medicine. Medical diamond journals are often embedded in local communities, especially in non-western countries: "It becomes apparent that local diamond OA journals are not only important in HSS, but also in medicine." An additional survey led by the OA Diamond Survey of 1,619 diamond OA journals highlights a more complex disciplinary distribution: although the social sciences (27.2%) and humanities (19.2%) are well represented, more than a quarter of respondents did not favor one discipline in


id: diamond-open-access-20260505-4
file: data/en.wikipedia.org/wiki/Diamond_open_access-4.md
category: reference
title: Diamond open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Diamond_open_access
date_saved: 2026-05-05T10:14:37.993676+00:00
instance: kb-cron
parent: diamond-open-access-20260505-0
summary:
Some journals argue that research funders have the responsibility to support or even favour OA diamond journals since they are often excluded from discussions on funding OA. While, the Plan S Principle 5 states that "the Funders support the diversity of business models for Open Access journals and platforms", perceptions will change once funders focus on OA diamond in addition to Gold OA and legacy publishing. This action has a significant potential to cover existing gaps in OA publishing. In 2020 and 2021, the institutional recognition of the diamond model has significantly progressed with unprecedented commitments from national and international organizations. The 2021 UNESCO recommendation for Open Science calls for "supporting not-for-profit, academic and scientific community-driven publishing models as a common good". The second French Plan for Open Science encouraged a "diversification of economic models" that especially highlight the diamond model as it should enable "a transition from subscription towards open access with no publishing fees". In March 2022, an Action Plan for Diamond Open Access was published with the support of the cOAlition S, Science Europe, OPERAS, and the French National Research Agency. This plan aims to "expand a sustainable, community-driven Diamond scholarly communication ecosystem." In 2024 the Toluca-Cape


id: open-access-20260505-0
file: data/en.wikipedia.org/wiki/Open_access-0.md
category: reference
title: Open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_access
date_saved: 2026-05-05T10:14:39.240543+00:00
instance: kb-cron
parent: open-access-20260505-0
summary:
Open access (OA) is a set of principles and a range of practices through which nominally copyrightable publications are delivered to readers free of access charges or other barriers. With open access strictly defined (according to the 2001 definition), or libre open access, barriers to copying or reuse are also reduced or removed by applying an open license for copyright, which regulates post-publication uses of the work. The main focus of the open access movement has been on peer reviewed research literature, and more specifically on academic journals. This is because: such publications have been a subject of serials crisis, unlike newspapers, magazines and fiction writing. The main difference between these two groups is in demand elasticity: whereas an English literature curriculum can substitute Harry Potter and the Philosopher's Stone with a public domain alternative, such as A Voyage to Lilliput, an emergency room physician treating a patient for a life-threatening urushiol poisoning cannot substitute the most recent, but paywalled review article on this topic with a 90-year-old copyright-expired article that was published before the invention of prednisone in 1954. the authors of research papers are not paid in any way, so they do not suffer any monetary losses, when


id: open-access-20260505-1
file: data/en.wikipedia.org/wiki/Open_access-1.md
category: reference
title: Open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_access
date_saved: 2026-05-05T10:14:39.240543+00:00
instance: kb-cron
parent: open-access-20260505-0
summary:
Similar to the free content definition, the terms 'gratis' and 'libre' were used in the Budapest Open Access Initiative definition to distinguish between free to read versus free to reuse. Gratis open access () refers to free online access, to read, free of charge, without re-use rights. Libre open access () also refers to free online access, to read, free of charge, plus some additional re-use rights, covering the kinds of open access defined in the Budapest Open Access Initiative, the Bethesda Statement on Open Access Publishing and the Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities. The re-use rights of libre OA are often specified by various specific Creative Commons licenses; all of which require as a minimum attribution of authorship to the original authors. In 2012, the number of works under libre open access was considered to have been rapidly increasing for a few years, though most open-access mandates did not enforce any copyright license and it was difficult to publish libre gold OA in legacy journals. However, there are no costs nor restrictions for green libre OA as preprints can be freely self-deposited with a free license, and most open-access repositories use Creative


id: open-access-20260505-2
file: data/en.wikipedia.org/wiki/Open_access-2.md
category: reference
title: Open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_access
date_saved: 2026-05-05T10:14:39.240543+00:00
instance: kb-cron
parent: open-access-20260505-0
summary:
Some open access journals (under the gold, and hybrid models) generate revenue by charging publication fees in order to make the work openly available at the time of publication. The money might come from the author but more often comes from the author's research grant or employer. While the payments are typically incurred per article published (e.g. BMC or PLOS journals), some journals apply them per manuscript submitted (e.g. Atmospheric Chemistry and Physics until recently) or per author (e.g. PeerJ). Charges typically range from $1,000–$3,000 ($5,380 for Nature Communications) but can be under $10, close to $5,000 or well over $10,000. APCs vary greatly depending on subject and region and are most common in scientific and medical journals (43% and 47% respectively), and lowest in arts and humanities journals (0% and 4% respectively). APCs can also depend on a journal's impact factor. Some publishers (e.g. eLife and Ubiquity Press) have released estimates of their direct and indirect costs that set their APCs. Hybrid OA generally costs more than gold OA and can offer a lower quality of service. A particularly controversial practice in hybrid open access journals is "double dipping", where both authors and subscribers are charged. By comparison, journal


id: open-access-20260505-3
file: data/en.wikipedia.org/wiki/Open_access-3.md
category: reference
title: Open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_access
date_saved: 2026-05-05T10:14:39.240543+00:00
instance: kb-cron
parent: open-access-20260505-0
summary:
==== Effect of preprints on later publication ==== A persistent concern surrounding preprints is that work may be at risk of being plagiarised or "scooped" – meaning that the same or similar research will be published by others without proper attribution to the original source – if publicly available but not yet associated with a stamp of approval from peer reviewers and traditional journals. These concerns are often amplified as competition increases for academic jobs and funding, and perceived to be particularly problematic for early-career researchers and other higher-risk demographics within academia. However, preprints, in fact, protect against scooping. Considering the differences between traditional peer-review based publishing models and deposition of an article on a preprint server, "scooping" is less likely for manuscripts first submitted as preprints. In a traditional publishing scenario, the time from manuscript submission to acceptance and to final publication can range from a few weeks to years, and go through several rounds of revision and resubmission before final publication. During this time, the same work will have been extensively discussed with external collaborators, presented at conferences, and been read by editors and reviewers in related areas of research. Yet, there is no official open record of


id: open-access-20260505-4
file: data/en.wikipedia.org/wiki/Open_access-4.md
category: reference
title: Open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_access
date_saved: 2026-05-05T10:14:39.240543+00:00
instance: kb-cron
parent: open-access-20260505-0
summary:
The intended audience of research articles is usually other researchers. Open access helps researchers as readers by opening up access to articles that their libraries do not subscribe to. All researchers benefit from open access as no library can afford to subscribe to every scientific journal and most can only afford a small fraction of them. This is known as the "serials crisis". Open access extends the reach of research beyond its immediate academic circle, as an open access article can be read by anyone. A 2008 study revealed that mental health professionals are roughly twice as likely to read a relevant article if it is freely available. ==== Research funders ==== Research funding agencies and universities want to ensure that the research they fund and support in various ways has the greatest possible research impact. As a means of achieving this, research funders are beginning to expect open access to the research they support. Many of them (including all UK Research Councils) have already adopted open-access mandates, and others are on the way to do so (see ROARMAP). ==== Universities ==== A growing number of universities are providing institutional repositories in which their researchers can deposit their published articles.


id: open-access-20260505-5
file: data/en.wikipedia.org/wiki/Open_access-5.md
category: reference
title: Open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_access
date_saved: 2026-05-05T10:14:39.240543+00:00
instance: kb-cron
parent: open-access-20260505-0
summary:
==== Low-income countries ==== In developing nations, open access archiving and publishing acquires a unique importance. Scientists, health care professionals, and institutions in developing nations often do not have the capital necessary to access scholarly literature. Many open access projects involve international collaboration. For example, the SciELO (Scientific Electronic Library Online), is a comprehensive approach to full open access journal publishing, involving a number of Latin American countries. Bioline International, a non-profit organization dedicated to helping publishers in developing countries is a collaboration of people in the UK, Canada, and Brazil; the Bioline International Software is used around the world. Research Papers in Economics (RePEc), is a collaborative effort of over 100 volunteers in 45 countries. The Public Knowledge Project in Canada developed the open-source publishing software Open Journal Systems (OJS), which is now in use around the world, for example by the African Journals Online group, and one of the most active development groups is Portuguese. This international perspective has resulted in advocacy for the development of open-source appropriate technology and the necessary open access to relevant information for sustainable development. == History == === Extent === Various studies have investigated the extent of open access. A study published


id: open-access-20260505-6
file: data/en.wikipedia.org/wiki/Open_access-6.md
category: reference
title: Open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_access
date_saved: 2026-05-05T10:14:39.240543+00:00
instance: kb-cron
parent: open-access-20260505-0
summary:
==== Readership ==== OA articles are generally viewed online and downloaded more often than paywalled articles and that readership continues for longer. Readership is especially higher in demographics that typically lack access to subscription journals (in addition to the general population, this includes many medical practitioners, patient groups, policymakers, non-profit sector workers, industry researchers, and independent researchers). OA articles are more read on publication management programs such as Mendeley. Open access practices can reduce publication delays, an obstacle which led some research fields such as high-energy physics to adopt widespread preprint access. ==== Citation rate ==== A main reason authors make their articles openly accessible is to maximize their citation impact. Open access articles are typically cited more often than equivalent articles requiring subscriptions. This 'citation advantage' was first reported in 2001. Although two major studies dispute this claim, the consensus of multiple studies support the effect, with measured OA citation advantage varying in magnitude between 1.3-fold to 6-fold depending on discipline. Citation advantage is most pronounced in OA articles in hybrid journals (compared to the non-OA articles in those same journals), and with articles deposited in green OA repositories. Notably, green OA articles show similar benefits to citation counts


id: open-access-20260505-7
file: data/en.wikipedia.org/wiki/Open_access-7.md
category: reference
title: Open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_access
date_saved: 2026-05-05T10:14:39.240543+00:00
instance: kb-cron
parent: open-access-20260505-0
summary:
=== Open irony === Open irony refers to the situation where a scholarly journal article advocates open access but the article itself is only accessible by paying a fee to the journal publisher to read the article. This has been noted in many fields, with more than 20 examples appearing since around 2010, including in widely-read journals such as The Lancet, Science and Nature. In 2012 Duncan Hull proposed the Open Access Irony award to publicly humiliate journals that publish these kinds of papers. Examples of these have been shared and discussed on social media using the hashtag #openirony. Typically, these discussions are humorous exposures of articles/editorials that are pro-open access, but locked behind paywalls. The main concern that motivates these discussions is that restricted access to public scientific knowledge is slowing scientific progress. The practice has been justified as important for raising awareness of open access. == Infrastructure == === Databases and repositories === Multiple databases exist for open access articles, journals and datasets. These databases overlap, however each has different inclusion criteria, which typically include extensive vetting for journal publication practices, editorial boards and ethics statements. The main databases of open access articles and journals are DOAJ and


id: open-access-20260505-8
file: data/en.wikipedia.org/wiki/Open_access-8.md
category: reference
title: Open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_access
date_saved: 2026-05-05T10:14:39.240543+00:00
instance: kb-cron
parent: open-access-20260505-0
summary:
Many universities, research institutions and research funders have adopted mandates requiring their researchers to make their research publications open access. For example, Research Councils UK spent nearly £60m on supporting their open access mandate between 2013 and 2016. New mandates are often announced during the Open Access Week, that takes place each year during the last full week of October. The idea of mandating self-archiving was raised at least as early as 1998. Since 2003 efforts have been focused on open access mandating by the funders of research: governments, research funding agencies, and universities. Some publishers and publisher associations have lobbied against introducing mandates. In 2002, the University of Southampton's School of Electronics & Computer Science became one of the first schools to implement a meaningful mandatory open access policy, in which authors had to contribute copies of their articles to the school's repository. More institutions followed suit in the following years. In 2007, Ukraine became the first country to create a national policy on open access, followed by Spain in 2009. Argentina, Brazil, and Poland are currently in the process of developing open access policies. Making master's and doctoral theses open access is an increasingly popular mandate by many


id: open-access-20260505-9
file: data/en.wikipedia.org/wiki/Open_access-9.md
category: reference
title: Open access
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_access
date_saved: 2026-05-05T10:14:39.240543+00:00
instance: kb-cron
parent: open-access-20260505-0
summary:
== Further reading == Darnton, Robert, "The Dream of a Universal Library" (review of Peter Baldwin, Athena Unbound: Why and How Scholarly Knowledge Should Be Free for All, MIT Press, 2023, 405 pp.), The New York Review of Books, vol. LXX, no. 20 (21 December 2023), pp. 73–74. Reviewer Darnton writes: "Baldwin warns: journal publishers are gouging their customers, scholarly monographs reach a tiny audience, libraries are floundering under budget pressures, academics are pursuing careers rather than truth, and readers are not getting all the information they deserve." (p. 74.) Writes Darnton: "Most scientific research is subsidized by the federal government." Under a 2022 White House directive, "As of December 31, 2025, all agencies... must require immediate open access... The G7 leaders took a similar stand on May 14, 2023, as did the European Council on May 23. The tide is turning in favor of unrestricted access, but the countervailing forces are so complex that the future remains cloudy." (p. 73.) Suber, Peter (2012). Open access (The MIT Press Essential Knowledge Series ed.). Cambridge, Mass.: MIT Press. ISBN 978-0-262-51763-8. Retrieved 20 October 2015. Kirsop, Barbara, and Leslie Chan. (2005) Transforming access to research literature for developing countries. Serials Reviews, 31(4):


id: subscribe-to-open-20260505-0
file: data/en.wikipedia.org/wiki/Subscribe_to_Open-0.md
category: reference
title: Subscribe to Open
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Subscribe_to_Open
date_saved: 2026-05-05T10:14:40.450152+00:00
instance: kb-cron
parent: subscribe-to-open-20260505-0
summary:
Subscribe to Open (S2O) is an economic model used by peer-reviewed scholarly journals to provide readers with open access (OA) to the journal’s content, without charging costs to authors. S2O converts journals that have a traditional subscription model to open access. When the academic libraries subscribing to a journal are asked to renew their subscriptions to the journal, they are told that, with the libraries’ support, the journal will be made open access to all readers, while authors are able to publish in it at no cost. If enough libraries renew on these terms, the journal is converted to open access, and if not, access to the journal remains restricted to subscribing libraries. == Background == The term “Open Access” (OA) was first coined in December 2001 in a call for greater access to academic journal articles, which were mainly available through subscriptions. Influential statements such as the Budapest Open Access Initiative (BOAI) in February 14, 2002, have called for improvement of the circulation of research through open access to scholarly journals. Since then, more than twenty financial models have been developed as alternatives to the traditional subscription model, beginning with authors paying article processing charges (APCs) to BioMed Central


id: academic-spring-20260505-0
file: data/en.wikipedia.org/wiki/Academic_Spring-0.md
category: reference
title: Academic Spring
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Academic_Spring
date_saved: 2026-05-05T10:14:41.679545+00:00
instance: kb-cron
parent: academic-spring-20260505-0
summary:
The Academic Spring was the designation, inspired by the Arab Spring, used for a short time in 2012 to indicate movements by academics, researchers, and scholars opposing the restrictive copyright and circulation of traditional academic journals and promoting free access online instead. == History == There have been previous attempts to increase the availability of free and up-to-date scientific research. In 2004, there were reports in British media of a "revolution in academic publishing" which would make research freely available online but many scientists continued to publish their work in the traditional big name journals like Nature. The barriers to free access for recent scientific research became a hot topic in 2012, after a blog post by mathematician Timothy Gowers went viral in January. According to the Financial Times, the movement was named by Dennis Johnson of Melville House Publishing, though scientist Mike Taylor has suggested the name came from The Economist. === Research Works Act === In December 2011 the Research Works Act was proposed in the US Congress to restrict open access to research funded by the US federal government. This followed other similar proposed measures such as the Fair Copyright in Research Works Act. These attempts to


id: academic-studies-press-20260505-0
file: data/en.wikipedia.org/wiki/Academic_Studies_Press-0.md
category: reference
title: Academic Studies Press
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Academic_Studies_Press
date_saved: 2026-05-05T10:14:42.867762+00:00
instance: kb-cron
parent: academic-studies-press-20260505-0
summary:
Academic Studies Press, (ASP) is an independent scholarly publisher of books and journals, based in Boston, Massachusetts. == History == Founded in 2007, ASP emphasizes Jewish studies and Slavic studies, but also publishes titles in religious studies, comparative literature, and history more broadly. Authors include Jacob Neusner, Fania Oz-Salzberger, Ellendea Proffer Teasley, Maxim D. Shrayer, Mark Lipovetsky, David Berger, Menachem Kellner, Viktor Zhivov, Jerold Auerbach, and Geoffrey Alderman, while works in translation include those of Maimonides, Ahad Ha'am, Mordecai Kaplan, Eliezer Schweid, and Yury Tynyanov. The press also specializes in Ukrainian translations, many of which received renewed interest during the 2022 Russian invasion of Ukraine. Its titles have won awards from the Jewish Book Council, the Modern Language Association, AATSEEL, and the Koffler Centre of the Arts, and have also appeared on reading lists published by Mosaic and The Washington Post. In 2017, ASP was the recipient of funding from the National Endowment for the Humanities to aid in the "creation of freely accessible e-books for 42 seminal titles in Russian literary and cultural history." In the same year, ASP collaborated jointly with the NEH and the Ukrainian Research Institute at Harvard University to publish Words for War, an anthology


id: article-processing-charge-20260505-0
file: data/en.wikipedia.org/wiki/Article_processing_charge-0.md
category: reference
title: Article processing charge
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Article_processing_charge
date_saved: 2026-05-05T10:14:46.180705+00:00
instance: kb-cron
parent: article-processing-charge-20260505-0
summary:
An article processing charge (APC), also known as a publication fee, is a fee which is sometimes charged to authors. Most commonly, it is involved in making an academic work available as open access (OA), in either a full OA journal or in a hybrid journal. This fee may be paid by the author, the author's institution, or their research funder. Sometimes, publication fees are also involved in traditional journals or for paywalled content. Some publishers waive the fee in cases of hardship or geographic location, but this is not a widespread practice. An article processing charge does not guarantee that the author retains copyright to the work, or that it will be made available under a Creative Commons license. == Background == Journals use a variety of ways to generate the income required to cover publishing costs (including editorial costs, any costs of administering the peer review system), such as subsidies from institutions and subscriptions. A majority of open access journals do not charge article processing charges, but a significant and growing number of them do. They are the most common funding method for professionally published open access articles. APC fees applied to academic research are usually expensive, effectively


id: article-processing-charge-20260505-1
file: data/en.wikipedia.org/wiki/Article_processing_charge-1.md
category: reference
title: Article processing charge
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Article_processing_charge
date_saved: 2026-05-05T10:14:46.180705+00:00
instance: kb-cron
parent: article-processing-charge-20260505-0
summary:
==== Cost to scientists and funding bodies ==== Article processing charges shift the burden of payment from readers to authors (or their funders), which creates a new set of concerns. One concern is that if a publisher makes a profit from accepting papers, it has an incentive to accept anything submitted, rather than selecting and rejecting articles based on quality. This could be remedied, however, by charging for the peer-review rather than acceptance. Another concern is that institutional budgets may need to be adjusted in order to provide funding for the article processing charges required to publish in many open access journals (e.g. those published by BioMed Central). It has been argued that this may reduce the ability to publish research results due to lack of sufficient funds, leading to some research not becoming a part of the public record. Another concern is the redirection of money by major funding agencies such as the National Institutes of Health and the Wellcome Trust from the direct support of research to the support of open access publication. Robert Terry, Senior Policy Advisor at the Wellcome Trust, has said that he feels that 1–2% of their research budget will change from the creation


id: base-search-engine-20260505-0
file: data/en.wikipedia.org/wiki/BASE_(search_engine)-0.md
category: reference
title: BASE (search engine)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/BASE_(search_engine)
date_saved: 2026-05-05T10:14:47.317292+00:00
instance: kb-cron
parent: base-search-engine-20260505-0
summary:
BASE (Bielefeld Academic Search Engine) is a multi-disciplinary search engine to scholarly internet resources, created by Bielefeld University Library in Bielefeld, Germany. It is based on free and open-source software such as Apache Solr and VuFind. It harvests OAI metadata from institutional repositories and other academic digital libraries that implement the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH), and then normalizes and indexes the data for searching. In addition to OAI metadata, the library indexes selected web sites and local data collections, all of which can be searched via a single search interface. == History == BASE was developed at the German university of Bielefeld beginning in 2002. The project's initial goal was to develop a search engine that would provide users access to the university's research resources. Yet as the initiative advanced, the creators came to see the need for a more thorough search engine that might provide users access to academic resources outside of the university. The initial iteration of BASE was released as a prototype in 2004 and made accessible to the general public for testing. The search engine was created to index and offer access to scholarly materials such journals, institutional repositories, and digital collections


id: beall-s-list-20260505-0
file: data/en.wikipedia.org/wiki/Beall's_List-0.md
category: reference
title: Beall's List
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Beall's_List
date_saved: 2026-05-05T10:14:49.561109+00:00
instance: kb-cron
parent: beall-s-list-20260505-0
summary:
Beall's List was a list of predatory open-access publishers that was maintained by University of Colorado Denver librarian Jeffrey Beall on his blog Scholarly Open Access. The list aimed to document open-access publishers who did not perform real peer review, effectively publishing any article as long as the authors pay the article processing charge. Originally started as a personal endeavor in 2008, Beall's List became a widely followed piece of work by the mid-2010s. The list was used by scientists to identify exploitative publishers and detect publisher spam. The influence of Beall's List led some publishers on the list to threaten defamation lawsuits against Beall, as well as to lodge official complaints against Beall's work to the University of Colorado. In January 2017, Beall removed the list from his blog, scholarlyoa.com. Six months later, he published an article in the journal Biochemia Medica claiming that pressure from his employer led to the blog shutdown, although the university's official statement and a response by Beall's direct supervisor both disputed this account. The closure of Beall's List was cited by some as a loss of an important resource, and successors have set out to continue Beall's work. == Early history == Beall


id: beall-s-list-20260505-1
file: data/en.wikipedia.org/wiki/Beall's_List-1.md
category: reference
title: Beall's List
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Beall's_List
date_saved: 2026-05-05T10:14:49.561109+00:00
instance: kb-cron
parent: beall-s-list-20260505-0
summary:
==== "Dr Fraud" experiment ==== In 2015, four researchers created a fictitious sub-par scientist named Anna O. Szust (oszust is Polish for "fraud"), and applied on her behalf for an editor position to 360 scholarly journals. Szust's qualifications were dismal for the role of an editor; she had never published a single article and had no editorial experience. The books and book chapters listed on her CV were made-up, as were the publishing houses that allegedly published the books. One-third of the journals to which Szust applied were sampled from Beall's List. Forty of these predatory journals accepted Szust as editor without any background vetting and often within days or even hours. By comparison, she received minimal to no positive response from the "control" journals which "must meet certain standards of quality, including ethical publishing practices." Among journals sampled from the Directory of Open Access Journals (DOAJ), 8 of 120 accepted Szust. The DOAJ has since removed some of the affected journals in a 2016 purge. None of the 120 sampled journals listed in Journal Citation Reports (JCR) offered Szust the position. The results of the experiment were published in Nature in March 2017, and widely presented in the press.


id: beall-s-list-20260505-2
file: data/en.wikipedia.org/wiki/Beall's_List-2.md
category: reference
title: Beall's List
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Beall's_List
date_saved: 2026-05-05T10:14:49.561109+00:00
instance: kb-cron
parent: beall-s-list-20260505-0
summary:
Since Beall's List closed, similar lists have been started by others, including CSIR-Structural Engineering Research Centre, and an anonymous group at Stop Predatory Journals. Cabell's International, a company that offers scholarly publishing analytics and other scholarly services, has also offered both a black list and a white list for subscription on their website. Since 2021, the Norwegian Scientific Index includes the category "level X" that includes journals suspected of being predatory; its establishment was linked to expressions of concern regarding the publisher MDPI. A site entitled Beall's List of Potential Predatory Journals and Publishers states that it includes the original list as at 15 January 2017, with updates listed separately, maintained by an anonymous European postdoctoral researcher. == See also == Journalology == References == == Further reading == Buschman, John (2020). "A Political Sociology of the Beall's List Affair". The Library Quarterly. 90 (3): 298–313. doi:10.1086/708959. S2CID 224809316. == External links == Beall, Jeffrey. "List of Publishers: Potential, possible, or probable predatory scholarly open-access publishers" (last archived ed.). Archived from the original on January 12, 2017. Beall, Jeffrey. "List of Standalone Journals: Potential, possible, or probable predatory scholarly open-access journals" (last archived ed.). Archived from the original on January


id: bibsam-consortium-20260505-0
file: data/en.wikipedia.org/wiki/Bibsam_Consortium-0.md
category: reference
title: Bibsam Consortium
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Bibsam_Consortium
date_saved: 2026-05-05T10:14:50.757805+00:00
instance: kb-cron
parent: bibsam-consortium-20260505-0
summary:
Bibsam Consortium is a consortium in which 85 higher education and research institutions in Sweden participate to negotiate license agreements for electronic information resources. The consortium is headed by the National Library of Sweden and negotiates as well as administrates license agreements for e-resource packages. The participating institutions sign a power of attorney which allows the National Librarian to sign contracts with the e-resource providers. == History and scope == The Bibsam Consortium was formed in 1996 in order to negotiate license agreements for electronic resources on behalf of Swedish Universities, research institutes and government agencies. The total turnover of the agreements in 2015 was € 33 million and € 35 million in 2017 with 73% of the turnover being generated by the ten largest universities in Sweden. There are six members in National Library of Sweden to negotiate and administer the 100 license agreements for approximately 40 e-resource packages. == Negotiation with Elsevier == In 2018, the Bibsam Consortium terminated its agreement with Elsevier publishers in order to stop rising prices of publishing and to support open access publishing. The termination went into effect on 1 July 2018, as a result of which Swedish Universities and colleges had no


id: centre-pour-l-dition-lectronique-ouverte-20260505-0
file: data/en.wikipedia.org/wiki/Centre_pour_l'Édition_Électronique_Ouverte-0.md
category: reference
title: Centre pour l'Édition Électronique Ouverte
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Centre_pour_l'Édition_Électronique_Ouverte
date_saved: 2026-05-05T10:14:53.040562+00:00
instance: kb-cron
parent: centre-pour-l-dition-lectronique-ouverte-20260505-0
summary:
The Centre pour l'Édition Électronique Ouverte (CLEO, Cléo; transl. Centre for Open Electronic Publishing), based in Marseille, France, is overseen by Aix-Marseille University, the Centre National de la Recherche Scientifique, School for Advanced Studies in the Social Sciences, and University of Avignon and the Vaucluse. It produces the open access academic publishing portal OpenEdition.org, which includes platforms Calenda, Hypotheses, OpenEdition Books, and OpenEdition Journals. OpenEdition focuses on publications in the academic fields of humanities and social sciences. The centre also issues a blog about open access. == OpenEdition Books == include: Bak-Geller, Sarah (28 July 2022). "Patrimonio alimentario y ciudadanía indígena. El caso coca de Mezcala, Jalisco (México)". In Rebaï, Nasser; Bilhaut, Anne-Gaël; de Suremain, Charles-Édouard; Katz, Esther; Paredes, Myriam (eds.). Patrimonios alimentarios en América Latina : Recursos locales, actores y globalización (in Spanish). IRD Éditions. pp. 191–214. ISBN 978-2-7099-2943-1. Retrieved 27 April 2023 – via Centre pour l'Édition Électronique Ouverte. Introducción == OpenEdition Journals == The following list includes some examples of titles in Journals.openedition.org (prior to December 2017 known as Revues.org): == See also == OpenEdition access via Wikipedia Library Open access journal Open access in France List of academic databases and search engines == References == ==


id: copim-20260505-0
file: data/en.wikipedia.org/wiki/COPIM-0.md
category: reference
title: COPIM
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/COPIM
date_saved: 2026-05-05T10:14:54.247395+00:00
instance: kb-cron
parent: copim-20260505-0
summary:
The Copim community is an international group of researchers, universities, librarians, open access book publishers and infrastructure providers. It is building community-owned, open systems and infrastructures to enable open-access book publishing to flourish. The collaboration is being funded by Research England and Arcadia Fund, via two consecutive projects between November 2019 and April 2026. The community's name is derived from the original project acronym of COPIM (Community-led Open Publication Infrastructures for Monographs). During its first project phase (11/2019-04/2023), the community has been involved in the foundational project of the same name. As of 05/2023, this is now followed by a second project phase under the title of Open Book Futures, through which the Copim community aims to expand and accelerate the uptake of the infrastructures developed during its initial project phase. Following the principle of 'Scaling Small', the project has developed a set of proof-of-concepts of non-profit and community-owned, open infrastructures to enable open access book publishing to prosper. Copim has been named as a Supporting Action in UKRI's 2020 Open Access Review Consultation. == Work Packages == In seven distinct Work Packages, the COPIM project explored: how to scope and build support for an integration of open access books


id: the-cost-of-knowledge-20260505-0
file: data/en.wikipedia.org/wiki/The_Cost_of_Knowledge-0.md
category: reference
title: The Cost of Knowledge
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/The_Cost_of_Knowledge
date_saved: 2026-05-05T10:14:56.579118+00:00
instance: kb-cron
parent: the-cost-of-knowledge-20260505-0
summary:
The Cost of Knowledge is a protest by academics against the business practices of academic journal publisher Elsevier. Among the reasons for the protests were a call for lower prices for journals and to promote increased open access to information. The main work of the project was to ask researchers to sign a statement committing not to support Elsevier journals by publishing, performing peer review, or providing editorial services for these journals. == History == Before the advent of the Internet, it was difficult for scholars to distribute articles giving their research results. Historically, publishers performed services including proofreading, typesetting, copyediting, printing, and worldwide distribution. In more recent times, all researchers became expected to give the publishers digital copies of their work which needed no further processing – in other words, the modern academic is expected to do, often for free, duties traditionally assigned to the publisher, and for which, traditionally, the publisher is paid in exchange. For digital distribution, printing is unnecessary, copying is (almost) free, and worldwide distribution happens online instantly. Internet technology, and with it the aforementioned significant decrease in overhead costs, enabled the four major scientific publishers – Elsevier, Springer, Wiley, and Informa – to cut


id: the-cost-of-knowledge-20260505-1
file: data/en.wikipedia.org/wiki/The_Cost_of_Knowledge-1.md
category: reference
title: The Cost of Knowledge
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/The_Cost_of_Knowledge
date_saved: 2026-05-05T10:14:56.579118+00:00
instance: kb-cron
parent: the-cost-of-knowledge-20260505-0
summary:
=== Impact and reception === In February 2012, analysts of the Exane Paribas bank reported a financial impact on Elsevier with the company's stock prices falling due to the boycott. Dennis Snower criticised the monopoly of scientific publishers, but said at the same time that he did not support the boycott even though he himself is the editor-in-chief of an open-access journal on economics. He thinks that more competition among the various journals should instead be encouraged. The Senate of the University of Kansas has been reported to consider joining the boycott of Elsevier. In allusion to the revolutions of the Arab Spring, the German Frankfurter Allgemeine Zeitung daily newspaper called the movement the "Academic Spring" (German: Akademischer Frühling). When the British Wellcome Trust made a commitment to open up science, The Guardian similarly called this the "Academic Spring". After the Wellcome Trust announcement, The Cost of Knowledge campaign was recognized by that newspaper as the start of something new. A 2016 study evaluating the boycott stated that in the past four years 38% of signatories had abandoned their "won't publish in an Elsevier outlet" commitment and that only around 5000 researchers were still clearly boycotting Elsevier by publishing elsewhere.


id: data-publishing-20260505-0
file: data/en.wikipedia.org/wiki/Data_publishing-0.md
category: reference
title: Data publishing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Data_publishing
date_saved: 2026-05-05T10:14:59.043159+00:00
instance: kb-cron
parent: data-publishing-20260505-0
summary:
Data publishing (also data publication) is the act of releasing research data in published form for use by others. It is a practice consisting in preparing certain data or data set(s) for public use thus to make them available to everyone to use as they wish. This practice is an integral part of the open science movement. There is a large and multidisciplinary consensus on the benefits resulting from this practice. The main goal is to elevate data to be first class research outputs. There are a number of initiatives underway as well as points of consensus and issues still in contention. There are several distinct ways to make research data available, including: publishing data as supplemental material associated with a research article, typically with the data files hosted by the publisher of the article hosting data on a publicly available website, with files available for download hosting data in a repository that has been developed to support data publication, e.g. figshare, Dryad, Dataverse, Zenodo. A large number of general and specialty (such as by research topic) data repositories exist. For example, the UK Data Service enables users to deposit data collections and re-share these for research purposes. publishing a


id: directory-of-open-access-journals-20260505-0
file: data/en.wikipedia.org/wiki/Directory_of_Open_Access_Journals-0.md
category: reference
title: Directory of Open Access Journals
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Directory_of_Open_Access_Journals
date_saved: 2026-05-05T10:15:03.862197+00:00
instance: kb-cron
parent: directory-of-open-access-journals-20260505-0
summary:
The Directory of Open Access Journals (DOAJ) is a website that hosts a community-curated list of open access journals, maintained by Infrastructure Services for Open Access (IS4OA). It was launched in 2003 with 300 open access journals and now has expanded to over 22,886 indexed open access journals and 12,746,462 articles. The mission of DOAJ is to "increase the visibility, accessibility, reputation, usage and impact of quality, peer-reviewed, open access scholarly research journals globally, regardless of discipline, geography or language." In 2015, DOAJ launched a reapplication process based on updated and expanded inclusion criteria. At the end of the process (December 2017), close to 5,000 journals, out of the 11,600 indexed in May 2016, had been removed from their database, in majority for failure to reapply. Notwithstanding the substantial cleanup, the number of journals included in DOAJ has continued to grow, to reach 14,299 as of 3 March 2020. As of April 2025, the independent database contains more than 21,480 open access journals and 11,045,921 articles covering all areas of science, technology, medicine, social sciences and the humanities. DOAJ provides a change log on Google Sheets that has been updated since March 2014 and identifies the journals added and the


id: disciplinary-repository-20260505-0
file: data/en.wikipedia.org/wiki/Disciplinary_repository-0.md
category: reference
title: Disciplinary repository
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Disciplinary_repository
date_saved: 2026-05-05T10:15:05.025845+00:00
instance: kb-cron
parent: disciplinary-repository-20260505-0
summary:
A disciplinary repository (or subject repository) is an online archive, often an open-access repository, containing works or data associated with these works of scholars in a particular subject area. Disciplinary repositories can accept work from scholars from any institution. A disciplinary repository shares the roles of collecting, disseminating, and archiving work with other repositories, but is focused on a particular subject area. These collections can include academic and research papers. Disciplinary repositories can acquire their content in many ways. Many rely on author or organization submissions, such as SSRN. Others such as CiteSeerX crawl the web for scholar and researcher websites and download publicly available academic papers from those sites. AgEcon, established in 1995, grew as a result of active involvement of academia and societies. A disciplinary repository generally covers one broad based discipline, with contributors from many different institutions supported by a variety of funders; the repositories themselves are likely to be funded from one or more sources within the subject community. Deposit of material in a disciplinary repository is sometimes mandated by research funders. Disciplinary repositories can also act as stores of data related to a particular subject, allowing documents along with data associated with that work to


id: economics-of-open-science-20260505-0
file: data/en.wikipedia.org/wiki/Economics_of_open_science-0.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T10:15:06.320001+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
The economics of open science describe the economic aspects of making a wide range of scientific outputs (e.g., publications, data, software) to all levels of society. Open science involves a plurality of economic models and goods. Historically, academic journals and other academic institutions, such as learned societies, have favored a knowledge club or a toll access model: publications are managed as a community service for the selected benefit of academic readers and authors. During the second half of the 20th century, the "big 5" largest publishers (Elsevier, Springer, Wiley, Taylor & Francis, and the American Chemical Society) have partly absorbed or outcompeted non-profits structure and applied an industrial approach to scholarly publishing. The development of the web shifted the focus of scholarly communication from publication to a large variety of outputs (data, software, metrics). It also challenged the values and the organization of existing actors with the development of an international initiatives in favor of open access and open science. While initially distanced by new competitors, the main commercial publishers have started to flip to author-pay models after 2000, funded through article processing charges and the negotiation of transformative deals. Actors like Elsevier or Wiley have diversified their activities from


id: economics-of-open-science-20260505-1
file: data/en.wikipedia.org/wiki/Economics_of_open_science-1.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T10:15:06.320001+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
=== Open science club === The economic theory of club goods was originally developed in the 1965 by James Buchanan to complement the distinction between private and public goods. While clubs are private organizations they also manage the allocation of the resources between the individual members, in a similar manner to a public service. Membership criteria are a fundamental feature of clubs and affect their efficiency: "The central question in a theory of clubs is that of determining the membership margin, so to speak, the size of the most desirable cost and consumption sharing arrangement." ==== Definitions of knowledge club ==== Before the Second World War, academic publishing was mostly characterized by a wide range of community-driven scholarly structures with little concerns for profitability. They relied on informal community norms rather than commercial regulations. Theses structures have been described as knowledge clubs: "until the second part of the twentieth century, most journals could be assimilated to a club model". While managed by a community and publicly available, knowledge club are demic and mostly used to the benefit of their members. As a defining feature of the club model, scientific authors are not paid for their publications: "ever since the first


id: economics-of-open-science-20260505-2
file: data/en.wikipedia.org/wiki/Economics_of_open_science-2.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T10:15:06.320001+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
==== Knowledge club and open science ==== The OA Diamond Study states that non-commercial journals in open access "maintain a secular tradition of "club" journals, set up for the uses and interests of a specific closed community of knowledge." While access to read is no longer a material condition for membership, non-commercial journals are still largely managed for the benefits of a community. They are "still strongly embedded in institutional environments (from a legal and governance perspective)." Club journals have gained a new relevance with the development of electronic publishing and played a fundamental role in the early development of online open science in the early 1990s. Pioneers of open access electronic publishings were non-commercial and community-driven initiatives that built up on a trend of grassroot publishing innovation in the social sciences and the humanities: "In the late '80s and early '90s, a host of new journal titles launched on listservs and (later) the Web. Journals such as Postmodern Cultures, Surfaces, the Bryn Mawr Classical Review and the Public-Access Computer Systems Review were all managed by scholars and library workers rather than publishing professionals." The development of the web and free editing tools for scientific publications like Open Journal System


id: economics-of-open-science-20260505-3
file: data/en.wikipedia.org/wiki/Economics_of_open_science-3.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T10:15:06.320001+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
The small society presses, struggling to cope with growing scale, were supported and then largely supplanted by the 'Big 5' commercial presses: Elsevier (which acquired Pergamon in 1991), Wiley, Springer, Taylor & Francis and Sage. These newly-empowered players brought an industrial approach to the publication and dissemination process, for the first time realising the benefits that these specialised capital and skills could provide by operating at a scale that was unprecedented to that date. As it became a private good, the scientific journal was also transformed into an industrial product, with an increased standardization of publishing norms, peer-review process or copyrights. In contrast smaller scientific publishers participate to a more typical publishing market, with a persistent competition. Four out of the five most costly journals "are published by big five publishers". With the conversion to electronic journals, scientific publishing became a hybrid market: along with individual subscriptions, leading publishers introduced big deals or pluri-annual licenses to large bundle of journal titles. Big deals were typically negotiated with national networks of research libraries and academic institutions. Big deals proved advantageous to publishers as well as they limited the "administrative costs" of managing a large number of contracts between journals and buyers.


id: economics-of-open-science-20260505-4
file: data/en.wikipedia.org/wiki/Economics_of_open_science-4.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T10:15:06.320001+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
==== From readers to authors: hybrid and full open access ==== The early developments of Open science and the open sharing of scientific publication on the web was at first a challenge for leading commercial publishers: the executive board of Elsevier "had failed to grasp the significance of electronic publishing altogether, and therefore the deadly danger that it posed—the danger, namely, that scientists would be able to manage without the journal". Initial experiments of scientific journals were mostly led by non-commercial initiatives. Commercially viable open access journals have appeared in the late 1990s, under the leadership of new competitors such as the Public Library of Science (PLOS), MDPI or Hindawi. They relies generally on the author-pay model: the journal provides an editorial service to the author of a publication and charge an article-processing charge to cover the editing costs. This practice is anterior to open access, as subscription-based journals held by scientific societies occasionally charged for additional services (such as photographies in color). For Peter Suber, this economic model is similar to broadcast television: "If advertisers can pay all the costs of production, then a TV studio can broadcast a show without charging viewers. In the case of scholarly research


id: economics-of-open-science-20260505-5
file: data/en.wikipedia.org/wiki/Economics_of_open_science-5.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T10:15:06.320001+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
the largest supplier of academic journals is also in charge of evaluating and validating research quality and impact (e.g., Pure, Plum Analytics, Sci Val), identifying academic experts for potential employers (e.g., Expert Lookup5), managing the research networking platforms through which to collaborate (e.g., SSRN, Hivebench, Mendeley), managing the tools through which to find funding (e.g., Plum X, Mendeley, Sci Val), and controlling the platforms through which to analyze and store researchers' data (e.g., Hivebench, Mendeley). Since it has expanded beyond publishing, the vertical integration of privately owned infrastructures has become extensively integrated to daily research activities: "the privatised control of scholarly infrastructures is especially noticeable in the context of 'vertical integration' that publishers such as Elsevier and SpringerNature are seeking by controlling all aspects of the research lifecycle, from submission to publication and beyond". In contrast with publication, which was an outsourced business separated from institutional and community activities, the new services developed by large publishers are embedded in the infrastructure of universities and create potentially stronger dependency links: "Pure embeds Elsevier within the university workflow process through its abilities to manage research at the university level, including the provision of a dashboard to facilitate decision making by university research


id: economics-of-open-science-20260505-6
file: data/en.wikipedia.org/wiki/Economics_of_open_science-6.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T10:15:06.320001+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
==== The emergence of digital knowledge commons ==== Until the 1990s open knowledge was not considered as a commons in economic theory but as a "classic example of a pure public good, a good available to all and where one person's use does not subtract from another's use". For Elinor Ostrom and Charlotte Hess, this framework is no longer viable as the principle of non-excludability has been significantly weakened: "new technologies can enable the capture of what were once free and open public goods (...) Knowledge, which can seem so ubiquitous in digital form, is, in reality, more vulnerable than ever before" In a scientific context, examples of new enclosures of public goods may include all the surveillance data systems put in place by Elsevier, Springer or Academic social networks that capturate activities such as social interactions, reference collections. The uncontrolled development of the early web highlighted the need for common management of knowledge resources: "People started to notice behaviors and conditions on the web — congestion, free riding, conflict, overuse, and pollution — that had long been identified with other types of commons." The open access of the 1990s and early 2000s movement aimed to ensure that science will


id: economics-of-open-science-20260505-7
file: data/en.wikipedia.org/wiki/Economics_of_open_science-7.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T10:15:06.320001+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
==== Consolidation of the common ecosystem (2015-) ==== Since 2015, open science infrastructures, platforms and journals have converged to the creation of digital academic commons. While they were initially conceived either as a public good (a "grid" that ensure the distribution of a non-excludable resource) or a club good (with a limited range beyond a specific communities), open science infrastructures have been increasingly structured around a shared ecosystem of services and standards has emerged through the network of dependencies from one infrastructure to another. Open science infrastructures face similar issues met by other open institutions such as open data repositories or large scale collaborative project such as Wikipedia: "When we study contemporary knowledge infrastructures we find values of openness often embedded there, but translating the values of openness into the design of infrastructures and the practices of infrastructuring is a complex and contingent process". The conceptual definition of open science infrastructures has been largely influenced by the analysis of Elinor Ostrom on the commons and more specifically on the knowledge commons. In accordance with Ostrom, Cameron Neylon understates that open infrastructures are not only a public good characterized by the management of a pool of common resources but also by


id: economics-of-open-science-20260505-8
file: data/en.wikipedia.org/wiki/Economics_of_open_science-8.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T10:15:06.320001+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
=== Editorial work and evaluation === Editorial work and the management of peer review remain the core activity of academic journals and their most identified contribution and service rendered to scientific communities. It is the main expenses of the non-commercial journals surveyed by the OA Diamond Study: "the five main expenses/payables of the journal are editing (531), copy-editing (463), technical and software support (393), typesetting (384), and design (336)". Translation is a frequently quoted added cost, that may have been incentivicized by open science as the potential audience of local non-academic readers create incentives to maintain a multilingual website. Even before their conversion to electronic publishing, non-for-profits journals have maintained an affordable price, due to a nearly exclusive focus on editorial services: "in 2013, the mean price per article in for-profit journals was 3.2 times higher than in non-for-profit journals, and that the corresponding ratio for the median price per article was even 4.33:1". With Internet publication, costs can be significantly lower, due to additional cuts in transaction and labor costs, use of share platforms and infrastructure or reliance on voluntary work: "over 60% of journals reported annual costs in the previous year under $/€10,000, including in-kind contributions." In contrast


id: economics-of-open-science-20260505-9
file: data/en.wikipedia.org/wiki/Economics_of_open_science-9.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T10:15:06.320001+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
=== Commercial services and prestige === The overall price per article of commercial publishers is consistently higher than in the non-commercial sectors. This discrepancy has been partly accounted by the maintenance of several services necessary to run a business activity (pricing, transaction management, marketing...), that non-commercial structure can drop entirely with little impact. Leading commercial journals claim to be more selective in regard to article submissions, which has the effect of creating a more complex and time-consuming acceptation workflow: "The more effort a publisher invests in each paper, and the more articles a journal rejects after peer review, the more costly is each accepted article to publish [although] the key question is whether the extra effort adds useful value". Besides, "costs vary widely in this sector". Without any transformation of the editorial workflow or efficiency gain a standard well-established subscription journal could "charge about $3,700 per paper to cover costs". Yet, in a publisher like Nature, the costs would be "at £20,000–30,000 ($30,000–40,000) per paper". In the higher end of the commercial spectrum, cost per articles are more likely to embed services that are not directly related to publishing : "One possible reason for such variation between journals and publishers


id: economics-of-open-science-20260505-10
file: data/en.wikipedia.org/wiki/Economics_of_open_science-10.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T10:15:06.320001+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
=== Transaction costs === In a market economy, the diffusion of private goods is usually assorted with transactions costs. Theses costs cover all the services required to manage the commoditization of a product, both from the side of the producer as from the side of a consumer. In a wider sense, it encompasses all the work and time allocated all the stakeholders of the transactions to perform it, such as benchmarks, negotiations or contractualizations. Savings on transaction costs are frequently quoted as a significant advantage of non-excludable resource system (common good, public good) over private markets. Since access to the resource is weakly restrained and conditioned by unformal rules, its allocation is less costly overall: "a community could (...) produce better quality outcomes at lower economic costs, because of lower transaction costs, than alternative institutional systems involving private property" According to a 2017 OECD report, market allocation of open knowledge outputs is not sufficiently efficient: as the price of a public good converges to zero, any attempt at setting up a price will result in excessive exclusion and reduced collective benefits. The market may not be the best mechanism for the allocation of a public good, as any price above


id: economics-of-open-science-20260505-11
file: data/en.wikipedia.org/wiki/Economics_of_open_science-11.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T10:15:06.320001+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
=== Access costs === Access to pre-existent research outputs such as publications, datasets or code is a major condition of research. The subscription model used to rely on the assumptions that researchers only need to access a few specialized publications. In practice, research is more unpredictible and frequently rely crossing methods and observations from different fields or even different disciplines. In 2011, a survey of JISC showed that 68% of UK researchers felt they did have a sufficiently wide access to journal and conference papers. Non-academic professional audiences experience difficulties in accessing directly relevant research: "a quarter of those in industry/commerce described their current level of access as fairly/very difficult" as "the main barrier was unwillingness to pay". A survey of business use of research in Denmark highlighted a large range of strategies to avoid the high cost of pay-per-view, especially through collaboration with academics that have institutional access. The impact of open access is amplified by the high degree of internationalization of research: "83% of the economic return on cancer research is drawn from research from non-UK sources" which are less likely to be accessible in a subscription-based model. Beyond the extended coverage, Open science can enhance the efficiency


id: economics-of-open-science-20260505-12
file: data/en.wikipedia.org/wiki/Economics_of_open_science-12.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T10:15:06.320001+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
=== Research efficiency === Impacts of open science on research efficiency stem from the benefits of enhanced access to previous work. Due to the complexity of bibliography search, closed subscription system "can lead to high levels of duplication—that is, where separate teams work on the same thing unbeknownst to each other." The issue is not limited to academic research, but affect industrial R&D as well: "an analysis of pharmaceutical patents by 18 large companies showed that 86% of target compounds were investigated by two or more companies" Non-publication of data or intermediary results can also have cascading effects on the overall quality of research. Meta-analysis rely on the reproductibility of pre-existent observations and experiments to identify the scientific consensus on a specific topic or field of research. They can be affected by statistical errors and bias, as well as the pre-selection of statistically significant results. Extensive opening of final and intermediary data sources makes it easier to spot potential mistakes. Text and data mining projects have more recently become a major focus of studies on potential gain of research efficiency. In contrast with the standard procedures of state of the art, text mining projects process very large corpus and are


id: economics-of-open-science-20260505-13
file: data/en.wikipedia.org/wiki/Economics_of_open_science-13.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T10:15:06.320001+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
=== Economic and social development === The potential economic impact for open science research outputs is significant. Innovation commons are a major, although overlooked, source of economic growth: "The innovation commons is the true origin of innovation. It is the source from which the subsequent markers of innovation emerge — the entrepreneurial actors, the innovating firms, the new markets, and so on." Recent developments like the growth of data analytics services across a large variety of economic sectors have created further needs for research data: "There are many other values (...) that are promoted through the longterm stewardship and open availability of research data. The rapidly expanding area of artificial intelligence (AI) relies to a great extent on saved data." In 2019, the combined data market of the 27 countries of the European Union and the United Kingdom was estimated at 400 billion euros and had a sustained growth of 7.6% per year. although no estimation was given of the specific value of research data, research institutions were identified as important stakeholders in the emerging ecosystem of "data commons". In 2011, a JISC report estimated that there was 1.8 million knowledge workers in the United Kingdom working in R&D, IT,


id: economics-of-open-science-20260505-14
file: data/en.wikipedia.org/wiki/Economics_of_open_science-14.md
category: reference
title: Economics of open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Economics_of_open_science
date_saved: 2026-05-05T10:15:06.320001+00:00
instance: kb-cron
parent: economics-of-open-science-20260505-0
summary:
== Economic regulation of open science == Economic regulation of scientific publishing has long be stuck in a "collective action dilemma", due to the lack of coordinations between all stakeholders: "To truly reduce their costs, librarians would have to build a shared online collection of scholarly resources jointly managed by the academic community as a whole, but individual academic institutions lack the private incentives necessary to invest in a shared collection." Although it was initially expected by some economists, that the academic publishing markets would be structurally disrupted by new open access competitors, change was mostly driven by scientific communities, scientific institutions and, lately, coordinations of funders. In the 2000s, forms of regulation appear at a local scale to solve obvious market failure in the management of open science outuput. Development of research data repositories has been sustained by the implementation of "government or funder mandates for open data that require the producers of data to make them openly accessible". Mandates have been less easily expanded to other scientific outputs such as publications, that could not be covered by open data programs and were already invested by large commercial structures. In the great recession, scientific institutions and libraries had to


id: embargo-academic-publishing-20260505-0
file: data/en.wikipedia.org/wiki/Embargo_(academic_publishing)-0.md
category: reference
title: Embargo (academic publishing)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Embargo_(academic_publishing)
date_saved: 2026-05-05T10:15:07.515279+00:00
instance: kb-cron
parent: embargo-academic-publishing-20260505-0
summary:
In academic publishing, an embargo is a period during which access to academic journals is not allowed to users who have not paid for access (or have access through their institution). The purpose of this is to ensure publishers have revenue to support their activities, although the impact of embargoes on publishers is hotly debated, with some studies finding no impact while publisher experience suggests otherwise. A 2012 survey of libraries by the Association of Learned, Professional, and Society Publishers on the likelihood of journal cancellations in cases where most of the content was made freely accessible after six months suggests there would be a major negative impact on subscriptions, but this result has been debated. Various types exist: A 'moving wall' is a fixed period of months or years. A fixed date is a particular time point that does not change. A current year (or other period) is setting a time point on Jan. 1 of the current year, so that all material earlier than that is available. Although fixed during the year, it will change each year. == Purpose == There are various purposes: For delayed open access journals, the embargo separates the most recent period, for which


id: eprint-20260505-0
file: data/en.wikipedia.org/wiki/Eprint-0.md
category: reference
title: Eprint
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Eprint
date_saved: 2026-05-05T10:15:08.666512+00:00
instance: kb-cron
parent: eprint-20260505-0
summary:
In academic publishing, an eprint or e-print is a digital version of a research document (usually a journal article, but could also be a thesis, conference paper, book chapter, or a book) that is accessible online, usually as green open access, whether from a local institutional or a central digital repository. When applied to journal articles, the term "eprints" covers both preprints (before peer review) and postprints (after peer review). Digital versions of materials other than research documents are not usually called e-prints, but some other name, such as e-books. == See also == Electronic article Electronic journal Electronic publishing Open access Open science == References == == External links == What is an eprint? as defined in the FAQ section of eprints.org Eprints as defined by Stevan Harnad


id: fair-access-to-science-and-technology-research-act-20260505-0
file: data/en.wikipedia.org/wiki/Fair_Access_to_Science_and_Technology_Research_Act-0.md
category: reference
title: Fair Access to Science and Technology Research Act
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Fair_Access_to_Science_and_Technology_Research_Act
date_saved: 2026-05-05T10:15:09.839963+00:00
instance: kb-cron
parent: fair-access-to-science-and-technology-research-act-20260505-0
summary:
The Fair Access to Science and Technology Research Act (FASTR) is a bill in the United States that would mandate earlier public release of taxpayer-funded research. The bill has been introduced in 2013, 2015, and 2017. Sen. Ron Wyden (D-Ore.) and Sen. John Cornyn (R-Texas) introduced the Senate version, while the bill was introduced to the House by Reps. Zoe Lofgren (D-Calif.), Mike Doyle (D-Penn.) and Kevin Yoder (R-Kans.). The bill is a successor to the Federal Research Public Access Act (FRPAA), which had been introduced in 2006, 2010, and 2012. Senator Wyden advocated for the passage of the bill by arguing that "taxpayer funded research should never be hidden behind a paywall." FASTR has been described as "The Other Aaron's Law", named for open-access activist Aaron Swartz who died in a dramatic case in support of open access research in January 2013. The Senate Committee on Homeland Security and Governmental Affairs unanimously approved the bill on July 29, 2015. It was the first time that the bill or any of its predecessors had gained committee approval and been forwarded to a full house of Congress. The bill is often compared to and discussed in conjunction with the Public Access


id: federal-research-public-access-act-20260505-0
file: data/en.wikipedia.org/wiki/Federal_Research_Public_Access_Act-0.md
category: reference
title: Federal Research Public Access Act
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Federal_Research_Public_Access_Act
date_saved: 2026-05-05T10:15:11.008884+00:00
instance: kb-cron
parent: federal-research-public-access-act-20260505-0
summary:
The Federal Research Public Access Act (FRPAA) is a proposal to require open public access to research funded by eleven U.S. federal government agencies. It was originally proposed by Senators John Cornyn and Joe Lieberman in 2006 and then again in 2010, and then once more in 2012. A later version of the bill, the Fair Access to Science and Technology Research Act, was introduced in 2013, 2015 and 2017. == Provisions of bill == The FRPAA would require that those eleven agencies with research expenditures over $100 million, create online repositories of journal articles of the research completed by that agency and make them publicly available. They must be maintained and preserved by the agency, or another repository that permits free and open access. It must be available to users without charge within six months after it has been published in a peer-reviewed journal. The agencies included in this bill are: Department of Agriculture Department of Commerce Department of Defense Department of Education Department of Energy Department of Health and Human Services Department of Homeland Security Department of Transportation Environmental Protection Agency National Aeronautics and Space Administration National Science Foundation == Legislative history == == Reaction == === Support


id: force11-20260505-0
file: data/en.wikipedia.org/wiki/FORCE11-0.md
category: reference
title: FORCE11
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/FORCE11
date_saved: 2026-05-05T10:15:12.231934+00:00
instance: kb-cron
parent: force11-20260505-0
summary:
FORCE11 is an international coalition of researchers, librarians, publishers and research funders working to reform or enhance the research publishing and communication system. Initiated in 2011 as a community of interest on scholarly communication, FORCE11 is a registered 501(c)(3) organization based in the United States but with members and partners around the world. Key activities include an annual conference, the Scholarly Communications Institute and a range of working groups. == History == FORCE11 grew out of the FORC Workshop held in Dagstuhl, Germany in August 2011. This meeting resulted in the collaborative creation of a white paper which summarized the problems of scholarly communication and proposed a vision to address them. == Activities == Through various working groups FORCE11 has undertaken a range of activities to improve the standards, interoperability and functionality of digital research communications and developed various statements on principles and policies for best practice. These include: FAIR Data Principles: The development of a set of principles based on making data Findable, Accessible, Interoperable, and Reusable (FAIR) Research Resource Identification Initiative (RRID): supporting new guidelines and identifiers in biomedical publications Joint Declaration of Data Citation Principles (JDDCP): intended to help achieve widespread, uniform human and machine accessibility of


id: free-journal-network-20260505-0
file: data/en.wikipedia.org/wiki/Free_Journal_Network-0.md
category: reference
title: Free Journal Network
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Free_Journal_Network
date_saved: 2026-05-05T10:15:13.437879+00:00
instance: kb-cron
parent: free-journal-network-20260505-0
summary:
The Free Journal Network is an index of open access scholarly journals, specifically for those that do not charge article processing charges. == Criteria == The network founded in early 2018 in order to promote free, open access journals, a publishing model that is sometimes called diamond or platinum open access. Such journals are typically smaller than equivalent commercial journals (often supported by academic societies). Main criteria include: adherence to the Fair Open Access Principles that are publicly supported by many renowned scientists, publication of article titles and abstracts in English, clear publication ethics and quality assurance policies. == FJN Member Journals == As of November 2024, there are 90 journals that have been accepted into the Free Journal Network. Some notable examples include: Discrete Analysis European Journal of Taxonomy Glossa Journal of Open Source Software Journal of Political Ecology Norwegian Journal of Geology SciPost Physics Volcanica == See also == Directory of Open Access Journals Open Access Scholarly Publishers Association == References == == External links == Official website


id: toby-green-publisher-20260505-0
file: data/en.wikipedia.org/wiki/Toby_Green_(publisher)-0.md
category: reference
title: Toby Green (publisher)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Toby_Green_(publisher)
date_saved: 2026-05-05T10:15:15.693892+00:00
instance: kb-cron
parent: toby-green-publisher-20260505-0
summary:
Toby Green is a scholarly publisher who has worked with Academic Press, Applied Science Publishers, Pergamon Press, Elsevier Science, and the Organisation for Economic Co-operation and Development (OECD). At OECD, Green launched important digital publishing initiatives such as SourceOECD (2001), its successor the OECD iLibrary (2010), and the OECD Better Life Index (2011). In 2017, OECD Publishing won the Academic and Professional Publisher Award from The London Book Fair. Green has chaired the Council of the Association of Learned and Professional Society Publishers (ALPSP, 2010) and served on the publishing board of the Royal Society of Chemistry and the board of Annual Reviews. In 2019, Green co-founded Coherent Digital to improve access to grey literature policy documents from IGOs, NGOs, research centers and think tanks. == Early life and education == Green was born in Broadwindsor, Dorset, England and educated at Marlborough College. He attended the University of Warwick in Coventry, receiving a BSc in Microbiology and Virology in 1980. == Career == Toby Green is a scholarly publisher who has worked with a wide range of organizations, publishing content for commercial organizations, scholarly societies, intergovernmental organizations (IGOs) and nongovernmental organizations (NGOs). Since 1982, Green has worked for Academic Press


id: grey-literature-network-service-20260505-0
file: data/en.wikipedia.org/wiki/Grey_Literature_Network_Service-0.md
category: reference
title: Grey Literature Network Service
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Grey_Literature_Network_Service
date_saved: 2026-05-05T10:15:16.890978+00:00
instance: kb-cron
parent: grey-literature-network-service-20260505-0
summary:
GreyNet International, the Grey Literature Network Service, is an independent organization founded in 1992. It is dedicated to research, publication, open access, education, and bringing public awareness to grey literature. Grey literature is often defined as "Information produced and distributed on all levels of government, academics, business and industry in electronic and print formats not controlled by commercial publishing i.e. where publishing is not the primary activity of the producing body." GreyNet is corporate author of the Proceeding issues from the International Conference Series on Grey Literature, The Grey Journal, An International Journal on Grey Literature, as well as other types of publications such as reports, program books, and newsletters. GreyNet also maintains a Listserv and a presence on a number of social media including LinkedIn, Netvibes, Twitter, and Facebook. GreyNet is a not for profit organization fostering the production and dissemination of scientific literature. It is also engaged in the open source movement and was invited to the 10th Libre Software Meeting 2009 in Nantes, France, with a communication on knowledge sharing in the field of grey literature. During the 11th International Conference on Grey Literature in December 2009, GreyNet signed a Partnership Agreement with ICSTI, International Council for


id: grey-literature-network-service-20260505-1
file: data/en.wikipedia.org/wiki/Grey_Literature_Network_Service-1.md
category: reference
title: Grey Literature Network Service
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Grey_Literature_Network_Service
date_saved: 2026-05-05T10:15:16.890978+00:00
instance: kb-cron
parent: grey-literature-network-service-20260505-0
summary:
== GreyNet and the OpenGrey Repository == For the past 20 years, GreyNet has sought to serve researchers and authors in the field of grey literature. To further this end, GreyNet has signed on to the OpenGrey repository and in so doing seeks to preserve and make openly available research results originating in the International Conference Series on Grey Literature. GreyNet together with INIST-CNRS have designed the format for a metadata record, which encompasses standardized PDF attachments of the full-text conference preprints, PowerPoint presentations, abstracts, biographical notes, and post-publication commentaries. GreyNet's collection of over 270 conference preprints is both current and comprehensive. Comment from Peter Suber, Open Access News (Thursday, January 29, 2009): GreyNet started making its conference proceedings OA through its repository in May 2008. I applaud its determination to complete the collection retroactively, even if it means buying permission from a publisher. Note to other conference organizers: This is a reason to self-archive your proceedings as you go, or at least to retain the right to self-archive them without a fee. == GreyNet and the DANS Data Archive == GreyNet’s research data is cross-linked to the corresponding conference preprint in OpenGrey via the DANS Data Archive. In this


id: grey-literature-network-service-20260505-2
file: data/en.wikipedia.org/wiki/Grey_Literature_Network_Service-2.md
category: reference
title: Grey Literature Network Service
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Grey_Literature_Network_Service
date_saved: 2026-05-05T10:15:16.890978+00:00
instance: kb-cron
parent: grey-literature-network-service-20260505-0
summary:
== Bibliography == Farace D. & Schöpfel J. (eds.) (2010). Grey Literature in Library and Information Studies. De Gruyter Saur. Schöpfel J., Stock C., Farace D.J., Frantzen J. Citation Analysis and Grey Literature: Stakeholders in the Grey Circuit. The Grey Journal 2005, vol. 1, n° 1, p. 31-40. hdl:10068/697850 Farace D., Frantzen J., Schöpfel J., Stock C. Knowledge Generation in the Field of Grey Literature: A Review of Conference-based Research Results]. GL8 Conference Proceedings. Eighth International Conference on Grey Literature: Harnessing the Power of Grey. New Orleans, 4–5 December 2006. hdl:10068/697768 Farace D.J., Frantzen J., Schöpfel J., Stock C. Grey Literature: A Pilot Course constructed and implemented via Distance Education. The Grey Journal 2008, vol. 4, n° 1, p. 41-45. hdl:10068/697878 Farace D., Frantzen J., Schöpfel J., Stock C., Henrot N. OpenSIGLE, Home to GreyNet’s Research Community and its Grey Literature Collections: Initial Results and a Project Proposal. GL10 Conference Proceedings. Tenth International Conference on Grey Literature: Designing the Grey Grid for Information Society. Amsterdam, 8–9 December 2008. Gelfand J. Interview with Dominic Farace, founder of GreyNet. International Journal on Grey Literature. 2000, vol. 1, n° 2, p. 73-76. Covers how Dominic Farace, the GreyNet director, first became involved in


id: guerilla-open-access-manifesto-20260505-0
file: data/en.wikipedia.org/wiki/Guerilla_Open_Access_Manifesto-0.md
category: reference
title: Guerilla Open Access Manifesto
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Guerilla_Open_Access_Manifesto
date_saved: 2026-05-05T10:15:18.127551+00:00
instance: kb-cron
parent: guerilla-open-access-manifesto-20260505-0
summary:
The Guerilla Open Access Manifesto is a document published by (and widely attributed to) Aaron Swartz in 2008 that argues for transgressive approaches to achieving the goals of the open access movement through civil disobedience, willful violation of copyright and contracts that restrict redistribution of knowledge, and activities that exist in legal grey areas. The goal of the open access movement taken up by the manifesto include the removal of barriers and paywalls that prohibit the general public from accessing scientific research publications and other forms of data. While most of the open access movement has focused on standing up new open access publishers, working with traditional publishers to switch to open access, and organizing scholars who produce and edit articles, these focuses primarily affect the accessibility of future publications. The manifesto is largely concerned with the existing proprietary articles and data that are unlikely to be released as open access by the current copyright holders. The manifesto appears to have been written in 2008 at a meeting of librarians and was subsequently published on Swartz's personal blog. Although the authorship of the document is widely attributed to Swartz, his role in writing the manifesto and the degree to which


id: guerilla-open-access-manifesto-20260505-1
file: data/en.wikipedia.org/wiki/Guerilla_Open_Access_Manifesto-1.md
category: reference
title: Guerilla Open Access Manifesto
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Guerilla_Open_Access_Manifesto
date_saved: 2026-05-05T10:15:18.127551+00:00
instance: kb-cron
parent: guerilla-open-access-manifesto-20260505-0
summary:
== Text of the Manifesto == Information is power. But like all power, there are those who want to keep it for themselves. The world's entire scientific and cultural heritage, published over centuries in books and journals, is increasingly being digitized and locked up by a handful of private corporations. Want to read the papers featuring the most famous results of the sciences? You'll need to send enormous amounts to publishers like Reed Elsevier. There are those struggling to change this. The Open Access Movement has fought valiantly to ensure that scientists do not sign their copyrights away but instead ensure their work is published on the Internet, under terms that allow anyone to access it. But even under the best scenarios, their work will only apply to things published in the future. Everything up until now will have been lost. That is too high a price to pay. Forcing academics to pay money to read the work of their colleagues? Scanning entire libraries but only allowing the folks at Google to read them? Providing scientific articles to those at elite universities in the First World, but not to children in the Global South? It's outrageous and unacceptable. "I agree,"


id: hybrid-open-access-journal-20260505-0
file: data/en.wikipedia.org/wiki/Hybrid_open-access_journal-0.md
category: reference
title: Hybrid open-access journal
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Hybrid_open-access_journal
date_saved: 2026-05-05T10:15:19.297877+00:00
instance: kb-cron
parent: hybrid-open-access-journal-20260505-0
summary:
A hybrid open-access journal is a subscription journal in which some of the articles are open access. This status typically requires the payment of a publication fee (also called an article processing charge or APC) to the publisher in order to publish an article open access, in addition to the continued payment of subscriptions to access all other content. Strictly speaking, the term "hybrid open-access journal" is incorrect, possibly misleading, as using the same logic such journals could also be called "hybrid subscription journals". Simply using the term "hybrid access journal" is accurate. Publishers that offer a hybrid open access option often use different names for it. The SHERPA/RoMEO site provides a list of publishers and the names of their options. The Open Access Directory provides a list of funds that support open access journals, and provides information about which funds will pay fees for hybrid open access journals. == Origins == The concept was first proposed in 1998 when Thomas Walker suggested that authors could purchase extra visibility at a price. The first journal recognized as using this model was Walker's own Florida Entomologist; it was later extended to the other publications of the Entomological Society of America. The


id: institutional-repository-20260505-0
file: data/en.wikipedia.org/wiki/Institutional_repository-0.md
category: reference
title: Institutional repository
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Institutional_repository
date_saved: 2026-05-05T10:15:20.491930+00:00
instance: kb-cron
parent: institutional-repository-20260505-0
summary:
An institutional repository (IR) is an archive for collecting, preserving, and disseminating digital copies of the intellectual output of an institution, particularly a research institution. Academics also utilize their IRs for archiving published works to increase their visibility and collaboration with other academics. However, most of these outputs produced by universities are not effectively accessed and shared by researchers and other stakeholders. As a result academics should be involved in the implementation and development of an IR project so that they can learn the benefits and purpose of building an IR. An institutional repository has been defined as "a set of services that a university offers to members of its community for the management and dissemination of digital materials created by the institution and its community members." For a university, this includes materials such as monographs, eprints of academic journal articles—both before (preprints) and after (postprints) undergoing peer review—as well as electronic theses and dissertations (ETDs). An institutional repository might also include other digital assets generated by academics, such as datasets, administrative documents, course notes, learning objects, academic posters or conference proceedings. Deposit of material in an institutional repository is sometimes mandated by an institution. Some of the main objectives


id: iowa-state-university-digital-press-20260505-0
file: data/en.wikipedia.org/wiki/Iowa_State_University_Digital_Press-0.md
category: reference
title: Iowa State University Digital Press
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Iowa_State_University_Digital_Press
date_saved: 2026-05-05T10:15:21.684131+00:00
instance: kb-cron
parent: iowa-state-university-digital-press-20260505-0
summary:
The Iowa State University Digital Press (also known as ISUDP) is a digital university press affiliated with Iowa State University, located in Ames, Iowa. The press, which is a unit of the Iowa State University Library, was organized in 2018 and is dedicated to the creation, publication, and dissemination of open-access books and journal articles. Often seen as a successor of sorts to the Iowa State University Press (a now-defunct publisher that had previously been an active member of the Association of American University Presses), the Iowa State University Digital Press was founded to "support of Iowa State University’s land-grant mission." The publisher is currently a member of the Library Publishing Coalition. == Publications == === Notable journals === Journal of Librarianship and Scholarly Communication Journal of Technology, Management, and Applied Engineering Meat and Muscle Biology === Notable proceedings === International Interactive Symposium on Ultra-High Performance Concrete International Textile and Apparel Association Annual Conference Proceedings Pronunciation in Second Language Learning and Teaching Proceedings == See also == List of English-language book publishing companies List of university presses == References == == External links == Official website Pressbooks website


id: jairo-20260505-0
file: data/en.wikipedia.org/wiki/JAIRO-0.md
category: reference
title: JAIRO
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/JAIRO
date_saved: 2026-05-05T10:15:24.024520+00:00
instance: kb-cron
parent: jairo-20260505-0
summary:
JAIRO (ジャイロ), which stands for Japanese Institutional Repositories Online, is a web-based search interface that provides aggregated open access to Japanese academic content, including journal articles, theses, research bulletins, and reports. It is administered by Japan's National Institute of Informatics (NII). == History == A beta version of JAIRO was launched on October 22, 2008, and its official opening was on April 1 of the following year. JAIRO began as the JuNii+ service, which operated from May 2007 until March 2009. As of September 30, 2015, nearly 1.6 million full-text documents were accessible through JAIRO. == External links == Official website == References ==


id: lever-press-20260505-0
file: data/en.wikipedia.org/wiki/Lever_Press-0.md
category: reference
title: Lever Press
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Lever_Press
date_saved: 2026-05-05T10:15:26.351094+00:00
instance: kb-cron
parent: lever-press-20260505-0
summary:
Lever Press is a university press, based out of Ann Arbor, MI. Though founded in 2016 with the help of Michigan Publishing, Amherst College Press, and the Oberlin Group, Lever Press is not affiliated with a single university. Instead, it represents a consortium of universities, each of which helps govern and guide the press. All publications issued by the press are released as open access works, with the cost of production being paid for by the participating universities. The press is a member of the Association of University Presses. == Participating institutions == Participating institutions include the following: == See also == List of English-language book publishing companies List of university presses University of Michigan Library University of Michigan Press == References == == External links == Lever Press homepage


id: library-publishing-20260505-0
file: data/en.wikipedia.org/wiki/Library_publishing-0.md
category: reference
title: Library publishing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Library_publishing
date_saved: 2026-05-05T10:15:27.537799+00:00
instance: kb-cron
parent: library-publishing-20260505-0
summary:
Library publishing, also known as campus-based publishing, is the practice of an academic or public library providing publishing services. == Concept == A library publishing service usually publishes academic journals and often provides a broader range of publishing services as well. This can include publishing other formats such as scholarly monographs and conference proceedings. It generally has a preference for open access publishing. Library publishing often focuses on electronic publishing rather than print, thus complementing the role of traditional academic presses. Sometimes a library and a university press based at the same institution will form a partnership, with each focusing on their own area of expertise. For example, the University of Pittsburgh library publishing service publishes peer-reviewed journals and also collaborates with the university press to publish open access monographs. Software is available to manage the journal publication process. The open source Open Journal Systems by the Public Knowledge Project, and Digital Commons' bepress, are both widely used by library publishing services. Some libraries use Open Journal Systems to create overlay journals which present scholarly content that is held in an institutional repository. == History == Library publishing has a long history and has been around since before the Internet.


id: list-of-academic-publishers-by-preprint-policy-20260505-0
file: data/en.wikipedia.org/wiki/List_of_academic_publishers_by_preprint_policy-0.md
category: reference
title: List of academic publishers by preprint policy
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_academic_publishers_by_preprint_policy
date_saved: 2026-05-05T10:15:28.763243+00:00
instance: kb-cron
parent: list-of-academic-publishers-by-preprint-policy-20260505-0
summary:
This is a list of publishers of academic journals by their submission policies regarding the use of preprints prior to publication (example list). Publishers' policies on self-archiving (including of preprint versions) can also be found at SHERPA/RoMEO. == Policies by publisher == Submission of preprints is accepted by all open access journals. Over the last decade, they have been joined by most subscription journals, however publisher policies are often vague or ill-defined. In general, most publishers that permit preprints require that: the authors disclose the existence of the preprint at submission (e.g. in the cover letter) once an article is published, the preprint should link to the published version (typically via DOI) the preprint should not have been formally peer reviewed Publishers may place additional restrictions (e.g. specifying non-commercial servers or preferred licenses). Most publishers have a unified policy across all of their journals, however some journals list exceptions in their own policies. == See also == Copyright policies of academic publishers Ingelfinger rule List of open-access journals List of preprint repositories List of research funders by preprint licensing policy == References == == External links == SHERPA/RoMEO - a list of publisher policies on copyright, preprints, and self-archiving


id: malamud-decision-20260505-0
file: data/en.wikipedia.org/wiki/Malamud_decision-0.md
category: reference
title: Malamud decision
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Malamud_decision
date_saved: 2026-05-05T10:15:29.928284+00:00
instance: kb-cron
parent: malamud-decision-20260505-0
summary:
In the Malamud decision, the European Court of Justice (ECJ) held on 5 March 2024 in Case C-588/21 P that there may be an overriding public interest in the dissemination of harmonised European standards. == Background == Carl Malamud had requested access to several European standards for his organisation public.resource.org. The European Commission refused to make the requested European standards for toy safety available free of charge, whereupon Malamud filed a lawsuit. The ECJ ruled that those harmonised technical standards (HTN) that are mandatory are part of Union law. As the principle of the rule of law requires free access to Union law, these standards must be accessible free of charge. However, the Court did not generally rule out copyright protection for harmonised standards. Free access to some harmonised standards is now possible after registration, see Access to documents == References ==


id: mega-journal-20260505-0
file: data/en.wikipedia.org/wiki/Mega_journal-0.md
category: reference
title: Mega journal
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Mega_journal
date_saved: 2026-05-05T10:15:31.098887+00:00
instance: kb-cron
parent: mega-journal-20260505-0
summary:
A mega journal (also mega-journal and megajournal) is a peer-reviewed academic open access journal designed to be much larger than a traditional journal by exercising low selectivity among accepted articles. It was pioneered by PLOS ONE. This "very lucrative publishing model" was soon emulated by other publishers. == Definition == A mega journal has the following defining characteristics: broad coverage of different subject areas; accepting articles for publication based on whether they are technically sound rather than selecting for perceived importance; and using article processing charges to cover the costs of publishing, although it is also possible for a mega journal to function as a non-profit (one example is Open Library of Humanities). Other less universal characteristics are "an accelerated review and publication process", "fast turnaround time"; "academic editors", even "a large editorial board of academic editors", (instead of professional editors); and value-added services such as reusable graphics and data through Creative Commons licenses. Mega journals are also online-only, with no printed version, and are fully open access, in contrast to hybrid open access journals. Some "predatory" open access publishers use the mega journal model. == Influence == It has been suggested that the academic journal landscape might become dominated


id: open-access-monograph-20260505-0
file: data/en.wikipedia.org/wiki/Open-access_monograph-0.md
category: reference
title: Open-access monograph
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open-access_monograph
date_saved: 2026-05-05T10:15:32.297651+00:00
instance: kb-cron
parent: open-access-monograph-20260505-0
summary:
An open-access monograph (open-access book or OA book) is a scholarly publication usually made openly available online with an open license. These books are freely accessible to the public, typically via the internet. They are part of the open access movement. == Concept == Open access is when academic research is made freely available online for anyone to read and re-use. As with open access journals, there are different business models for funding open-access books, including publication charges, institutional support, library publishing, and consortium models. Some publishers, like OECD Publishing, uses a freemium model where the ebook version is made available for free, but readers have the option to purchase a print copy. Sales of the print version subsidise the cost of producing the book. There is some evidence that making electronic editions of books open access can increase sales of the print edition. == History == While open access to journal articles has become very common, with 50% of articles published in 2011 available as open access, open access to books has not yet seen as much uptake at this time. However, some dedicated open-access book publishers, such as Open Book Publishers, Punctum Books, and others who publish both


id: narcis-20260505-0
file: data/en.wikipedia.org/wiki/NARCIS-0.md
category: reference
title: NARCIS
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/NARCIS
date_saved: 2026-05-05T10:15:33.491076+00:00
instance: kb-cron
parent: narcis-20260505-0
summary:
NARCIS (National Academic Research and Collaboration Information System) of the Netherlands was an online portal for searching Dutch scientific research publications and data. As of July 2018, NARCIS indexed 268,989 data sets and 1,707,486 publications, including a significant proportion of open access works. It started in 2004 as a project of the Koninklijke Nederlandse Akademie van Wetenschappen, Information Centre of the Radboud University of Nijmegen (METIS), Nederlandse Organisatie voor Wetenschappelijk Onderzoek, and Vereniging van Universiteiten. Since 2011 the Data Archiving and Networked Services (DANS) operated NARCIS from headquarters in The Hague. In 2015, it was decided to replace the Digital Author Identifier used until then with the International Standard Name Identifier or ORCID. As of 3 July 2023, the portal has been decommissioned. == See also == Open access in the Netherlands == References == == Further reading == Elly Dijk; et al. (2006), NARCIS: The Gateway to Dutch Scientific Information (PDF), Proceedings ELPUB2006 Conference on Electronic Publishing, Bansko, Bulgaria == External links == Official site "Science and Technology Government Information Sources: International: Netherlands", ACRL Wiki, US: American Library Association's Association of College and Research Libraries (includes NARCIS)


id: open-access-button-20260505-0
file: data/en.wikipedia.org/wiki/Open_Access_Button-0.md
category: reference
title: Open Access Button
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Access_Button
date_saved: 2026-05-05T10:15:35.759722+00:00
instance: kb-cron
parent: open-access-button-20260505-0
summary:
The Open Access Button was a browser bookmarklet which registers when people hit a paywall to an academic article and cannot access it. It is supported by Medsin UK and the Right to Research Coalition. A prototype was built at a BMJ Hack Weekend. All code is openly available online at GitHub. A beta version of the Open Access Button was officially launched on 18 November 2013 at the Berlin 11 Satellite Conference for Students & Early Stage Researchers. It records instances of hitting a paywall, and also provides options to try to locate an open access version of the article. In April 2014 a crowdfunding campaign was started to build a second version. The second version of the button was launched on 21 October 2014 as part of Open Access Week. In February 2015 the Open Access Button and its co-founders, David Carroll and Joseph McArthur ("the button boys"), were awarded a SPARC Innovator Award by the Scholarly Publishing and Academic Resources Coalition (SPARC). The third version of the button was launched on 28 October 2016, again, as part of open access week. On September 18, 2025 OA.Works shut down the project. == See also == 12ft Anna's Archive


id: open-access-citation-advantage-20260505-0
file: data/en.wikipedia.org/wiki/Open_access_citation_advantage-0.md
category: reference
title: Open access citation advantage
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_access_citation_advantage
date_saved: 2026-05-05T10:15:36.958647+00:00
instance: kb-cron
parent: open-access-citation-advantage-20260505-0
summary:
Open access citation advantage (OACA) is a type of bias whereby scholars tend to cite academic journals with open access (OA)—that is, journals that make their full text available on the Internet without charge and not behind a paywall—in preference to toll-access publications. The concept was first introduced under the name FUTON bias ("full text on the net") by UK medical researcher Reinhard Wentz in a letter to The Lancet in 2002. Scholars in some fields can more easily discover and access articles whose full text is available online, which increases authors' likelihood of reading and citing these articles, an issue that was first raised and has been mainly studied in connection with medical research. In the context of evidence-based medicine, articles in expensive journals that do not provide open access may be "priced out of evidence", giving a greater weight to open access publications. Open access citation advantage may increase the impact factor of open access journals relative to journals without open access. One study concluded that authors in medical fields "concentrate on research published in journals that are available as full text on the internet, and ignore relevant studies that are not available in full text, thus introducing


id: open-access-mandate-20260505-0
file: data/en.wikipedia.org/wiki/Open-access_mandate-0.md
category: reference
title: Open-access mandate
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open-access_mandate
date_saved: 2026-05-05T10:15:38.169520+00:00
instance: kb-cron
parent: open-access-mandate-20260505-0
summary:
An open-access mandate is a policy adopted by a research institution, research funder, or government which requires or recommends researchers—usually university faculty or research staff and/or research grant recipients—to make their published, peer-reviewed journal articles and conference papers open access (1) by self-archiving their final, peer-reviewed drafts in a freely accessible institutional repository or disciplinary repository ("Green OA") or (2) by publishing them in an open-access journal ("Gold OA") or both. == Characteristics == Among the universities that have adopted open-access mandates for faculty are Harvard University, Massachusetts Institute of Technology, University College London, Queensland University of Technology, University of Minho (Portugal), University of Liège and ETH Zürich. Among the funding organizations that have adopted open-access mandates for grant recipients are National Institutes of Health (with the NIH Public Access Policy), Research Councils UK, National Fund for Scientific Research, Wellcome Trust and European Research Council. For a full index of institutional and funder open-access mandates adopted to date, see the Registry of Open Access Mandatory Archiving Policies (ROARMAP). Open-access mandates can be classified in many ways: by the type of mandating organization (employing institution or research funder), by the locus (institutional or institution-external) and timing of deposit itself (immediate, delayed),


id: open-access-mandate-20260505-1
file: data/en.wikipedia.org/wiki/Open-access_mandate-1.md
category: reference
title: Open-access mandate
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open-access_mandate
date_saved: 2026-05-05T10:15:38.169520+00:00
instance: kb-cron
parent: open-access-mandate-20260505-0
summary:
=== Canadian funding agencies === The Canadian Institutes of Health Research (CIHR) proposed a mandate in 2006 and adopted it in September 2007, becoming the first North American public research funder to do so. The CIHR Policy on Access to Research Outputs provides two options to researchers: publication in open access journals, and making their manuscripts available in an online central (PubMed Central Canada is recommended) or institutional repository. In October 2013, the two other Canadian federal funding agencies, the National Science and Engineering Council (NSERC) and the Social Science and Humanities Research Council (SSHRC) jointly proposed the same mandate as CIHR's, and launched a two-month consultation on what will become the Tri-Agency Open Access Policy. On 27 February 2015 a Tri-Agency Open Access Policy on Publications was announced. Peer-reviewed journal publications arising from Agency-supported research must be made freely available within 12 months of publication, whether by depositing in an online repository or by publishing in a journal that offers immediate or delayed open access. The policy is effective for grants awarded from 1 May 2015 onward. On 1 May 2015 the International Development Research Centre adopted a new open access policy. Books and journal articles must be made


id: open-access-mandate-20260505-2
file: data/en.wikipedia.org/wiki/Open-access_mandate-2.md
category: reference
title: Open-access mandate
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open-access_mandate
date_saved: 2026-05-05T10:15:38.169520+00:00
instance: kb-cron
parent: open-access-mandate-20260505-0
summary:
For the four institutions with the oldest self-archiving mandates, the averaged percentage of green open-access self-archiving has been compared to the percentage for control articles from other institutions published in the same journals (for years 2002–2009, measured in 2011). Open-access mandates triple the percent Green OA (see figure below). Respective totals are derived from the Thomson Reuters Web of Science. === Tracking mandates === As of May 2015, open-access mandates have been adopted by over 550 universities and research institutions, and over 140 research funders worldwide. Examples of universities which have open-access mandates are Harvard University and MIT in the United States, University College London in the UK and ETH Zürich in Europe. Funders which require open access when their funding recipients publish include the NIH in the US and RCUK and ERC in the EU. Mandate policy models and guidance have been provided by the Open Society Institute's EPrints Handbook, EOS, OASIS and Open Access Archivangelism. ROARMAP, the searchable Registry of Open Access Repository Mandates and Policies at the University of Southampton indexes the world's institutional, funder and governmental OA mandates (and the Open Access Scholarly Information Sourcebook (OASIS) as well as EnablingOpenScholarship (EOS) graph the quarterly outcome). SHERPA/JULIET


id: open-access-mandate-20260505-3
file: data/en.wikipedia.org/wiki/Open-access_mandate-3.md
category: reference
title: Open-access mandate
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open-access_mandate
date_saved: 2026-05-05T10:15:38.169520+00:00
instance: kb-cron
parent: open-access-mandate-20260505-0
summary:
==== Harvard University ==== On February 12, 2008, the Faculty of Arts and Sciences of Harvard University approved their Open Access Policy, granting to the President and Fellows of Harvard to "make available his or her scholarly articles and to exercise the copyright in those articles ... in a nonexclusive, irrevocable, paid-up, worldwide license..." Since then, several other schools within the University now participate in the Open Access Policies supported by the Office for Scholarly Communication: the Graduate School of Design, the School of Education, the Business School, the Law School, the Kennedy School of Government, the Divinity School, and the School of Public Health. The University's open-access repository is called DASH (Digital Access to Scholarship at Harvard) which is where the faculty upload their scholarly articles for access by all. ==== Massachusetts Institute of Technology ==== Adopted by a unanimous vote on March 18, 2009, the Massachusetts Institute of Technology (MIT) Faculty adopted an open access policy. The policy applies to "all scholarly articles written while the person is a member of the Faculty except for any articles completed before the adoption of this policy and any articles for which the Faculty member entered into an incompatible licensing or


id: open-access-mandate-20260505-4
file: data/en.wikipedia.org/wiki/Open-access_mandate-4.md
category: reference
title: Open-access mandate
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open-access_mandate
date_saved: 2026-05-05T10:15:38.169520+00:00
instance: kb-cron
parent: open-access-mandate-20260505-0
summary:
==== University of Kansas ==== In 2005 the University of Kansas (KU) created KU ScholarWorks, a digital repository for scholarly work created by KU faculty and staff. Faculty Senate President Lisa Wolf-Wendel, professor of education leadership and policy studies, approved a new policy, "Open Access Policy for University of Kansas Scholarship" on April 30, 2009, in order to provide the broadest possible access to the journal literature authored by KU faculty." In June 2009, under a faculty-initiated policy approved by Chancellor Robert Hemenway, KU became the first U.S. public university to implement an open access policy. Unless a KU author sought a waiver, all articles must be submitted to KU ScholarWorks. "Processes to Implement the KU Open Access Policy Archived 23 September 2020 at the Wayback Machine" were endorsed by the Faculty Senate in February 2010. Theses and dissertations at the University of Kansas are also openly available, however in 2010 KU Graduate Studies established a policy that a student may request permission to embargo its publication for six months, one year or two years. Graduates earning the KU Master of Fine Arts in Creative Writing or PhD in English (Literature and Creative Writing track) may request a permanent embargo.


id: open-access-scholarly-publishing-association-20260505-0
file: data/en.wikipedia.org/wiki/Open_Access_Scholarly_Publishing_Association-0.md
category: reference
title: Open Access Scholarly Publishing Association
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Access_Scholarly_Publishing_Association
date_saved: 2026-05-05T10:15:39.330669+00:00
instance: kb-cron
parent: open-access-scholarly-publishing-association-20260505-0
summary:
The Open Access Scholarly Publishing Association (OASPA) is a non-profit trade association of open access journal and book publishers. Having started with an exclusive focus on open access journals, it has since expanded its activities to include matters pertaining to open access books and open scholarly infrastructure. == History == The OASPA was launched on October 14, 2008 at an "Open Access Day" celebration in London hosted by the Wellcome Trust. The following organizations are founding members: The OASPA faced some criticism for a perceived conflict between its self-declared role as the "stamp of quality for open access publishing" and the application of its own criteria for membership. One member organization, Frontiers Media, was included on Jeffrey Beall's list of predatory open access publishing companies. Two members, Hindawi and MDPI - initially called predatory by Beall - were later removed from his list after pressure was applied to his employer. There was also concern around the fact that OASPA had been founded by BioMed Central and other open access publishers, which would cause a conflict of interest in their "seal of approval". OASPA has also been criticized for promoting gold open access in a way that may be at the


id: open-access-repository-20260505-0
file: data/en.wikipedia.org/wiki/Open-access_repository-0.md
category: reference
title: Open-access repository
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open-access_repository
date_saved: 2026-05-05T10:15:41.663023+00:00
instance: kb-cron
parent: open-access-repository-20260505-0
summary:
An open repository or open-access repository is a digital platform that holds research output and provides free, immediate and permanent access to research results for anyone to use, download and distribute. To facilitate open access such repositories must be interoperable according to the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH). Search engines harvest the content of open access repositories, constructing a database of worldwide, free of charge available research. Data repositories are the cornerstone for FAIR (findable, accessible, interoperable and reusable) data practices and are used expeditiously within the scientific community. Open-access repositories, such as an institutional repository or disciplinary repository, provide free access to research for users outside the institutional community and are one of the recommended ways to achieve the open access vision described in the Budapest Open Access Initiative definition of open access. This is sometimes referred to as the self-archiving or "green" route to open access. == Benefits == The benefits of open-access repositories are: Opening up outputs of the institution to a worldwide audience; Maximizing the visibility and impact of these outputs as a result; Showcasing the institution to interested constituencies – prospective staff, prospective students and other stakeholders; Collecting and curating digital output;


id: open-journal-systems-20260505-0
file: data/en.wikipedia.org/wiki/Open_Journal_Systems-0.md
category: reference
title: Open Journal Systems
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Journal_Systems
date_saved: 2026-05-05T10:15:43.916399+00:00
instance: kb-cron
parent: open-journal-systems-20260505-0
summary:
Open Journal Systems, also known as OJS, is an open source and free software for the management of peer-reviewed academic journals, created by the Public Knowledge Project, and released under the GNU General Public License. == History == Open Journal Systems (OJS) was conceived to facilitate the development of open access, peer-reviewed publishing, providing the technical infrastructure for the presentation of journal articles along with an editorial-management workflow, including article submission, peer-review, and indexing. OJS relies upon individuals fulfilling different roles, such as journal manager, editor, reviewer, author, and reader. It has a module that supports subscription journals. Like other community-based projects such as WordPress, the software has a plugin architecture, which allows new features to be integrated without changing its core codebase. Available plugins facilitate indexing in Google Scholar and PubMed Central, publishing RSS/Atom web syndication feeds, and providing COUNTER statistics about online usage, several plugins are curated and directly available for download through its plugin gallery interface. OJS is also LOCKSS-compliant, which helps ensure ongoing access to journal contents. Third-party plugins include Reading Tools, which point readers to related studies, media stories, and policy documents in open access databases, the Better Password plugin, which forces the users to


id: open-science-20260505-0
file: data/en.wikipedia.org/wiki/Open_science-0.md
category: reference
title: Open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science
date_saved: 2026-05-05T10:15:45.346466+00:00
instance: kb-cron
parent: open-science-20260505-0
summary:
Open science (also known as open research) is the movement to make scientific research, including publications, data, physical samples, software, and models, transparent and accessible to all levels of society through collaborative networks. This encompasses practices such as publishing open research, campaigning for open access, encouraging scientists to practice open-notebook science (such as openly sharing data and code), broader dissemination and public engagement in science, and generally making it easier to publish, access, and communicate scientific knowledge. Usage of the term varies substantially across disciplines, with a notable prevalence in the STEM disciplines. The term 'open research' has gained currency as a broader alternative to 'open science,' encompassing the humanities and arts alongside traditional scientific disciplines. The primary focus connecting all disciplines is the widespread uptake of new technologies and tools, and the underlying ecology of the production, dissemination and reception of knowledge from a research-based point-of-view. The term 'open scholarship' has also been proposed to include research from the arts and humanities as well as the different roles and practices that researchers perform as educators and communicators. Open science can be seen as continuing, rather than revolutionizing, practices that began in the 17th century with the academic journal, which


id: open-science-20260505-1
file: data/en.wikipedia.org/wiki/Open_science-1.md
category: reference
title: Open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science
date_saved: 2026-05-05T10:15:45.346466+00:00
instance: kb-cron
parent: open-science-20260505-0
summary:
Peer review is widely acknowledged as time-consuming. Citation impact, attributed to the authors, correlates more closely with journal circulation than with article quality. Open Science–aligned publishing formats rarely conform to traditional journal structures that calculate impact factors. Hence, this school argues that there are faster impact measurement technologies that can account for a range of publication types as well as social media web coverage of a scientific contribution to arrive at a complete evaluation of how impactful the science contribution was. The gist of the argument for this school is that hidden uses like reading, bookmarking, sharing, discussing and rating are traceable activities, and these traces can and should be used to develop a newer measure of scientific impact. The umbrella jargon for this new type of impact measurements is called altmetrics, coined in a 2011 article by Priem et al., (2011). Markedly, the authors discuss evidence that altmetrics differ from traditional webometrics which are slow and unstructured. Altmetrics are proposed to rely upon a greater set of measures that account for tweets, blogs, discussions, and bookmarks. Scholars propose that altmetrics should capture the entire research lifecycle, including collaboration patterns, to produce comprehensive impact measures. However, the authors are explicit


id: open-science-20260505-2
file: data/en.wikipedia.org/wiki/Open_science-2.md
category: reference
title: Open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science
date_saved: 2026-05-05T10:15:45.346466+00:00
instance: kb-cron
parent: open-science-20260505-0
summary:
=== Before journals === Before the advent of scientific journals, scientists had little to gain and much to lose by publicizing scientific discoveries. Many scientists, including Galileo, Kepler, Isaac Newton, Christiaan Huygens, and Robert Hooke, made claim to their discoveries by describing them in papers coded in anagrams or cyphers and then distributing the coded text. Their intent was to develop their discovery into something off which they could profit, then reveal their discovery to prove ownership when they were prepared to make a claim on it. The system of not publicizing discoveries caused problems because discoveries were not shared quickly and because it sometimes was difficult for the discoverer to prove priority. Newton and Gottfried Leibniz both claimed priority in discovering calculus. Newton said that he wrote about calculus in the 1660s and 1670s, but did not publish until 1693. Leibniz published "Nova Methodus pro Maximis et Minimis", a treatise on calculus, in 1684. Debates over priority are inherent in systems where science is not published openly, and this was problematic for scientists who wanted to benefit from priority. Under aristocratic patronage, scientists received funding to develop useful innovations or provide entertainment, creating pressure to satisfy patrons' desires and


id: open-science-20260505-3
file: data/en.wikipedia.org/wiki/Open_science-3.md
category: reference
title: Open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science
date_saved: 2026-05-05T10:15:45.346466+00:00
instance: kb-cron
parent: open-science-20260505-0
summary:
=== Internet and the free access to scientific documents === The open science movement, as presented in activist and institutional discourses at the beginning of the 21st century, refers to different ways of opening up science, especially in the Internet age. Its first pillar is free access to scientific publications. This issue entered the political landscape when the Budapest Open Access Initiative was released February 14, 2002, following a conference organized by the Open Society Institute (now Open Society Foundations) on December 1–2, 2001. The resulting declaration calls for the use of digital tools such as open archives and open access journals, free of charge for the reader. The idea of open access to scientific publications quickly became inseparable from the question of free licenses to guarantee the right to disseminate and possibly modify shared documents, such as the Creative Commons licenses, created in 2002. In 2011, a new text from the Budapest Open Initiative explicitly refers to the relevance of the CC-BY license to guarantee free dissemination and not only free access to a scientific document. Beyond publications, the open access principle has expanded to include research data — the empirical foundation of scientific studies across disciplines, as mentioned


id: open-science-20260505-4
file: data/en.wikipedia.org/wiki/Open_science-4.md
category: reference
title: Open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science
date_saved: 2026-05-05T10:15:45.346466+00:00
instance: kb-cron
parent: open-science-20260505-0
summary:
== Open Science and Research Assessment == A central aspect of the Open Science movement is the reform of research assessment. Initiatives such as the Coalition for Advancing Research Assessment (CoARA) (launched in 2022) and the San Francisco Declaration on Research Assessment (DORA) advocate moving away from traditional quantitative metrics like the Journal Impact Factor (JIF) and the h-Index, as these often exhibit biases and neglect qualitative aspects. Instead, alternative metrics and indicators, such as altmetrics and Open Science indicators, are to be given greater consideration. Open Science indicators include metrics such as the number of open access publications, data management plans, preprints, FAIR-licensed data, and open peer review reports. These approaches aim to promote the transparency and reusability of scientific outcomes, thereby enabling a fairer and more comprehensive evaluation of scientific achievements.While Open Science aims to enhance transparency, accessibility, and collaboration, the introduction of numerous new metrics to measure openness has led to unintended consequences. These metrics often rely on quantitative indicators, which conflict with the holistic and qualitative approaches advocated by initiatives such as CoARA and DORA. The core issue is that these metrics are designed not only to measure but also to influence researchers' behavior. This can


id: open-science-20260505-5
file: data/en.wikipedia.org/wiki/Open_science-5.md
category: reference
title: Open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science
date_saved: 2026-05-05T10:15:45.346466+00:00
instance: kb-cron
parent: open-science-20260505-0
summary:
=== Disadvantages === Arguments against open science tend to focus on the advantages of data ownership and concerns about the misuse of data, but see. Other concerns around data misuse involve privacy and safety risks that arise from ecological data on protected animal populations or sensitive data on human specimens that could potentially be re-identified and lead to hard and stigma for certain populations. Potential misuse Allowing open access can bring documented cases of misuse, and such misuse can take various forms from accidental errors to intentional forms of misuse like misrepresenting data in order to manipulate or deceive. In 2011, Dutch researchers announced their intention to publish a research paper in the journal Science describing the creation of a strain of H5N1 influenza which can be easily passed between ferrets, the mammals which most closely mimic the human response to the flu. The announcement triggered a controversy in both political and scientific circles about the ethical implications of publishing scientific data which could be used to create biological weapons. These events are examples of how science data could potentially be misused. It has been argued that constraining the dissemination of dual-use knowledge can in certain cases be justified because,


id: open-science-20260505-6
file: data/en.wikipedia.org/wiki/Open_science-6.md
category: reference
title: Open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science
date_saved: 2026-05-05T10:15:45.346466+00:00
instance: kb-cron
parent: open-science-20260505-0
summary:
=== Open-science projects === Different projects conduct, advocate, develop tools for, or fund open science. The Allen Institute for Brain Science conducts numerous open science projects while the Center for Open Science has projects to conduct, advocate, and create tools for open science. Other workgroups have been created in different fields, such as the Decision Analysis in R for Technologies in Health (DARTH) workgroup], which is a multi-institutional, multi-university collaborative effort by researchers who have a common goal to develop transparent and open-source solutions to decision analysis in health. Organizations have extremely diverse sizes and structures. The Open Knowledge Foundation (OKF) is a global organization sharing large data catalogs, running face to face conferences, and supporting open source software projects. In contrast, Blue Obelisk is an informal group of chemists and associated cheminformatics projects. The tableau of organizations is dynamic with some organizations becoming defunct, e.g., Science Commons, and new organizations trying to grow, e.g., the Self-Journal of Science. Common organizing forces include the knowledge domain, type of service provided, and even geography, e.g., OCSDNet's concentration on the developing world. The Allen Brain Atlas maps gene expression in human and mouse brains; the Encyclopedia of Life documents all the terrestrial


id: open-science-20260505-7
file: data/en.wikipedia.org/wiki/Open_science-7.md
category: reference
title: Open science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_science
date_saved: 2026-05-05T10:15:45.346466+00:00
instance: kb-cron
parent: open-science-20260505-0
summary:
F1000Research provides open publishing and open peer review for the life sciences. The Open Library of Humanities is a non-profit open access publisher for the humanities and social sciences. The Journals Library of the National Institute for Health and Care Research (NIHR) publishes all relevant documents and data from the onset of research projects, updating them alongside the progress of the study. Journal support for open-science does not conflict with preprint servers: figshare archives and shares images, readings, and other data; and Open Science Framework preprints, arXiv, and HAL Archives Ouvertes provide electronic preprints across many fields. === Software === A variety of computer resources support open science. These include software like the Open Science Framework from the Center for Open Science to manage project information, data archiving and team coordination; distributed computing services like Ibercivis to use unused CPU time for computationally intensive tasks; and services like Experiment.com to provide crowdsourced funding for research projects. Blockchain platforms for open science have been proposed. The first such platform is the Open Science Organization, which aims to solve urgent problems with fragmentation of the scientific ecosystem and difficulties of producing validated, quality science. Among the initiatives of Open Science Organization include


id: open-science-infrastructure-20260505-0
file: data/en.wikipedia.org/wiki/Open_Science_Infrastructure-0.md
category: reference
title: Open Science Infrastructure
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Infrastructure
date_saved: 2026-05-05T10:15:46.620146+00:00
instance: kb-cron
parent: open-science-infrastructure-20260505-0
summary:
Open Science Infrastructure (or open scholarly infrastructure) is information infrastructure that supports the open sharing of scientific productions such as publications, datasets, metadata or code. In November 2021 the Unesco recommendation on Open Science describes it as "shared research infrastructures that are needed to support open science and serve the needs of different communities". Open science infrastructures are a form of scientific infrastructure (also called cyberinfrastructure, e-Science or e-infrastructure) that support the production of open knowledge. Beyond the management of common resources, they are frequently structured as community-led initiatives with a set collective norms and governance regulations, which makes them also a form of knowledge commons. The definition of open science infrastructures usually exclude privately owned scientific infrastructures run by leading commercial publishers. Conversely it may include actors not always characterized as scientific infrastructures that play a critical role in the ecosystem of open science, such as publishing platforms in open access (open scholarly communication service). Computing infrastructures and online services have played a key role in the production and diffusion of scientific knowledge since the 1960s. While these early scientific infrastructure were initially envisioned as community initiatives, they could not be openly used due to the lack of interconnectivity


id: open-science-infrastructure-20260505-1
file: data/en.wikipedia.org/wiki/Open_Science_Infrastructure-1.md
category: reference
title: Open Science Infrastructure
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Infrastructure
date_saved: 2026-05-05T10:15:46.620146+00:00
instance: kb-cron
parent: open-science-infrastructure-20260505-0
summary:
=== Openness and the commons === Open science infrastructures are open, which differentiate them with other scientific and knowledge infrastructure and, more specifically, with subscription-based commercial infrastructures. Openness is both a core value and a directing principle that affect the aims, the governance and the management of the infrastructure. Open science infrastructure face similar issues met by other open institutions such as open data repositories or large scale collaborative project such as Wikipedia: "When we study contemporary knowledge infrastructures we find values of openness often embedded there, but translating the values of openness into the design of infrastructures and the practices of infrastructuring is a complex and contingent process". The conceptual definition of open science infrastructures has been largely influenced by the analysis of Elinor Ostrom on the commons and more specifically on the knowledge commons. In accordance with Ostrom, Cameron Neylon understates that open infrastructures are not only characterized by the management of a pool of common resources but also by the elaboration of common governance and norms. The economic theory of the commons make it possible to expand beyond the scope of limited scope of scholar associations toward large scale community-led initiatives: "Ostrom's work (…) provides a template


id: open-science-infrastructure-20260505-2
file: data/en.wikipedia.org/wiki/Open_Science_Infrastructure-2.md
category: reference
title: Open Science Infrastructure
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Infrastructure
date_saved: 2026-05-05T10:15:46.620146+00:00
instance: kb-cron
parent: open-science-infrastructure-20260505-0
summary:
Scientific projects have been among the earliest use case for digital infrastructure. The theorization of scientific knowledge infrastructure even predates the development of computing technologies. The knowledge network envisioned by Paul Otlet or Vannevar Bush already incorporated numerous features of online scientific infrastructures. After the Second World War, the United States faced a "periodical crisis": existing journals could not keep up with the rapidly increasing scientific output. The issue became politically relevant after the successful launch of Sputnik: "The Sputnik crisis turned the librarians' problem of bibliographic control into a national information crisis." The emerging computing technologies were immediately considered as a potential solution to make a larger amount of scientific output readable and searchable. Access to foreign language publication was also a key issue that was expected to be solved by machine translation: in the 1950s, a significant amount of scientific publications were not available in English, especially the one coming from the Soviet bloc. Influent members of the National Science Foundation like Joshua Ledeberg advocated for the creation of a "centralized information system", SCITEL that would at first coexist with printed journals and gradually replace them altogether on account of its efficiency. In the plan laid out by


id: open-science-infrastructure-20260505-3
file: data/en.wikipedia.org/wiki/Open_Science_Infrastructure-3.md
category: reference
title: Open Science Infrastructure
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Infrastructure
date_saved: 2026-05-05T10:15:46.620146+00:00
instance: kb-cron
parent: open-science-infrastructure-20260505-0
summary:
=== The Web Revolution (1990–1995) === The World Wide Web was originally framed as an open scientific infrastructure. The project was inspired by ENQUIRE, an information management software commissioned to Tim Berners-Lee by the CERN for the specific needs of high energy physics. The structure of ENQUIRE was closer to an internal web of data: it connected "nodes" that "could refer to a person, a software module, etc. and that could be interlined with various relations such as made, include, describes and so forth". While it "facilitated some random linkage between information" Enquire was not able to "facilitate the collaboration that was desired for in the international high-energy physics research community". Like any significant computing scientific infrastructure before the 1990s, the development of ENQUIRE was ultimately impeded by the lack of interoperability and the complexity of managing network communications: "although Enquire provided a way to link documents and databases, and hypertext provided a common format in which to display them, there was still the problem of getting different computers with different operating systems to communicate with each other". Sharing of data and data documentation was a major focus in the initial communication of the World Wide Web when the project


id: open-science-infrastructure-20260505-4
file: data/en.wikipedia.org/wiki/Open_Science_Infrastructure-4.md
category: reference
title: Open Science Infrastructure
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Infrastructure
date_saved: 2026-05-05T10:15:46.620146+00:00
instance: kb-cron
parent: open-science-infrastructure-20260505-0
summary:
The development of the World-Wide Web had rendered numerous pre-existing scientific infrastructure obsolete. It also lifted numerous restrictions and obstacles to online contribution and network management that made it possible to attempt more ambitious project. By the end of the 1990s, the creation of public scientific computing infrastructure became a major policy issue. The first wave of web-based scientific projects in the 1990s and the early 2000s revealed critical issues of sustainability. As funding was allocated on a specific time period, critical databases, online tools or publishing platforms could hardly be maintained; and project managers were faced with a valley of death "between grant funding and ongoing operational funding". Several competing terms appeared to fill this need. In the United States, the cyber-infrastructure was used in a scientific context by a US National Science Foundation (NSF) blue-ribbon committee in 2003: "The newer term cyberinfrastructure refers to infrastructure based upon distributed computer, information and communication technology. If infrastructure is required for an industrial economy, then we could say that cyberinfrastructure is required for a knowledge economy." E-infrastructure or e-science were used in a similar meaning in the United Kingdom and European countries. Thanks to "sizable investments", major national and international infrastructures


id: open-science-infrastructure-20260505-5
file: data/en.wikipedia.org/wiki/Open_Science_Infrastructure-5.md
category: reference
title: Open Science Infrastructure
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Infrastructure
date_saved: 2026-05-05T10:15:46.620146+00:00
instance: kb-cron
parent: open-science-infrastructure-20260505-0
summary:
=== Toward open science infrastructures (2015-…) === The consolidation and expansion of commercial scientific infrastructure had entailed renewed calls to secure "community-controlled infrastructure". The acquisition of the open repositories Digital Commons and SSRN by Elsevier has highlighted the lack of reliability of critical scientific infrastructure for open science. The SPARC report on European Infrastructures underlines that "a number of important infrastructures at risk and as a consequence, the products and services that comprise open infrastructure are increasingly being tempted by buyout offers from large commercial enterprises. This threat affects both not-for-profit open infrastructure as well as closed, and is evidenced by the buyout in recent years of commonly relied on tools and platforms such as SSRN, bepress, Mendeley, and Github." In contrast with the consolidation of privately owned infrastructure, the open science movement "has tended to overlook the importance of social structures and systemic constraints in the design of new forms of knowledge infrastructures". It remained mostly focused to the content of scientific research, with little integration of technical tools and few large community initiatives. "Common pool of resources is not governed or managed by the current scholarly commons initiative. There is no dedicated hard infrastructure and though there may


id: open-science-infrastructure-20260505-6
file: data/en.wikipedia.org/wiki/Open_Science_Infrastructure-6.md
category: reference
title: Open Science Infrastructure
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Infrastructure
date_saved: 2026-05-05T10:15:46.620146+00:00
instance: kb-cron
parent: open-science-infrastructure-20260505-0
summary:
=== Type and roles === Open Access repositories are the most frequent form of Open Science Infrastructure with 5,791 repositories in existence in December 2021 according to OpenDOAR Yet, there is a significant diversification of the roles and the activities of open science infrastructure, at least among the largest infrastructures. In the survey of European infrastructure conducted by SPARC Europe, 95% of the respondents mention that they provide services in at least three different stages of research production out of six (Creation, Evaluation, Publishing, Hosting, Discovering and Archiving). Aggregation, hosting and indexing are especially central activities, common to most Open Science Infrastructures regardless of their focus. Specialization does happen at a higher level. A network analysis identifies "two main clusters of activities": Publishing-focused infrastructures which are associated with the "publishing and hosting traditional text formats". Among them, "paper submission (41 out of 70) and review (30) were the most commonly reported activities". Creation-focused infrastructures which deal preferably with the "processing and storing research outputs, particularly data". Theses actors provide specific services in the field of "data gathering (47 out of 71), and data analysis (40)". Besides, "computation and machine learning (18) and Experimentation (15) were roughly half as common". ===


id: open-science-infrastructure-20260505-7
file: data/en.wikipedia.org/wiki/Open_Science_Infrastructure-7.md
category: reference
title: Open Science Infrastructure
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_Science_Infrastructure
date_saved: 2026-05-05T10:15:46.620146+00:00
instance: kb-cron
parent: open-science-infrastructure-20260505-0
summary:
=== Economics === Many Open Science Infrastructure run "at a relatively low cost" as small infrastructures are an important part of the open science ecosystem. In 2020, 21 out of 53 surveyed European infrastructures "report spending less than €50,000". Consequently, more than 75% of surveyed European infrastructures are run by small teams of 5 FTEs or less. The size of the infrastructure and the extent of its funding is far from always proportional to the critical service it offers: "some of the most heavily used services make ends meet with a tiny core team of two to five people." Volunteer contributions are significant as well with is both "a strength and weakness to an OSI's sustainability". The landscape of open science infrastructures is therefore rather close to the ideals of a "decentralised network of small projects" envisioned by theoricians of the scholarly commons. A very large majority of open science infrastructure are non-commercial and collaborations or financial support from the private sector remain very limited. Overall, European infrastructures were financially sustainable in 2020 which contrasts with the situation ten years prior: in 2010, European infrastructures had much less visibility: they usually lacked "a long-term perspective" and struggled "with securing the


id: open-source-20260505-0
file: data/en.wikipedia.org/wiki/Open_source-0.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T10:15:48.029597+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
Open source is software that is made freely available for possible modification and redistribution, also in form of source code. The licensing conditions include permission to use and view the source code, design documents, or content of the product. The open source model is a decentralized software development model that encourages open collaboration. A main principle of open source software development is peer production, with products such as source code, blueprints, and documentation freely available to the public. The open source movement in software began as a response to the limitations of proprietary code. The model is used for projects such as in open source eCommerce, open source appropriate technology, and open source drug discovery. Open source promotes universal access via an open-source or free license to a product's design or blueprint, and universal redistribution of that design or blueprint. Before the phrase open source became widely adopted, developers and producers used a variety of other terms, such as free software, shareware, and public domain software. The term Open source was introduced in 1998 and gained hold with the rise of the Internet. The open-source software movement arose to clarify copyright, licensing, domain, and consumer issues. Generally, open source refers


id: open-source-20260505-1
file: data/en.wikipedia.org/wiki/Open_source-1.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T10:15:48.029597+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
Some economists agree that open-source is an information good or "knowledge good" with original work involving a significant amount of time, money, and effort. The cost of reproducing the work is low enough that additional users may be added at zero or near zero cost – this is referred to as the marginal cost of a product. Copyright creates a monopoly so that the price charged to consumers can be significantly higher than the marginal cost of production. This allows the author to recoup the cost of making the original work. Copyright thus creates access costs for consumers who value the work more than the marginal cost but less than the initial production cost. Access costs also pose problems for authors who wish to create a derivative work—such as a copy of a software program modified to fix a bug or add a feature, or a remix of a song—but are unable or unwilling to pay the copyright holder for the right to do so. Open source eliminates some of the access costs of consumers and creators of derivative works by reducing the restrictions of copyright. Basic economic theory predicts that lower costs would lead to higher consumption and also


id: open-source-20260505-2
file: data/en.wikipedia.org/wiki/Open_source-2.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T10:15:48.029597+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
The open-source model is a decentralized software development model that encourages open collaboration, meaning "any system of innovation or production that relies on goal-oriented yet loosely coordinated participants who interact to create a product (or service) of economic value, which they make available to contributors and noncontributors alike." A main principle of open-source software development is peer production, with products such as source code, blueprints, and documentation freely available to the public. The open-source movement in software began as a response to the limitations of proprietary code. The model is used for projects such as in open-source appropriate technology, and open-source drug discovery. The open-source model for software development inspired the use of the term to refer to other forms of open collaboration, such as in Internet forums, mailing lists and online communities. Open collaboration is also thought to be the operating principle underlining a gamut of diverse ventures, including TEDx and Wikipedia. Open collaboration is the principle underlying peer production, mass collaboration, and wikinomics. It was observed initially in open-source software, but can also be found in many other instances, such as in Internet forums, mailing lists, Internet communities, and many instances of open content, such as Creative Commons.


id: open-source-20260505-3
file: data/en.wikipedia.org/wiki/Open_source-3.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T10:15:48.029597+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
Linux (that much of world's server parks are running) MediaWiki (that Wikipedia is based upon) Many more: List of free and open-source software packages List of formerly proprietary software The Google Summer of Code, often abbreviated to GSoC, is an international annual program in which Google awards stipends to contributors who successfully complete a free and open-source software coding project during the summer. GSoC is a large scale project with 202 participating organizations in 2021. There are similar smaller scale projects such as the Talawa Project run by the Palisadoes Foundation (a non profit based in California, originally to promote the use of information technology in Jamaica, but now also supporting underprivileged communities in the US) === Electronics === Open-source hardware is hardware which initial specification, usually in a software format, is published and made available to the public, enabling anyone to copy, modify and redistribute the hardware and source code without paying royalties or fees. Open-source hardware evolves through community cooperation. These communities are composed of individual hardware/software developers, hobbyists, as well as very large companies. Examples of open-source hardware initiatives are: Openmoko: a family of open-source mobile phones, including the hardware specification and the operating system. OpenRISC: an


id: open-source-20260505-4
file: data/en.wikipedia.org/wiki/Open_source-4.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T10:15:48.029597+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
Open-source principles can be applied to technical areas such as digital communication protocols and data storage formats. Open-design – which involves applying open-source methodologies to the design of artifacts and systems in the physical world. It is very nascent but has huge potential. Open-source appropriate technology (OSAT) refers to technologies that are designed in the same fashion as free and open-source software. These technologies must be "appropriate technology" (AT) – meaning technology that is designed with special consideration to the environmental, ethical, cultural, social, political, and economic aspects of the community it is intended for. An example of this application is the use of open-source 3D printers like the RepRap to manufacture appropriate technology. Teaching – which involves applying the concepts of open source to instruction using a shared web space as a platform to improve upon learning, organizational, and management challenges. An example of an Open-source courseware is the Java Education & Development Initiative (JEDI). Other examples include Khan Academy and wikiversity. At the university level, the use of open-source-appropriate technology classroom projects has been shown to be successful in forging the connection between science/engineering and social benefit: This approach has the potential to use university students' access to


id: open-source-20260505-5
file: data/en.wikipedia.org/wiki/Open_source-5.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T10:15:48.029597+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
== Agriculture, economy, manufacturing and production == Open-source appropriate technology (OSAT), is designed for environmental, ethical, cultural, social, political, economic, and community aspects Open-design movement, development of physical products, machines and systems via publicly shared design information, including free and open-source software and open-source hardware, among many others: Open Architecture Network, improving global living conditions through innovative sustainable design OpenCores, a community developing digital electronic open-source hardware Open Design Alliance, develops Teigha, a software development platform to create engineering applications including CAD software Open Hardware and Design Alliance (OHANDA), sharing open hardware and designs via free online services Open Source Ecology (OSE), a network of farmers, engineers, architects and supporters striving to manufacture the Global Village Construction Set (GVCS) OpenStructures (OSP), a modular construction model where everyone designs on the basis of one shared geometrical OS grid Open manufacturing or "Open Production" or "Design Global, Manufacture Local", a new socioeconomic production model to openly and collaboratively produce and distribute physical objects Open-source architecture (OSArc), emerging procedures in imagination and formation of virtual and real spaces within an inclusive universal infrastructure Open-source cola, cola soft drinks made to open-sourced recipes Open-source hardware, or open hardware, computer hardware, such as microprocessors, that


id: open-source-20260505-6
file: data/en.wikipedia.org/wiki/Open_source-6.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T10:15:48.029597+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
== Society == The rise of open-source culture in the 20th century resulted from a growing tension between creative practices that involve require access to content that is often copyrighted, and restrictive intellectual property laws and policies governing access to copyrighted content. The two main ways in which intellectual property laws became more restrictive in the 20th century were extensions to the term of copyright (particularly in the United States) and penalties, such as those articulated in the Digital Millennium Copyright Act (DMCA), placed on attempts to circumvent anti-piracy technologies. Although artistic appropriation is often permitted under fair-use doctrines, the complexity and ambiguity of these doctrines create an atmosphere of uncertainty among cultural practitioners. Also, the protective actions of copyright owners create what some call a "chilling effect" among cultural practitioners. The idea of an "open-source" culture runs parallel to "Free Culture", but is substantively different. Free culture is a term derived from the free software movement, and in contrast to that vision of culture, proponents of open-source culture (OSC) maintain that some intellectual property law needs to exist to protect cultural producers. Yet they propose a more nuanced position than corporations have traditionally sought. Instead of seeing intellectual property


id: open-source-20260505-7
file: data/en.wikipedia.org/wiki/Open_source-7.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T10:15:48.029597+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
=== Media === Open-source journalism formerly referred to the standard journalistic techniques of news gathering and fact checking, reflecting open-source intelligence, a similar term used in military intelligence circles. Now, open-source journalism commonly refers to forms of innovative publishing of online journalism, rather than the sourcing of news stories by a professional journalist. In the 25 December 2006 issue of TIME magazine this is referred to as user created content and listed alongside more traditional open-source projects such as OpenSolaris and Linux. Weblogs, or blogs, are another significant platform for open-source culture. Blogs consist of periodic, reverse chronologically ordered posts, using a technology that makes webpages easily updatable with no understanding of design, code, or file transfer required. While corporations, political campaigns and other formal institutions have begun using these tools to distribute information, many blogs are used by individuals for personal expression, political organizing, and socializing. Some, such as LiveJournal or WordPress, use open-source software that is open to the public and can be modified by users to fit their own tastes. Whether the code is open or not, this format represents a nimble tool for people to borrow and re-present culture; whereas traditional websites made the illegal reproduction


id: open-source-20260505-8
file: data/en.wikipedia.org/wiki/Open_source-8.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T10:15:48.029597+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
Within the academic community, there is discussion about expanding what could be called the "intellectual commons" (analogous to the Creative Commons). Proponents of this view have hailed the Connexions Project at Rice University, OpenCourseWare project at MIT, Eugene Thacker's article on "open-source DNA", the "Open Source Cultural Database", Salman Khan's Khan Academy and Wikipedia as examples of applying open source outside the realm of computer software. Open-source curricula are instructional resources whose digital source can be freely used, distributed and modified. Another strand to the academic community is in the area of research. Many funded research projects produce software as part of their work. Due to the benefits of sharing software openly in scientific endeavours, there is an increasing interest in making the outputs of research projects available under an open-source license. In the UK the Joint Information Systems Committee (JISC) has developed a policy on open-source software. JISC also funds a development service called OSS Watch which acts as an advisory service for higher and further education institutions wishing to use, contribute to and develop open-source software. On 30 March 2010, President Barack Obama signed the Health Care and Education Reconciliation Act, which included $2 billion over four years


id: open-source-20260505-9
file: data/en.wikipedia.org/wiki/Open_source-9.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T10:15:48.029597+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
=== Ideologically-related movements === The open-access movement is a movement that is similar in ideology to the open source movement. Members of this movement maintain that academic material should be readily available to provide help with "future research, assist in teaching and aid in academic purposes." The open-access movement aims to eliminate subscription fees and licensing restrictions of academic materials. The free-culture movement is a movement that seeks to achieve a culture that engages in collective freedom via freedom of expression, free public access to knowledge and information, full demonstration of creativity and innovation in various arenas, and promotion of citizen liberties. Creative Commons is an organization that "develops, supports, and stewards legal and technical infrastructure that maximizes digital creativity, sharing, and innovation." It encourages the use of protected properties online for research, education, and creative purposes in pursuit of a universal access. Creative Commons provides an infrastructure through a set of copyright licenses and tools that creates a better balance within the realm of "all rights reserved" properties. The Creative Commons license offers a slightly more lenient alternative to "all rights reserved" copyrights for those who do not wish to exclude the use of their material. The Zeitgeist Movement


id: open-source-20260505-10
file: data/en.wikipedia.org/wiki/Open_source-10.md
category: reference
title: Open source
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_source
date_saved: 2026-05-05T10:15:48.029597+00:00
instance: kb-cron
parent: open-source-20260505-0
summary:
=== Literature on legal and economic aspects === Abramson, Bruce (2005). Digital Phoenix; Why the Information Economy Collapsed and How it Will Rise Again. MIT Press. ISBN 978-0-262-51196-4. Benkler, Y. (December 2002). "Coase's Penguin, or, Linux and The Nature of the Firm" (PDF). Yale Law Journal. 112 (3): 369–446. arXiv:cs/0109077. doi:10.2307/1562247. hdl:10535/2974. ISSN 0044-0094. JSTOR 1562247. S2CID 16684329. Berry, D.M.; Moss, G. (2008). "Libre Culture: Meditations on Free Culture" (PDF). Canada: Pygmalion Books. Bitzer, J.; Schröder, P.J.H. (2005). "The Impact of Entry and Competition by Open Source Software on Innovation Activity" (PDF). Industrial Organization. EconWPA. v. Engelhardt, S. (2008). "The Economic Properties of Software" (PDF). Jena Economic Research Papers. 2: 2008–045. v. Engelhardt, S. (2008): "Intellectual Property Rights and Ex-Post Transaction Costs: the Case of Open and Closed Source Software", Jena Economic Research Papers 2008-047. (PDF) v. Engelhardt, S.; Swaminathan, S. (2008). "Open Source Software, Closed Source Software or Both: Impacts on Industry Growth and the Role of Intellectual Property Rights" (PDF). Discussion Papers of Diw Berlin. European Commission. (2006). Economic impact of open source software on innovation and the competitiveness of the Information and Communication Technologies sector in the EU. Brussels. v. Hippel, E.; v. Krogh, G. (2003). "Open


id: open-source-ventilator-20260505-0
file: data/en.wikipedia.org/wiki/Open-source_ventilator-0.md
category: reference
title: Open-source ventilator
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open-source_ventilator
date_saved: 2026-05-05T10:15:49.197945+00:00
instance: kb-cron
parent: open-source-ventilator-20260505-0
summary:
An open source ventilator is a disaster-situation ventilator made using a freely licensed (open-source) design, and ideally, freely available components and parts (open source hardware). Designs, components, and parts may be anywhere from completely reverse-engineered or completely new creations, components may be adaptations of various inexpensive existing products, and special hard-to-find and/or expensive parts may be 3D-printed instead of purchased. As of early 2020, the levels of documentation and testing of open source ventilators was well below scientific and medical-grade standards. One small, early prototype effort was the Pandemic Ventilator created in 2008 during the resurgence of H5N1 avian influenza that began in 2003, so named "because it is meant to be used as a ventilator of last resort during a possible avian (bird) flu pandemic." == Quality assessment == The policy of using both free and open source software (FOSS) and open source hardware theoretically allows community-wide peer-review and correction of bugs and faults in open source ventilators, which is not available in closed source hardware development. In early 2020 during the COVID-19 pandemic, a review of open source ventilators stated that "the tested and peer-reviewed systems lacked complete documentation and the open systems that were documented were either


id: open-source-ventilator-20260505-1
file: data/en.wikipedia.org/wiki/Open-source_ventilator-1.md
category: reference
title: Open-source ventilator
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open-source_ventilator
date_saved: 2026-05-05T10:15:49.197945+00:00
instance: kb-cron
parent: open-source-ventilator-20260505-0
summary:
On March 16, 2020, the Open Source Ventilator Ireland (OSV) group was formed initially with the goal of building a focus team in Ireland to begin development on what was termed the “Field Emergency Ventilator (FEV)”. Inspired by the initial efforts of the Open Source Medical Supplies (OSCMS), which initially focused on developing open ventilators but quickly refocusing mainly on the local production of Personal Protective Experiment (PPE). OSV Ireland partnered with the OpenLung team in Canada, who were developing and publishing open source designs via GitLab. The group quickly grew amassing volunteer engineers, designers and medical professionals with the goal of developing new, low resource medical interventions to support a perceived lack of mechanical ventilation equipment globally. The well-known Bag Valve Mask (BVM) quickly became the core functional component of their design, with the goal of utilizing 3D printed and traditionally manufactured components for localized assembly of the systems to maximise potential manufacturing capabilities around the globe. The Open Source Ventilator Ireland (OSV) group evolved into TeamOSV, to fully incorporate both ventilator and other covid related medical equipment. The FOSS Initiative OpenVentilator.io project began on March 19, after two weeks of research. Jeremias Almadas had posted some drafts he


id: open-source-ventilator-20260505-2
file: data/en.wikipedia.org/wiki/Open-source_ventilator-2.md
category: reference
title: Open-source ventilator
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open-source_ventilator
date_saved: 2026-05-05T10:15:49.197945+00:00
instance: kb-cron
parent: open-source-ventilator-20260505-0
summary:
The University of Minnesota Bakken Medical Device Center initiated a collaboration with various companies to bring a ventilator alternative to the market that works as a one-armed robot and replaces the need for manual ventilation in emergency situations. The Coventor device was developed in a very short time and approved on April 15, 2020, by the FDA, only 30 days after conception. The mechanical ventilator is designed for use by trained medical professionals in intensive care units and easy to operate. It has a compact design and is relatively inexpensive to manufacture and distribute. The cost is only about 4% of a normal ventilator. In addition, this device does not require pressurized oxygen or air supply, as is normally the case. A first series is manufactured by Boston Scientific. The plans are to be freely available online to the general public without royalties. The Polish company Urbicum reports successful testing of a 3D-printed, open source prototype device called VentilAid. The makers describe it as a last resort device when professional equipment is missing. The design is publicly available. The first Ventilaid prototype requires compressed air to run. On March 21, 2020, the New England Complex Systems Institute (NECSI) began maintaining


id: opencitations-20260505-0
file: data/en.wikipedia.org/wiki/OpenCitations-0.md
category: reference
title: OpenCitations
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/OpenCitations
date_saved: 2026-05-05T10:15:50.394520+00:00
instance: kb-cron
parent: opencitations-20260505-0
summary:
OpenCitations (established in 2010) is a project aiming to publish open bibliographic citation information in RDF. It produces the "OpenCitations Corpus" citation database in the process. == Datasets == OpenCitations publishes the following datasets which encompass bibliographic data, citation metadata, and in-text reference data. The datasets can be accessed via SPARQL, a REST API, as dumps on Figshare, as individual bibliographic entities, or using OSCAR (OpenCitations RDF Search Application) or Lucinda (The OpenCitations RDF Resource Browser). === OpenCitations Corpus === The OpenCitations Corpus (OCC) is an open repository of scholarly citation data. The repository is released under the CC0 public domain to ensure that the scholarly citation data is open to all. As of March 19, 2022, the OCC has ingested the references from 326,743 citing bibliographic resources and contains information about 13,964,148 citation links to 7,565,367 cited resources. === OpenCitations Indexes === The OpenCitations Indexes are collections of citations, which treat citations as first-class data objects that include citation metadata, as well as identifiers to the citing and cited works. For example, COCI is the OpenCitations Index of Crossref open DOI-to-DOI citations. A 2021 comparison with other citations tools found that COCI was the smallest in coverage, and a


id: opendoar-20260505-0
file: data/en.wikipedia.org/wiki/OpenDOAR-0.md
category: reference
title: OpenDOAR
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/OpenDOAR
date_saved: 2026-05-05T10:15:51.553114+00:00
instance: kb-cron
parent: opendoar-20260505-0
summary:
OpenDOAR: Directory of Open Access Repositories is a UK-based website that lists open access repositories (including academic ones). It is searchable by locale, content, and other measures. The service does not require complete repository details and does not search repositories' metadata. OpenDOAR is maintained by the University of Nottingham under the SHERPA umbrella of services and was developed in collaboration with Lund University. The project is funded by the Open Science Institute, Jisc, the Consortium of Research Libraries (CURL) and SPARC Europe. As of 2015, OpenDOAR and the UK-based Registry of Open Access Repositories (ROAR) "are considered the Two leading open access directories worldwide. ROAR is the larger directory and allows direct submissions to the directory. OpenDOAR controls submission of materials and is dependent on the discretion of its staff. OpenDOAR requires open access of scholarly publications; whereas ROAR allows other types of materials to be included. ROAR allows filtering by country, type of repository, and sorting by repository name." == See also == List of academic databases and search engines OAIster == References == == External links == OpenDOAR


id: overlay-journal-20260505-0
file: data/en.wikipedia.org/wiki/Overlay_journal-0.md
category: reference
title: Overlay journal
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Overlay_journal
date_saved: 2026-05-05T10:15:52.708920+00:00
instance: kb-cron
parent: overlay-journal-20260505-0
summary:
An overlay journal or overlay ejournal is a type of open access academic journal, almost always an online electronic journal (ejournal), that does not produce its own content, but selects from texts that are already freely available online. While many overlay journals derive their content from preprint servers, others, such as the Lund Medical Faculty Monthly, contain mainly papers published by commercial publishers, but with links to self-archived preprint or postprints when possible. The editors of an overlay journal locate suitable material from open access repositories and public domain sources, read it, and evaluate its worth. This evaluation may take the form of the judgement of a single editor or editors, or a full peer review process. Public validation of subsequently approved texts may take several forms. At its most formal, the editor may republish the article with explicit approval. Approval might take the form of an addition to the text or its metadata. Or the editor may simply link to the article, via the table of contents of the overlay journal. An alternative approach is to link to articles already published in various open access ejournals, but adding value by grouping scattered articles together as a single themed issue


id: pers-e-web-portal-20260505-0
file: data/en.wikipedia.org/wiki/Persée_(web_portal)-0.md
category: reference
title: Persée (web portal)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Persée_(web_portal)
date_saved: 2026-05-05T10:15:53.890363+00:00
instance: kb-cron
parent: pers-e-web-portal-20260505-0
summary:
Persée is a digital library of open access, mostly French-language scholarly journals, established by the Ministry of National Education of France. The website launched in 2005. The resource is maintained by the École normale supérieure de Lyon, French National Centre for Scientific Research, and University of Lyon. It is one of the largest francophone portals dedicated to human and social sciences, with about 600 000 documents freely available. == See also == List of journals in Persee.fr (fr) Open access journal List of open access bibliographic databases (fr) == References == == Bibliography == == External links == Official site


id: polish-studies-interdisciplinary-20260505-0
file: data/en.wikipedia.org/wiki/Polish-Studies.Interdisciplinary-0.md
category: reference
title: Polish-Studies.Interdisciplinary
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Polish-Studies.Interdisciplinary
date_saved: 2026-05-05T10:15:55.063984+00:00
instance: kb-cron
parent: polish-studies-interdisciplinary-20260505-0
summary:
Polish-Studies.Interdisciplinary (Pol-Int) is a free online platform for information on and international exchange in the field of Polish studies. The platform was launched in 2014 and serves as a tool for a growing interdisciplinary community of scholars worldwide to promote their own research and publications in Polish studies. Users can publish reviews, share information about conferences, events, and career opportunities as well as connect and engage in discussions on current issues. Pol-Int is headed by Dagmara Jajeśniak-Quast and based at the Center for Interdisciplinary Polish Studies (ZIP) at the European University Viadrina in Frankfurt (Oder) and at the Collegium Polonicum in Słubice. The platform is co-financed by the Foundation for Polish-German Cooperation, the Polish-German Foundation for Science, the European University Viadrina and the European Regional Development Fund. == Profile == Pol-Int offers up-to-date information on Polish studies worldwide: publications, journals and articles, reviews, job offers (including scholarships and grants), events, conference reports, and calls for papers. Anyone interested in the field of Polish studies can register, set up an individual profile, as well as publish and obtain information, share and promote their own research projects, and find project partners. Thus, Pol-Int serves as a networking tool for scholars dealing with


id: postprint-20260505-0
file: data/en.wikipedia.org/wiki/Postprint-0.md
category: reference
title: Postprint
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Postprint
date_saved: 2026-05-05T10:15:56.269010+00:00
instance: kb-cron
parent: postprint-20260505-0
summary:
A postprint is a digital draft of a research journal article after it has been peer reviewed and accepted for publication, but before it has been typeset and formatted by the journal. == Related terminology == A digital draft before peer review is called a preprint. Postprints are also sometimes called accepted author manuscripts (AAMs), because they are the version accepted by the journal after the author has addressed the peer reviewer comments. Jointly, postprints and preprints are called eprints. Postprints are variously referred to by different publishers as pre-proofs, author's original version and variations of these. After typesetting by a journal, authors will often be provided with proofs (the draft of the final formatting) and finally the version that is published is called the published/publisher's version. The term postprint used to also refer to the formatted publishers version, however usage has narrowed to refer only to the current definition of accepted but unformatted. == Role in open access == Journal publication licenses typically claim copyright over the typeset and formatted version, but permit authors to release the postprint version as open access (self-archiving). This is often termed green open access, and enables access and reuse of material even in


id: predatory-publishing-20260505-0
file: data/en.wikipedia.org/wiki/Predatory_publishing-0.md
category: reference
title: Predatory publishing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Predatory_publishing
date_saved: 2026-05-05T10:15:57.520910+00:00
instance: kb-cron
parent: predatory-publishing-20260505-0
summary:
Predatory publishing, also known as write-only publishing or deceptive publishing, is an exploitative and fraudulent academic publishing model in which journals or publishers prioritize their own financial or reputational gain over the advancement of scholarship. It is characterized by misleading or false information about editorial practices, a deviation from standard peer-review procedures, lack of transparency, and the use of aggressive or coercive solicitation tactics to attract authors. Predatory publishers often exploit the pressures on researchers to publish, undermining the integrity and credibility of scholarly communication. The phenomenon of "open-access predatory publishers" was first noticed by Jeffrey Beall around 2012, when he described "publishers that are ready to publish any article for payment". However, criticisms about the label "predatory" have been raised. A lengthy review of the controversy started by Beall appears in The Journal of Academic Librarianship. Predatory publishers are so regarded because scholars are tricked into publishing with them, although some authors may be aware that the journal is poor quality or even fraudulent but publish in them anyway. New scholars from developing countries are said to be especially at risk of being misled by predatory publishers. A 2022 report found that "nearly a quarter of the respondents from


id: predatory-publishing-20260505-1
file: data/en.wikipedia.org/wiki/Predatory_publishing-1.md
category: reference
title: Predatory publishing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Predatory_publishing
date_saved: 2026-05-05T10:15:57.520910+00:00
instance: kb-cron
parent: predatory-publishing-20260505-0
summary:
=== "Dr Fraud" experiment === In 2015, four researchers created a fictitious sub-par scientist named Anna O. Szust (oszust is Polish for "fraudster"), and applied on her behalf for an editor position to 360 scholarly journals. Szust's qualifications were dismal for the role of an editor; she had never published a single article and had no editorial experience. The books and book chapters listed on her CV were made-up, as were the publishing houses that published the books. One-third of the journals to which Szust applied were sampled from Beall's List of predatory journals. Forty of these predatory journals accepted Szust as editor without any background vetting and often within days or even hours. By comparison, she received minimal to no positive response from the "control" journals which "must meet certain standards of quality, including ethical publishing practices". Among journals sampled from the Directory of Open Access Journals (DOAJ), 8 of 120 accepted Szust. The DOAJ has since removed some of the affected journals in a 2016 purge. None of the 120 sampled journals listed in Journal Citation Reports (JCR) offered Szust the position. The results of the experiment were published in Nature in March 2017, and widely presented in


id: predatory-publishing-20260505-2
file: data/en.wikipedia.org/wiki/Predatory_publishing-2.md
category: reference
title: Predatory publishing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Predatory_publishing
date_saved: 2026-05-05T10:15:57.520910+00:00
instance: kb-cron
parent: predatory-publishing-20260505-0
summary:
The publisher is not a member of any recognized professional organisation committed to best publishing practices (like COPE or EASE) The journal is not indexed in well-established electronic databases (like MEDLINE or Web of Science) The publisher claims to be a "leading publisher" even though it just got started The journal and the publisher are unfamiliar to you and all your colleagues The papers of the journal are of poor research quality, and may not be academic at all (for instance allowing for obvious pseudo-science) There are fundamental errors in the titles and abstracts, or frequent and repeated typographical or factual errors throughout the published papers The journal website is not professional The journal website does not present an editorial board or gives insufficient detail on names and affiliations The journal website does not reveal the journal's editorial office location or uses an incorrect address The publishing schedule is not clearly stated The journal title claims a national affiliation that does not match its location (such as "American Journal of ..." while being located on another continent) or includes "International" in its title while having a single-country editorial board The journal mimics another journal title or the website of said


id: predatory-publishing-20260505-3
file: data/en.wikipedia.org/wiki/Predatory_publishing-3.md
category: reference
title: Predatory publishing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Predatory_publishing
date_saved: 2026-05-05T10:15:57.520910+00:00
instance: kb-cron
parent: predatory-publishing-20260505-0
summary:
=== Growth and structure === A study in 2015 found that predatory journals rapidly increased their publication volumes from 53,000 in 2010 to an estimated 420,000 articles in 2014, published by around 8,000 active journals. Early on, publishers with more than 100 journals dominated the market, but since 2012 publishers in the 10–99 journal size category have captured the largest market share. As of 2022, almost one third of the 100 largest publishers (by journal count) could be deemed predatory. The regional distribution of both the publisher's country and authorship is highly skewed, with three-quarters of the authors from Asia or Africa. Authors paid an average fee of US $178 each for articles to be published rapidly without review, typically within two to three months of submission. As reported in 2019, some 5% of Italian researchers have published in predatory journals, with a third of those journals engaging in fraudulent editorial practices. == Causes and impact == The root cause of exploitative practices is the author-facing article-processing charge (APC) business model, in which authors are charged to publish rather than to read. Such a model provides incentives for publishers to focus on the quantity of articles published, rather than their


id: predatory-publishing-20260505-4
file: data/en.wikipedia.org/wiki/Predatory_publishing-4.md
category: reference
title: Predatory publishing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Predatory_publishing
date_saved: 2026-05-05T10:15:57.520910+00:00
instance: kb-cron
parent: predatory-publishing-20260505-0
summary:
University of Colorado Denver librarian and researcher Jeffrey Beall, who coined the term "predatory publishing", first published his list of predatory publishers in 2010. Beall's list of potential, possible, or probable predatory scholarly open-access publishers attempted to identify scholarly open-access publishers with questionable practices. In 2013, Nature reported that Beall's list and web site were "widely read by librarians, researchers, and open-access advocates, many of whom applaud his efforts to reveal shady publishing practices." Others have raised the objection that "(w)hether it's fair to classify all these journals and publishers as 'predatory' is an open question—several shades of gray may be distinguishable." Beall's analyses have been called sweeping generalizations with no supporting evidence, and he has also been criticized for being biased against open-access journals from less economically developed countries. A 2018 study has shown that Beall's criteria of "predatory" publishing were in no way limited to OA publishers and that, applying them to both OA and non-OA journals in the field of library and information science, even top tier non-OA journals could be qualified as predatory. Similarly, another study reported on the difficulties of demarcating predatory and non-predatory journals in biomedicine. One librarian wrote that Beall's list "attempts a


id: predatory-publishing-20260505-5
file: data/en.wikipedia.org/wiki/Predatory_publishing-5.md
category: reference
title: Predatory publishing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Predatory_publishing
date_saved: 2026-05-05T10:15:57.520910+00:00
instance: kb-cron
parent: predatory-publishing-20260505-0
summary:
==== Cabells' Predatory Reports ==== At the May 2017 meeting of the Society for Scholarly Publishing, Cabell's International, a company that offers scholarly publishing analytics and other scholarly services, announced that it intended to launch a blacklist of predatory journals (not publishers) in June, and said that access would be by subscription only. The company had started work on its blacklist criteria in early 2016. In July 2017, both a black list and a white list were offered for subscription on their website. ==== Other blacklists ==== Since Beall's list closed, other list groups have started. These include Kscien's list, which used Beall's list as a starting point, updating it to add and remove publishers. In 2020, the Ministry of Science and Technology of China ordered Chinese Center of Scientometrics to launch a blacklist called Chinese Early Warning Journal List (EWJL). EWJL classifies journals into three grades: low, medium, or high risk, rather than two (predatory or not) like most other lists. Nevertheless, there is an ongoing criticism of this list as well. According to a 2020 systematic review of 93 lists, only three were assessed as evidence-based according to the authors' criteria. === Science funders === Multiple science funders


id: predatory-publishing-20260505-6
file: data/en.wikipedia.org/wiki/Predatory_publishing-6.md
category: reference
title: Predatory publishing
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Predatory_publishing
date_saved: 2026-05-05T10:15:57.520910+00:00
instance: kb-cron
parent: predatory-publishing-20260505-0
summary:
More transparent peer review, such as open peer review and post-publication peer review, has been advocated to combat predatory journals. Others have argued instead that the discussion on predatory journals should not be turned "into a debate over the shortcomings of peer review—it is nothing of the sort. It is about fraud, deception, and irresponsibility..." In an effort to "set apart legitimate journals and publishers from non-legitimate ones", principles of transparency and best practice have been identified and issued collectively by the Committee on Publication Ethics, the DOAJ, the Open Access Scholarly Publishers Association, and the World Association of Medical Editors. Various journal review websites (crowd-sourced or expert-run) have been started, some focusing on the quality of the peer review process and extending to non-OA publications. A group of libraries and publishers launched an awareness campaign. A number of measures have been suggested to further combat predatory journals. Others have called on research institutions to improve the publication literacy notably among junior researchers in developing countries. Some organisations have also developed criteria in which predatory publishers could be spotted through providing tips. As Beall has ascribed predatory publishing to a consequence of gold open access (particularly its author-pays variant), one


id: public-access-to-public-science-act-20260505-0
file: data/en.wikipedia.org/wiki/Public_Access_to_Public_Science_Act-0.md
category: reference
title: Public Access to Public Science Act
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Public_Access_to_Public_Science_Act
date_saved: 2026-05-05T10:15:58.721082+00:00
instance: kb-cron
parent: public-access-to-public-science-act-20260505-0
summary:
The Public Access to Public Science (PAPs) public access to research funded by specific Federal agencies under the jurisdiction of the House Science committee, including National Aeronautics and Space Administration (NASA), the National Science Foundation (NSF), the National Institute of Standards and Technology (NIST) and the National Weather Service (NWS). The Bill was introduced to the 113th Congress by Congressman Jim Sensenbrenner (R.-WI.) and Congresswoman Eddie Bernice Johnson (D-TX) and was referred to the Subcommittee on Research and Technology December 13, 2013. It has been endorsed by the Association of Public and Land-grant Universities (APLU) and the Association of American Universities (AAU). The bill is often compared to and discussed in conjunction with the Fair Access to Science and Technology Research Act (FASTR) bill, also introduced in 2013. == References == Congress.gov. H.R.3157 -- 113th Congress (2013-2014). Meindertsma, Jessica. October 25, 2013. "Public Access Policies (Part 1): FASTER, PAPS, and the OSTP Directive." Ohio State University Libraries. Sensenbrenner, Jim. September 6, 2016. "Give The Public What It Pays For: Scientific Research." Forbes. == External links == Full text of bill Letter of endorsement Notes on the Public Access to Public Science Act, Harvard Open Access Project FASTR v PAPS


id: registry-of-open-access-repositories-20260505-0
file: data/en.wikipedia.org/wiki/Registry_of_Open_Access_Repositories-0.md
category: reference
title: Registry of Open Access Repositories
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Registry_of_Open_Access_Repositories
date_saved: 2026-05-05T10:15:59.875819+00:00
instance: kb-cron
parent: registry-of-open-access-repositories-20260505-0
summary:
The Registry of Open Access Repositories (ROAR) is a searchable international database indexing the creation, location and growth of open access institutional repositories and their contents. ROAR was created by EPrints at University of Southampton, UK, in 2003. It began as the Institutional Archives Registry and was renamed Registry of Open Access Repositories in 2006. To date, over 3,000 institutional and cross-institutional repositories have been registered. As of 2015, ROAR and the UK-based Directory of Open Access Repositories (OpenDOAR) "are considered the two leading open access directories worldwide. ROAR is the larger directory and allows direct submissions to the directory. OpenDOAR controls submission of materials and is dependent on the discretion of its staff. OpenDOAR requires open access of scholarly publications; whereas ROAR allows other types of materials to be included. ROAR allows filtering by country, type of repository, and sorting by repository name." == ROARMAP == ROAR's companion Registry of Open Access Repository Mandates and Policies (ROARMAP) is a searchable international database of policies. It charts the growth of open access mandates and policies adopted by universities, research institutions and research funders that require their researchers to provide open access to their peer-reviewed research article output by depositing it


id: list-of-research-funders-by-preprint-licensing-policy-20260505-0
file: data/en.wikipedia.org/wiki/List_of_research_funders_by_preprint_licensing_policy-0.md
category: reference
title: List of research funders by preprint licensing policy
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_research_funders_by_preprint_licensing_policy
date_saved: 2026-05-05T10:16:01.063752+00:00
instance: kb-cron
parent: list-of-research-funders-by-preprint-licensing-policy-20260505-0
summary:
This is a list of funders of research by their open licensing policies for preprints. With the exception of some government employees and contractors, the majority of authors keep the copyright to their work. Many funders require their grantees to disseminate the work using licenses with specific reuse rights. Other details of funder open access policies can be found at the Registry of Open Access Repositories and the Open Policy Finder from JISC (formerly SHERPA). == Policies by funder == == Exceptions for government employees and contractors == In some countries, work performed by government employees or contractors is owned by the government and subject to their licensing stipulations. For example, in the US, work performed by government employees, such as employees of the NIH is deemed Public Domain in the US, and the US government holds copyright elsewhere. Government licensing policies may override funder requirements. == See also == List of academic publishers by preprint policy == References ==


id: research-works-act-20260505-0
file: data/en.wikipedia.org/wiki/Research_Works_Act-0.md
category: reference
title: Research Works Act
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research_Works_Act
date_saved: 2026-05-05T10:16:02.275907+00:00
instance: kb-cron
parent: research-works-act-20260505-0
summary:
The Research Works Act, 102 H.R. 3699, was a bill that was introduced in the United States House of Representatives at the 112th United States Congress on December 16, 2011, by Representative Darrell Issa (R-CA) and co-sponsored by Carolyn B. Maloney (D-NY). The bill contained provisions to prohibit open-access mandates for federally funded research and effectively revert the United States' National Institutes of Health Public Access Policy, which requires taxpayer-funded research to be freely accessible online. If enacted, it would have also severely restricted the sharing of scientific data. The bill was referred to the House Committee on Oversight and Government Reform, of which Issa is the chair. Similar bills were introduced in 2008 and 2009 but have not been enacted since. On February 27, 2012, Elsevier, a major publisher, announced that it was withdrawing support for the Act. Later that day, Issa and Maloney issued a statement saying that they would not push for legislative action on the bill. == Reception == The bill was supported by the Association of American Publishers (AAP) and the Copyright Alliance. The Scholarly Publishing and Academic Resources Coalition, the Alliance for Taxpayer Access, the American Library Association, the International Society for Computational Biology,


id: science-2-0-20260505-0
file: data/en.wikipedia.org/wiki/Science_2.0-0.md
category: reference
title: Science 2.0
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Science_2.0
date_saved: 2026-05-05T10:16:06.968333+00:00
instance: kb-cron
parent: science-2-0-20260505-0
summary:
Science 2.0 is a suggested new approach to science that uses information-sharing and collaboration made possible by network technologies. It is similar to the open research and open science movements and is inspired by Web 2.0 technologies. Science 2.0 stresses the benefits of increased collaboration between scientists. Science 2.0 uses collaborative tools like wikis, blogs and video journals to share findings, raw data and "nascent theories" online. Science 2.0 benefits from openness and sharing, regarding papers and research ideas and partial solutions. A general view is that Science 2.0 is gaining traction with websites beginning to proliferate, yet at the same time there is considerable resistance within the scientific community about aspects of the transition as well as discussion about what, exactly, the term means. There are several views that there is a "sea change" happening in the status quo of scientific publishing, and substantive change regarding how scientists share research data. There is considerable discussion in the scientific community about whether scientists should embrace the model and exactly how Science 2.0 might work, as well as several reports that many scientists are slow to embrace collaborative methods and are somewhat "inhibited and slow to adopt a lot of online


id: science-2-0-20260505-1
file: data/en.wikipedia.org/wiki/Science_2.0-1.md
category: reference
title: Science 2.0
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Science_2.0
date_saved: 2026-05-05T10:16:06.968333+00:00
instance: kb-cron
parent: science-2-0-20260505-0
summary:
Before the Internet, scientific publishing has been described as a "highly integrated and controlled process." Research was done in private. Next, it was submitted to scientific publications and reviewed by editors and gatekeepers and other scientists. Last, it was published. This has been the traditional pathway of scientific advancement, sometimes dubbed Science 1.0. Established journals provided a "critical service", according to one view. Publications such as Science and Nature have large editorial staffs to manage the peer-review process as well as have hired fact-checkers and screeners to look over submissions. These publications get revenue from subscriptions, including online ones, as well as advertising revenue and fees paid by authors. According to advocates of Science 2.0, however, this process of paper-submission and review was rather long. Detractors complained that the system is "hidebound, expensive and elitist", sometimes "reductionist", as well as being slow and "prohibitively costly". Only a select group of gatekeepers—those in charge of the traditional publications—limited the flow of information. Proponents of open science claimed that scientists could learn more and learn faster if there is a "friction-free collaboration over the Internet." Yet there is considerable resistance within the scientific community to a change of approach. The act of


id: science-2-0-20260505-2
file: data/en.wikipedia.org/wiki/Science_2.0-2.md
category: reference
title: Science 2.0
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Science_2.0
date_saved: 2026-05-05T10:16:06.968333+00:00
instance: kb-cron
parent: science-2-0-20260505-0
summary:
Public Library of Science. This project, sometimes termed PLoS, is a nonprofit open-access scientific publishing project aimed at creating a library of open access journals and other scientific literature under an open content license. By 2012, it publishes seven peer reviewed journals. It makes scientific papers immediately available online without charges for access or restrictions on passing them along, provided that the authors and sources are properly cited with the Creative Commons Attribution License. According to one report, the PLoS has gained "pretty wide acceptance" although many researchers in biomedicine still hope to be published in established journals such as Nature, Cell, and Science, according to one report. PLoS publishes 600 articles a month in 2012. arXiv, pronounced archive, is an online-accessible archive for electronic preprints of scientific papers in the fields of mathematics, physics, astronomy, computer science, quantitative biology, statistics, and quantitative finance. Galaxy Zoo is an online astronomy project which invites members of the public to assist in the morphological classification of large numbers of galaxies. It has been termed a citizen science project. The information has led to a substantial increase in scientific papers, according to one account. A website entitled Science 2.0 lets scientists share information.


id: scienceopen-20260505-0
file: data/en.wikipedia.org/wiki/ScienceOpen-0.md
category: reference
title: ScienceOpen
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/ScienceOpen
date_saved: 2026-05-05T10:16:08.138583+00:00
instance: kb-cron
parent: scienceopen-20260505-0
summary:
ScienceOpen is a web-based platform, that hosts open access journals. It is freely accessible for readers, authors and publishers, and it generates its revenues via promotional services for publishers and authors' institutions. The organization is based in Berlin and has a technical office in Boston. It is a member of CrossRef, ORCID, the Open Access Scholarly Publishers Association, STM Association and the Directory of Open Access Journals. The company was designated as one of “10 to Watch” by research advisory firm Outsell in its report “Open Access 2015: Market Size, Share, Forecast, and Trends.” == History == ScienceOpen began in 2013 when Alexander Grossmann, a professor of Publishing Management at the Leipzig University of Applied Sciences and former publishing director at scholarly publishing house De Gruyter, and Tibor Tscheke, president and CEO of the content management system company Ovitas, decided to start a platform that would allow researchers to share scientific information, both formally by publishing articles and participating in post-publication peer review, and informally by reviewing their colleagues’ work, providing endorsements and comments, and by updating their own papers. Its beta version was introduced in November 2013, and release 1.0 launched in May 2014. In September 2015, ScienceOpen hit


id: self-archiving-20260505-0
file: data/en.wikipedia.org/wiki/Self-archiving-0.md
category: reference
title: Self-archiving
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Self-archiving
date_saved: 2026-05-05T10:16:09.346015+00:00
instance: kb-cron
parent: self-archiving-20260505-0
summary:
Self-archiving is the act of (the author's) depositing a free copy of an electronic document online in order to provide open access to it. The term usually refers to the self-archiving of peer-reviewed research journal and conference articles, as well as theses and book chapters, deposited in the author's own institutional repository or open archive for the purpose of maximizing its accessibility, usage and citation impact. The term green open access has become common in recent years, distinguishing this approach from gold open access, where the journal itself makes the articles publicly available without charge to the reader. == Origins == Self-archiving was first explicitly proposed as a universal practice by Stevan Harnad in his 1994 online posting "Subversive Proposal" (later published in Association of Research Libraries) although computer scientists had been practicing self-archiving in anonymous FTP archives since at least the 1980s (see CiteSeer) and physicists had been doing it since the early 1990s on the web (see arXiv). The concept of green open access was coined in 2004 to describe a "mode of publishing in non open access journal but also self archiving it in an open access archive". Different drafts of a paper may be self-archived, such


id: shadow-library-20260505-0
file: data/en.wikipedia.org/wiki/Shadow_library-0.md
category: reference
title: Shadow library
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Shadow_library
date_saved: 2026-05-05T10:16:10.574634+00:00
instance: kb-cron
parent: shadow-library-20260505-0
summary:
Shadow libraries, also referred to as pirate libraries or black open access, are online repositories of freely available digital media that are normally paywalled, access-controlled, or otherwise not readily accessible. Shadow libraries usually contain textual works such as academic papers and ebooks, and may include other digital media like software, music, or films. Anna's Archive, Library Genesis, Sci-Hub, UbuWeb and Z-Library are some of the most popular shadow libraries for books and academic literature. == History == Early predecessors to shadow libraries were informal collections of unauthorized digital copies of books, scholarly literature, and other textual media, often shared with small groups via mailing lists, forums, or social media websites. Online communities of scientists also collaborated to share paywalled literature among themselves. Many shadow libraries originate in Russia, which has a rich history of samizdat stemming from the Soviet era. There was strict state censorship and control of print materials, which gave rise to the dissident activity of copying and disseminating censored or underground works. Even after the dissolution of the Soviet Union and the end of the official censorship program, these sharing practices continued as a result of widespread economic hardship. Texts were widely digitized and shared on Russian


id: shadow-library-20260505-1
file: data/en.wikipedia.org/wiki/Shadow_library-1.md
category: reference
title: Shadow library
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Shadow_library
date_saved: 2026-05-05T10:16:10.574634+00:00
instance: kb-cron
parent: shadow-library-20260505-0
summary:
== Legal status == Shadow libraries often host or link to copyrighted material without the consent of copyright holders, making them illegal or dubiously legal in many countries. Such libraries are also described as pirate libraries. Many shadow libraries maintain bibliographic catalogs separate from the hosting of files themselves. This is both an organizational convenience and a protection against legal challenges, since the law is often ambiguous on the distinction between hosting and indexing copyrighted content. However, several shadow library catalogs have been the target of injunctions and takedown threats. The aggressive legal strategies pursued by Western music and film industries against online filesharing websites during the 2000s were not widely mirrored by academic or literary publishers against shadow libraries. However, as shadow libraries have grown larger and more visible, they have attracted more legal challenges. Library.nu (previously Gigapedia) was shut down in 2012 by a lawsuit from a coalition of seventeen publishing companies including HarperCollins, Oxford University Press, and MacMillan. In 2015, the academic publisher Elsevier sued LibGen and Sci-Hub in American courts, accusing them of "operat[ing] an international network of piracy and copyright infringement". Elsevier won a default judgment against the two groups, and was awarded $15 million


id: subversive-proposal-20260505-0
file: data/en.wikipedia.org/wiki/Subversive_Proposal-0.md
category: reference
title: Subversive Proposal
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Subversive_Proposal
date_saved: 2026-05-05T10:16:13.908815+00:00
instance: kb-cron
parent: subversive-proposal-20260505-0
summary:
The "Subversive Proposal" was an Internet posting by Stevan Harnad on June 27, 1994 (presented at the 1994 Network Services Conference in London) calling on all authors of "esoteric" research writings to archive their articles for free for everyone online (in anonymous FTP archives or websites). It initiated a series of online exchanges, many of which were collected and published as a book in 1995: Scholarly Journals at the Crossroads: A Subversive Proposal for Electronic Publishing. This led to the creation in 1997 of Cogprints, an open access archive for self-archived articles in the cognitive sciences and in 1998 to the creation of the American Scientist Open Access Forum (initially called the "September98 Forum" until the founding of the Budapest Open Access Initiative which first coined the term "open access"). The Subversive Proposal also led to the development of the GNU EPrints software used for creating OAI-compliant open access institutional repositories, and inspired CiteSeer, a tool to locate and index the resulting eprints. The proposal was updated gradually across the years, as summarized in the American Scientist Open Access Forum on its 10th anniversary. A retrospective was written by Richard Poynder. A self-critique was posted on its 15th anniversary in


id: tri-agency-open-access-policy-on-publications-20260505-0
file: data/en.wikipedia.org/wiki/Tri-Agency_Open_Access_Policy_on_Publications-0.md
category: reference
title: Tri-Agency Open Access Policy on Publications
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Tri-Agency_Open_Access_Policy_on_Publications
date_saved: 2026-05-05T10:16:15.102611+00:00
instance: kb-cron
parent: tri-agency-open-access-policy-on-publications-20260505-0
summary:
Canada introduced the Tri-Agency Open Access Policy on Publications in May 2015 to mandate open access to research articles funded by Canada's three major research agencies: the Natural Sciences and Engineering Research Council (NSERC), the Social Sciences and Humanities Research Council (SSHRC) and the Canadian Institutes of Health Research (CIHR). CIHR has had an open access policy since 2008 and the new Tri-Agency policy is largely based on CIHR's pre-existing policy. The policy stipulates that peer-reviewed journal articles produced from funded research must be made open access within 12 months of publication by either: publication in an open access journal archiving in a subject repository or institutional repository == Applicability == The policy affects Tri-Agency grants awarded on or after May 1, 2015. All funded researchers are affected except graduate students and postdoctoral fellows. Only peer-reviewed journal articles are covered by the policy: other research outputs such as books or media, are not affected. Only postprints or final published articles may be archived in a subject or institutional repository; other article versions, e.g. preprints, are not acceptable. == Compliance == Enforcement of the Tri-Agency policy has not been explicitly described. Compliance with the CIHR open access policy has been managed


id: unza-institutional-repository-20260505-0
file: data/en.wikipedia.org/wiki/UNZA_Institutional_repository-0.md
category: reference
title: UNZA Institutional repository
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/UNZA_Institutional_repository
date_saved: 2026-05-05T10:16:17.342037+00:00
instance: kb-cron
parent: unza-institutional-repository-20260505-0
summary:
An institutional repository (IR) is simply a "digital archive of the intellectual products created by faculty research staff and students of an institution and accessible to end users both within and outside of the institution, with few if any barriers to access”. To enhance optimization and accessibility of the content in the IR, open access repositories are registered with the Directory of Open Access Repositories (OpenDOAR) which basically is a list of open academic repositories. Many universities have established IRs to promote open access to knowledge and information. The University of Zambia Institutional Repository (UNZA-IR) was established in 2010 with the support of the Netherlands Government to help archive the intellectual output of the university. The repository falls under the UNZA main Library and is headed by the repository manager who oversees the operations of the repository. The UNZA repository was created using Dspace, an "open source repository software package used for creating open access repositories. The UNZA repository houses research outputs including: post graduate research dissertations and thesis, research reports, conference presentations, book chapters and research articles (pre-prints and post prints). Currently, the repository houses approximately more than 8000 research publications with post graduate desertions and thesis being most


id: who-s-afraid-of-peer-review-20260505-0
file: data/en.wikipedia.org/wiki/Who's_Afraid_of_Peer_Review-0.md
category: reference
title: Who's Afraid of Peer Review?
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Who's_Afraid_of_Peer_Review?
date_saved: 2026-05-05T10:16:18.559856+00:00
instance: kb-cron
parent: who-s-afraid-of-peer-review-20260505-0
summary:
"Who's Afraid of Peer Review?" is an article written by Science correspondent John Bohannon that describes his investigation of peer review among fee-charging open-access journals. Between January and August 2013, Bohannon submitted fake scientific papers to 304 journals owned by fee-charging open access publishers. The papers, writes Bohannon, "were designed with such grave and obvious scientific flaws that they should have been rejected immediately by editors and peer reviewers", but 60% of the journals accepted them. The article and associated data were published in the 4 October 2013 issue of Science as open access. == Background == The first fee-charging open access scientific journals began appearing in 2000 with the creation of BioMed Central and then the Public Library of Science. Rather than deriving at least some of their revenue from subscription fees, fee-charging open access journals only charge the authors (or their funders) a publication fee. The published papers are then freely available on the internet. This business model, gold open access, is one of several solutions devised to make open access publishing sustainable. The number of articles published open access, or made freely available after some time behind a paywall (delayed open access), has grown rapidly. A 2013


id: who-s-afraid-of-peer-review-20260505-1
file: data/en.wikipedia.org/wiki/Who's_Afraid_of_Peer_Review-1.md
category: reference
title: Who's Afraid of Peer Review?
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Who's_Afraid_of_Peer_Review?
date_saved: 2026-05-05T10:16:18.559856+00:00
instance: kb-cron
parent: who-s-afraid-of-peer-review-20260505-0
summary:
=== Responses from open-access academic publishers === Since the story was released, publishers of three journals have stated that they are shutting them down. The DOAJ is reviewing its list and instituting tighter criteria for inclusion. The Open Access Scholarly Publishers Association (OASPA) formed a committee to investigate the circumstances that led to the acceptance of the fake paper by three of its members. On 11 November 2013, OASPA terminated the membership of two publishers (Dove Medical Press and Hikari Ltd.) who accepted the fake paper. SAGE Publications, which also accepted a fake paper, was put "under review" for 6 months. Sage announced in a statement that it was reviewing the journal that accepted the fake paper, but that it would not shut it down. Sage's membership was reinstated at the end of the review period following changes to the journal's editorial processes. === Responses from the scientific community === Within hours of its publication, the Science investigation came under intense criticism by some supporters of the open-access movement. The first substantial critique was posted by PLOS cofounder Michael Eisen on his blog. "To suggest – as Science (though not Bohannon) are trying to do – that the problem with


id: worldpop-project-20260505-0
file: data/en.wikipedia.org/wiki/WorldPop_Project-0.md
category: reference
title: WorldPop Project
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/WorldPop_Project
date_saved: 2026-05-05T10:16:19.821014+00:00
instance: kb-cron
parent: worldpop-project-20260505-0
summary:
WorldPop is a research programme based in the School of Geography and Environmental Science, University of Southampton. The programme employs a multidisciplinary team of researchers, analysts, GIS technicians, and project specialists who construct open data on populations and population attributes at high spatial resolution. Created from a combination of The AfriPop Project, AmeriPop, and AsiaPop projects in 2013, WorldPop engages in geospatial demographic projects with governments and institutions in low- and middle-income countries (LMICs) as well as collaborations with partner organisations, such as the Bill & Melinda Gates Foundation, Gavi, the Vaccine Alliance, United Nations agencies, the UK Foreign, Commonwealth and Development Office, commercial data providers and other international development organisations. The programme provides training in population modelling to ministries of health and national statistical offices in LMICs and works with them to support health and demographic surveys to achieve Sustainable Development Goals == Areas of interest == Demography Geographic information system data Satellite imagery Remote sensing Effects of Non-pharmaceutical intervention (epidemiology) on COVID-19 Geospatial predictive modeling == Population estimation == WorldPop develops statistical population modelling methods to produce gridded population estimates that support census activities. The programme develops new methods for data synthesis that use demographic and health surveys,


id: open-data-20260505-0
file: data/en.wikipedia.org/wiki/Open_data-0.md
category: reference
title: Open data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_data
date_saved: 2026-05-05T10:16:21.318197+00:00
instance: kb-cron
parent: open-data-20260505-0
summary:
Open data are data that are openly accessible, exploitable, editable and shareable by anyone for any purpose. Open data are generally licensed under an open license. The goals of the open data movement are similar to those of other "open(-source)" movements such as open-source software, open-source hardware, open content, open specifications, open education, open educational resources, open government, open knowledge, open access, open science, and the open web. The growth of the open data movement is paralleled by a rise in intellectual property rights. The philosophy behind open data has been long established (for example in the Mertonian tradition of science), but the term "open data" itself is recent, gaining popularity with the rise of the Internet and World Wide Web and, especially, with the launch of open-data government initiatives Data.gov, Data.gov.uk and Data.gov.in. Open data can be linked data—referred to as linked open data. One of the most important forms of open data is open government data (OGD), which is a form of open data created by ruling government institutions. The importance of open government data is born from it being a part of citizens' everyday lives, down to the most routine and mundane tasks that are seemingly far


id: open-data-20260505-1
file: data/en.wikipedia.org/wiki/Open_data-1.md
category: reference
title: Open data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_data
date_saved: 2026-05-05T10:16:21.318197+00:00
instance: kb-cron
parent: open-data-20260505-0
summary:
There are a range of different arguments for government open data. Some advocates say that making government information available to the public as machine readable open data can facilitate government transparency, accountability and public participation. "Open data can be a powerful force for public accountability—it can make existing information easier to analyze, process, and combine than ever before, allowing a new level of public scrutiny." Governments that enable public viewing of data can help citizens engage within the governmental sectors and "add value to that data." Open data experts have nuanced the impact that opening government data may have on government transparency and accountability. In a widely cited paper, scholars David Robinson and Harlan Yu contend that governments may project a veneer of transparency by publishing machine-readable data that does not actually make government more transparent or accountable. Drawing from earlier studies on transparency and anticorruption, World Bank political scientist Tiago C. Peixoto extended Yu and Robinson's argument by highlighting a minimal chain of events necessary for open data to lead to accountability: relevant data is disclosed; the data is widely disseminated and understood by the public; the public reacts to the content of the data; and public officials either


id: open-data-20260505-2
file: data/en.wikipedia.org/wiki/Open_data-2.md
category: reference
title: Open data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_data
date_saved: 2026-05-05T10:16:21.318197+00:00
instance: kb-cron
parent: open-data-20260505-0
summary:
permanent, persistent digital IDs, which enable access controls for datasets; permanent, discoverable metadata associated with each digital ID; application programming interface (API)-based access, tied to an authentication and authorization service; data portability; data "peering," without access, egress, and ingress charges; and a rationed approach to users computing data over the data commons. Beyond individual businesses and research centers, and at a more macro level, countries like Germany have launched their own official nationwide open data strategies, detailing how data management systems and data commons should be developed, used, and maintained for the greater public good. == Arguments for and against == Opening government data is only a waypoint on the road to improving education, improving government, and building tools to solve other real-world problems. While many arguments have been made categorically, the following discussion of arguments for and against open data highlights that these arguments often depend highly on the type of data and its potential uses. Arguments made on behalf of open data include the following: "Data belongs to the human race". Typical examples are genomes, data on organisms, medical science, environmental data following the Aarhus Convention. Public money was used to fund the work, and so it should


id: open-data-20260505-3
file: data/en.wikipedia.org/wiki/Open_data-3.md
category: reference
title: Open data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_data
date_saved: 2026-05-05T10:16:21.318197+00:00
instance: kb-cron
parent: open-data-20260505-0
summary:
Open access is concerned with making scholarly publications freely available on the internet. In some cases, these articles include open datasets as well. Open specifications are documents describing file types or protocols, where the documents are openly licensed. These specifications are primarily meant to improve different software handling the same file types or protocols, but monopolists forced by law into open specifications might make it more difficult. Open content is concerned with making resources aimed at a human audience (such as prose, photos, or videos) freely available. Open knowledge. Open Knowledge International argues for openness in a range of issues including, but not limited to, those of open data. It covers (a) scientific, historical, geographic or otherwise (b) Content such as music, films, books (c) Government and other administrative information. Open data is included within the scope of the Open Knowledge Definition, which is alluded to in Science Commons' Protocol for Implementing Open Access Data. Open notebook science refers to the application of the Open Data concept to as much of the scientific process as possible, including failed experiments and raw experimental data. Open-source software is concerned with the open-source licenses under which computer programs can be distributed and is


id: open-data-20260505-4
file: data/en.wikipedia.org/wiki/Open_data-4.md
category: reference
title: Open data
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Open_data
date_saved: 2026-05-05T10:16:21.318197+00:00
instance: kb-cron
parent: open-data-20260505-0
summary:
=== Real-life case === Application of open data for societal good has been demonstrated in academic research works. The paper "Optimization of Soft Mobility Localization with Sustainable Policies and Open Data" uses open data in two ways. First, it uses open data to identify the needs of different areas of a city. For example, it might use data on population density, traffic congestion, and air quality to determine where soft mobility resources, such as bike racks and charging stations for electric vehicles, are most needed. Second, it uses open data to develop algorithms that are fair and equitable. For example, it might use data on the demographics of a city to ensure that soft mobility resources are distributed in a way that is accessible to everyone, regardless of age, disability, or gender. The paper also discusses the challenges of using open data for soft mobility optimization. One challenge is that open data is often incomplete or inaccurate. Another challenge is that it can be difficult to integrate open data from different sources. Despite these challenges, the paper argues that open data is a valuable tool for improving the sustainability and equity of soft mobility in cities. An exemplification of how


id: 2025-united-states-government-online-resource-removals-20260505-0
file: data/en.wikipedia.org/wiki/2025_United_States_government_online_resource_removals-0.md
category: reference
title: 2025 United States government online resource removals
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/2025_United_States_government_online_resource_removals
date_saved: 2026-05-05T10:16:22.498115+00:00
instance: kb-cron
parent: 2025-united-states-government-online-resource-removals-20260505-0
summary:
The 2025 United States government online resource removals are a series of web page and dataset deletions and modifications across multiple United States federal agencies beginning in January 2025. Following executive orders from President Donald Trump's administration, government organizations removed or modified over 8,000 web pages and approximately 3,000 datasets. The changes primarily affected content related to diversity, equity, and inclusion (DEI) initiatives, gender identity, public health research, environmental policy, and various social programs, and other topics Trump and the Republican Party has expressed opposition to. Major affected agencies included the Centers for Disease Control and Prevention, which saw over 3,000 pages altered or removed, and the Census Bureau, which removed about 3,000 pages of research materials. While some content was later restored, the modifications represented significant changes to federal government data accessibility and sparked legal challenges from healthcare advocacy groups. == Background == Agencies of the United States government share open data for many uses. There are many civic technology, research, and business applications which rely on access to government data. Dataset deletion can be useful maintenance or the result of poor archiving practice. There is little government regulation on dataset management, so it can be challenging to determine


id: 2025-united-states-government-online-resource-removals-20260505-1
file: data/en.wikipedia.org/wiki/2025_United_States_government_online_resource_removals-1.md
category: reference
title: 2025 United States government online resource removals
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/2025_United_States_government_online_resource_removals
date_saved: 2026-05-05T10:16:22.498115+00:00
instance: kb-cron
parent: 2025-united-states-government-online-resource-removals-20260505-0
summary:
In January, NASA undertook a comprehensive removal of DEI-related content from its public-facing websites. An internal directive instructed employees to "drop everything" and immediately eliminate references to terms such as "DEIA", "indigenous people", "environmental justice", "underrepresented groups/people", and content specifically targeting women, including content about "women in leadership". This purge resulted in the deletion of various materials, including interviews with Black and female NASA employees, LGBTQ-related content, and two NASA-created comic books about women astronauts. More than 3,000 pages from the Census Bureau website were removed as of February 2, primarily including articles filed under research and methodology. Pages relating to data stewardship as well as survey and data set documentation were also removed. The Food and Drug Administration (FDA) removed more than 100 pages as of February 2, including dozens of regulatory guidelines on topics such as increasing diversity in clinical trials and the potential for addiction and abuse in drug studies. Close to 50 research papers from the Office of Scientific and Technical Information – part of the Department of Energy – were removed as of February 2. The removed papers covered a range of subjects, such as chemistry, optics, and experimental medicine. Twenty pages from the National


id: 2025-united-states-government-online-resource-removals-20260505-2
file: data/en.wikipedia.org/wiki/2025_United_States_government_online_resource_removals-2.md
category: reference
title: 2025 United States government online resource removals
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/2025_United_States_government_online_resource_removals
date_saved: 2026-05-05T10:16:22.498115+00:00
instance: kb-cron
parent: 2025-united-states-government-online-resource-removals-20260505-0
summary:
The Internal Revenue Service removed more than 25 pages as of February 2, including a form that private schools are required to submit annually to certify that they had not engaged in racial discrimination. The Consumer Financial Protection Bureau (CFPB) removed 386 videos from its official YouTube channel. As of February 2, there were 18 pages removed from the United States Patent and Trademark Office website, including information about veteran inventors and entrepreneurs, and a high school program teaching about intellectual property. The Department of the Interior removed eight pages from their website as of February 2, including several with information on environmental policy initiatives. The New York Times speculated that some of the pages may have been removed due to the use of the phrase "environmental justice". The National Park Service removed all references to the existence of transgender people from its webpages covering the Stonewall National Monument, the Stonewall riots, and LGBTQ+ history, changing the acronym from "LGBTQ+" to "LGB". As of February 3, four pages from the Nuclear Regulatory Commission have been deleted, including an overview of the commission's equal employment opportunity and diversity initiatives. The FDA's Office of Minority Health and Health Equity website was removed,


id: 2025-united-states-government-online-resource-removals-20260505-3
file: data/en.wikipedia.org/wiki/2025_United_States_government_online_resource_removals-3.md
category: reference
title: 2025 United States government online resource removals
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/2025_United_States_government_online_resource_removals
date_saved: 2026-05-05T10:16:22.498115+00:00
instance: kb-cron
parent: 2025-united-states-government-online-resource-removals-20260505-0
summary:
== Reactions == Representatives from the Population Association of America, the Council of Professional Associations on Federal Statistics, and the Association of Public Data Users (APDU) expressed disapproval of the data deletion. President of the APDU, Amy O'Hara, described a "mad scramble" as researchers searched for copies of the deleted data. Former US Department of Labor chief evaluation officer and board member of Data Foundation Molly Irwin warned of the dangers of deleting critical government data. She highlighted government data is a critical component of how politicians and analysts evaluate whether a particular policy is working as intended. The stock market, bond market, and Federal Reserve all continuously make decisions based on labor data. This data is typically stable, but changes to it reduce confidence in data about the economy. Uncertainty also encourages conspiracy theories which view government data as intentionally incorrect for malicious purposes. Furthermore, businesses rely on the essentially free government data as a part of their own operations, planning, products and services. Zillow, for example, utilizes government data to generate their product of real estate information and analysis. Scientists reacted by saying that they would restore access to some data, but doing so is not easy. The


id: academic-torrents-20260505-0
file: data/en.wikipedia.org/wiki/Academic_Torrents-0.md
category: reference
title: Academic Torrents
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Academic_Torrents
date_saved: 2026-05-05T10:16:23.948246+00:00
instance: kb-cron
parent: academic-torrents-20260505-0
summary:
Academic Torrents is a website which enables the sharing of research data using the BitTorrent protocol. The site was founded in November 2013, and is a project of the Institute for Reproducible Research (a 501(c)3 U.S. non-profit corporation). The project is said to be similar to LOCKSS but with a focus on "offering researchers the opportunity to distribute the hosting of their papers and datasets to authors and readers, providing easy access to scholarly works and simultaneously backing them up on computers around the world." == Notable datasets == === Developing Human Connectome Project === The developing Human Connectome Project related to the Human Connectome Project uses the platform. "Researchers from three leading British institutions are using BitTorrent to share over 150 GB of unique high-resolution brain scans of unborn babies with colleagues worldwide... The researchers opted to go for the Academic Torrents tracker, which specializes in sharing research data" === CrossRef metadata === The site hosts public metadata releases from Crossref which contain over 120+ million metadata records for scholarly work, each with a DOI. This was done so to allow the community to work with the entire database programmatically instead of using their API. "The sheer number of


id: american-art-collaborative-20260505-0
file: data/en.wikipedia.org/wiki/American_Art_Collaborative-0.md
category: reference
title: American Art Collaborative
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/American_Art_Collaborative
date_saved: 2026-05-05T10:16:26.351822+00:00
instance: kb-cron
parent: american-art-collaborative-20260505-0
summary:
The American Art Collaborative (AAC) is a consortium of 14 art museums in the United States, whose mission is the establishment of "a critical mass of linked open data (LOD) on the semantic web." As of 2024, the AAC has converted over 230,000 museum object records to linked open data. == Membership == As of 2024, the 14 members are: Amon Carter Museum of American Art Archives of American Art, Smithsonian Institution Autry Museum of the American West Colby College Museum of Art Crystal Bridges Museum of American Art Dallas Museum of Art (DMA) Indianapolis Museum of Art (IMA) Thomas Gilcrease Institute of American History and Art National Portrait Gallery, Smithsonian Institution National Museum of Wildlife Art Princeton University Art Museum Smithsonian American Art Museum Walters Art Museum Yale Center for British Art == References == == External links == Official website


id: art-architecture-thesaurus-20260505-0
file: data/en.wikipedia.org/wiki/Art_&_Architecture_Thesaurus-0.md
category: reference
title: Art & Architecture Thesaurus
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Art_&_Architecture_Thesaurus
date_saved: 2026-05-05T10:16:27.520520+00:00
instance: kb-cron
parent: art-architecture-thesaurus-20260505-0
summary:
The Art & Architecture Thesaurus (AAT) is a controlled vocabulary used for describing items of art, architecture, and material culture. The AAT contains generic terms, such as "cathedral", but no proper names, such as "Cathedral of Notre Dame." The AAT is used by, among others, museums, art libraries, archives, catalogers, and researchers in art and art history. The AAT is a thesaurus in compliance with ISO and NISO standards including ISO 2788, ISO 25964 and ANSI/NISO Z39.19. The AAT is a structured vocabulary of 55,661 concepts (as of January 2020), including 131,000 terms, descriptions, bibliographic citations, and other information relating to fine art, architecture, decorative arts, archival materials, and material culture. == History == The AAT project began in the late 1970s in response to the gradual automation of records by art libraries, art journal indexing services, and catalogers of museum objects and visual resources. Automation required consistency in cataloging as well as more efficient retrieval of information; a controlled vocabulary was a solution to both these problems. The project was conceived by library directors and architectural experts Toni Petersen, Dora Crouch, and Pat Molholt and was originally headquartered part-time at Rensselaer Polytechnic Institute in Troy, NY, then at Bennington


id: biblios-net-20260505-0
file: data/en.wikipedia.org/wiki/‡biblios.net-0.md
category: reference
title: ‡biblios.net
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/‡biblios.net
date_saved: 2026-05-05T10:16:28.685475+00:00
instance: kb-cron
parent: biblios-net-20260505-0
summary:
‡biblios.net is a free browser-based cataloging service with a data store containing over thirty million records. Records are licensed under the Open Data Commons Public Domain Dedication and License, making the service the world's largest repository of freely-licensed library records. The service was created and is maintained by LibLime. == Features == ‡biblios.net (pronounced 'biblios dot net') features a metadata editor with templates, macros, authority auto-completion and embedded context-sensitive help. The central record repository contains 25-million bibliographic records and just under eight-million authority records. The data is maintained by ‡biblios.net users. Catalogers can use and contribute to the database without restrictions because records in ‡biblios.net are freely-licensed under the Open Data Commons Public Domain Dedication and License. ‡biblios.net also includes a built-in federated search system, allowing catalogers to find records from any Z39.50 target. Additionally, there is a central Search Target Registry, seeded with over 2,000 Z39.50 servers, for catalogers to find, create and share Z39.50 targets. In addition to offering a traditional cataloging interface, ‡biblios.net offers social cataloging features. Built-in forums and private messaging make finding help and communicating with others possible within the software. == References == == External links == ‡biblios.net Website LibLime's Homepage


id: irina-bolychevsky-20260505-0
file: data/en.wikipedia.org/wiki/Irina_Bolychevsky-0.md
category: reference
title: Irina Bolychevsky
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Irina_Bolychevsky
date_saved: 2026-05-05T10:16:29.872986+00:00
instance: kb-cron
parent: irina-bolychevsky-20260505-0
summary:
Irina Bolychevsky (born 1986) is a British activist and data specialist, focused on Open Data, decentralized technologies, and technical standards. She is currently director of standards and interoperability at the NHSX of the United Kingdom Government. She has been part of large organizations in those fields, including the Open Knowledge Foundation, the World Wide Web Consortium, and the Open Data Institute, and worked for the UK, Dubai and UAE government administrations. She co-founded Redecentralize.org, an advocacy group promoting decentralized technologies. == Work == She was the product owner of the open-source open data portal CKAN from 2011 to 2014, the period in which it was redesigned in a 2.0 version and where she piloted the transition from a mostly national use in 2011, to international adoption. In this period, she managed its adoption by and relaunch of data.gov. Her work with CKAN allowed her to win the Open Data Individual Champion Award by the Open Data Institute. Bolychevsky was W3C staff from July 2015 till December 2016. During this period, she was part of the W3C Social Web working group. She actively participated in EU-funded research projects in which the W3C was part of, working on open standards for decentralized


id: bus-open-data-service-20260505-0
file: data/en.wikipedia.org/wiki/Bus_Open_Data_Service-0.md
category: reference
title: Bus Open Data Service
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Bus_Open_Data_Service
date_saved: 2026-05-05T10:16:31.060926+00:00
instance: kb-cron
parent: bus-open-data-service-20260505-0
summary:
The Bus Open Data Service (BODS) is a government-funded service in England, established in 2020 as part of the Bus Services Act 2017. It was created in a partnership between Ito World, the Department for Transport and KPMG. The service was described by Ito World as "an international first", as it provides Open Data of bus timetables, fares and Automatic Vehicle Location of buses across England. An extension to the Bus Open Data Service, Analyse Bus Open Data Service (ABOD), was introduced in 2021 to provide free-to-access reporting and analytics to operators and authorities nationally. The extended service provides access to on-time performance analytics, vehicle journey replays, and corridor reporting. == Data implementation == As part of the requirements set by the Department for Transport in The Public Service Vehicles (Open Data) (England) Regulations 2020, the Bus Open Data Service set deadlines for operators to provide data. The implementation requirements only applied in England 31 December 2020 — Obligation to provide bus timetable data to the Bus Open Data Service. 7 January 2021 — Obligation to provide vehicle location and basic fares and tickets data to the Bus Open Data Service. 7 January 2023 — Obligation to provide complex fares


id: bustimes-org-20260505-0
file: data/en.wikipedia.org/wiki/Bustimes.org-0.md
category: reference
title: Bustimes.org
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Bustimes.org
date_saved: 2026-05-05T10:16:32.220241+00:00
instance: kb-cron
parent: bustimes-org-20260505-0
summary:
bustimes.org is a transportation information website created to take advantage of Bus Services Act 2017 requirement for bus operators in England to provide bus timetables, fares and vehicle locations in an open data format, which can be utilised by app and website developers. This DfT service is called the Bus Open Data Service. The website also provides information on bus services in parts of the UK to which the Bus Services Act 2017 information requirement does not apply, as well as in Ireland. Location data for operators partially or completely owned by Transport for Edinburgh, is supplied to the site via their Open Data system. The site uses data from AVL tracking to determine and transmit the geographic location of a vehicle, such as data from Ticketer machines and the iBus system, in order to display live bus positions on a map. The site also uses data from the National Public Transport Gazetteer, and bus stop locations from NaPTAN. The live tracking system was added in response to the Department for Transport stating that they wanted "to see more people taking the bus, and those who do take it to have the best possible experience." with fares for companies operating


id: ckan-20260505-0
file: data/en.wikipedia.org/wiki/CKAN-0.md
category: reference
title: CKAN
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/CKAN
date_saved: 2026-05-05T10:16:33.414538+00:00
instance: kb-cron
parent: ckan-20260505-0
summary:
The Comprehensive Knowledge Archive Network (CKAN) is an open-source open data portal for the storage and distribution of open data. Initially inspired by the package management capabilities of Debian Linux, CKAN has developed into a powerful data catalogue system that is mainly used by public institutions seeking to share their data with the general public. Since its inception, CKAN has evolved and is the leading open data platform software in the world, used by governments including the US and UK, to publish millions of public datasets. Rufus Pollock developed its first version in 2005-2006. CKAN's codebase is maintained by the Open Knowledge Foundation. The system is used both as a public platform on Datahub and in various government data catalogues, such as the UK's data.gov.uk, the Dutch National Data Register, the United States government's Data.gov and the Australian government's "Gov 2.0". The state government of South Australia also makes government data freely available to the public on the CKAN platform. The Italian government makes available the open data of the Data & Analytics Framework on the CKAN platform. == Internal technology == CKAN's back end, the part running on the Web server, is written mainly in Python. The web pages


id: concepticon-20260505-0
file: data/en.wikipedia.org/wiki/Concepticon-0.md
category: reference
title: Concepticon
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Concepticon
date_saved: 2026-05-05T10:16:34.587218+00:00
instance: kb-cron
parent: concepticon-20260505-0
summary:
Concepticon is an open-source online lexical database of linguistic concept lists (word lists). It links concept labels (i.e., word list glosses) in concept lists (i.e., word lists) to concept sets (i.e., standardized word meanings). It is part of the Cross-Linguistic Linked Data (CLLD) project, which is hosted by the Max Planck Institute for the Science of Human History in Jena, Germany. Version 1.0 was released in 2016. == Concept == Concept lists in the Concepticon include: Swadesh list (100 items, 207 items, etc.) Swadesh–Yakhontov list Dolgopolsky list Leipzig–Jakarta list ASJP list == See also == Conceptualization (information science) Ontology (information science) Intercontinental Dictionary Series == References == List, Johann Mattis & Rzymski, Christoph & Greenhill, Simon & Schweikhard, Nathanael & Pianykh, Kristina & Tjuka, Annika & Hundt, Carolin & Forkel, Robert (eds.) 2021. CLLD Concepticon 2.5.0 [Data set]. Zenodo. doi:10.5281/zenodo.4911605 == External links == Official website Langavia Dictionary Synonyms Dictionary Concepticon on GitHub


id: coronavirus-tech-handbook-20260505-0
file: data/en.wikipedia.org/wiki/Coronavirus_Tech_Handbook-0.md
category: reference
title: Coronavirus Tech Handbook
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Coronavirus_Tech_Handbook
date_saved: 2026-05-05T10:16:35.788490+00:00
instance: kb-cron
parent: coronavirus-tech-handbook-20260505-0
summary:
The Coronavirus Tech Handbook was a website designed to crowdsource information about the SARS-CoV-2 coronavirus. It was developed at Newspeak House, a hackerspace for politics in London, England. The site, which launched in March 2020, was hosted as an interlinked collection of user-editable online documents, which made it effectively a wiki. As of October 2020 it had expanded to provide tools for consumers, businesses, local governments, and developers, amongst others, to help combat the COVID-19 pandemic. Its stated aim was to provide: a space for technologists, civic organisations, public & private institutions, researchers and specialists of all kinds to collaborate on a rapid and sophisticated response to the coronavirus outbreak and subsequent impacts. == References ==


id: covid-act-now-20260505-0
file: data/en.wikipedia.org/wiki/Covid_Act_Now-0.md
category: reference
title: Covid Act Now
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Covid_Act_Now
date_saved: 2026-05-05T10:16:36.944943+00:00
instance: kb-cron
parent: covid-act-now-20260505-0
summary:
Covid Act Now (CAN) is an independent, 501(c)(3) nonprofit that provides local-level disease intelligence and data analysis on the COVID-19 pandemic in the United States, via a website and an API. CAN assists partners ranging from local county health departments to multinational corporations in developing COVID response plans. Its API is used by many of the Fortune 500 to make data-driven reopening decisions. The organization's first product was a traditional SEIR model for predicting the rate of COVID spread in the U.S. The model was based on open-source code by Alison Hill, an assistant professor at the Johns Hopkins’ Institute for Computational Medicine. Rebecca Katz and her team have served as critical advisors. CAN's modelling and data partners include Grand Rounds, a digital healthcare company, and USA Facts. Its university affiliates are Georgetown University Medical Center, Stanford Medicine, and Harvard Global Health Institute. == History == CAN began as a collaboration between four volunteers — Max Henderson (a former Google employee), Igor Kofman (a former Dropbox engineer), Zachary Rosen, and Jonathan Kreiss-Tomkins — publishing the first version of their model on March 20, 2020. The team was soon joined by public health experts, data scientists, and other professionals. The initial


id: covid-moonshot-20260505-0
file: data/en.wikipedia.org/wiki/COVID_Moonshot-0.md
category: reference
title: COVID Moonshot
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/COVID_Moonshot
date_saved: 2026-05-05T10:16:38.156021+00:00
instance: kb-cron
parent: covid-moonshot-20260505-0
summary:
The COVID Moonshot is a collaborative open-science project started in March 2020 with the goal of developing an un-patented oral antiviral drug to treat SARS-CoV-2, the virus causing COVID-19. COVID Moonshot researchers are targeting the proteins needed to form functioning new viral proteins. They are particularly interested in proteases such as 3C-like protease (Mpro), a coronavirus nonstructural protein that mediates the breaking and replication of proteins. COVID Moonshot may be the first open-science community effort for the development of an antiviral drug. Hundreds of scientists around the world, from academic and industrial organizations, have shared their expertise, resources, data, and results to more rapidly identify, screen, and test candidate compounds for the treatment of COVID-19. == Project history == Development of antiviral drugs is a complicated and time-consuming multistage process. The public sharing of information in the early stages of genome identification and protein structure identification has accelerated the process of searching for COVID-19 treatments and established a basis for the COVID Moonshot initiative. === Genome identification === On January 3, 2020, Chinese virologist Yong-Zhen Zhang of Fudan University and the Shanghai Public Health Clinical Center received a test sample from Wuhan, China, where patients had a pneumonia-like illness. By


id: covid-moonshot-20260505-1
file: data/en.wikipedia.org/wiki/COVID_Moonshot-1.md
category: reference
title: COVID Moonshot
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/COVID_Moonshot
date_saved: 2026-05-05T10:16:38.156021+00:00
instance: kb-cron
parent: covid-moonshot-20260505-0
summary:
The design submissions were stored in Collaborative Drug Discovery's CDD Vault, a database used for large-scale management of chemical structures, experimental protocols and experimental results. Alpha Lee and Matt Robinson brought computational expertise from PostEra to the project. PostEra used techniques from artificial intelligence and machine learning to develop analysis tools for computational drug discovery, chemical synthesis and biochemical assays. When COVID Moonshot's appeal resulted in not hundreds but thousands of responses, they built a platform capable of triaging large numbers of compounds and designing routes for their synthetic formation. Supercomputer access was provided through the COVID-19 High Performance Computing (HPC) Consortium, accelerating the speed at which designs could be examined and compared. The distributed supercomputing initiative Folding@home has carried out multiple sprints to model novel protein structures and target desirable structures as a part of COVID Moonshot. Many of the criteria for selecting drug candidates were determined by the group's goals. An ideal drug candidate would be effective in treating COVID-19. It also would be easily and cheaply made, so that as many countries and companies as possible could produce and distribute it. The ingredients to make it should be easy to obtain, and the processes involved should be


id: merc-crosas-20260505-0
file: data/en.wikipedia.org/wiki/Mercè_Crosas-0.md
category: reference
title: Mercè Crosas
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Mercè_Crosas
date_saved: 2026-05-05T10:16:39.344482+00:00
instance: kb-cron
parent: merc-crosas-20260505-0
summary:
Mercè Crosas (born 1966, Barcelona) is a researcher and technologist specializing in data science, data management, and open data. Since November 2023 she is President of CODATA, the Committee on Data of the International Science Council. Crosas is the Director of Computational Social Sciences and Humanities at the Barcelona Supercomputing Center. == Biography == Crosas holds a degree in physics from the University of Barcelona (1989) and a PhD in astrophysics from Rice University (Houston, Texas, 1992), with predoctoral and postdoctoral stays at the Harvard-Smithsonian Center for Astrophysics. She has spent most of her professional life at Harvard University, first as an astrophysicist and research software engineer at the Harvard-Smithsonian Center for Astrophysics and later as Director of Data Science and Technology at the Institute for Quantitative Social Sciences, from Harvard University and as Chief Research Data Management Officer at Harvard University. From 2000 to 2004, she worked outside of Harvard at a pair of biotech startups leading software development teams to build their research data systems. During her time at Harvard University, Crosas worked closely with research, computing services, and libraries to direct the management and publication of research data and provide guidance on University policies, processes, and tools


id: data-collaboratives-20260505-0
file: data/en.wikipedia.org/wiki/Data_collaboratives-0.md
category: reference
title: Data collaboratives
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Data_collaboratives
date_saved: 2026-05-05T10:16:40.563232+00:00
instance: kb-cron
parent: data-collaboratives-20260505-0
summary:
Data collaboratives (sometimes called "corporate data philanthropy") are a form of collaboration in which participants from different sectors—including private companies, research institutions, and government agencies—can exchange data and data expertise to help solve public problems. == Types == Data collaboratives can take many forms. They can be organized as: Public Interfaces: Private firms publish select data assets to be public for use by external parties. Firms typically present this information as Application Programming Interfaces (APIs) or data platforms. Trusted Intermediary: Private sector firms share data with partners from public, civil society actors, and academia. Data can be brokered by third parties, who provide valuable data under fixed terms and time limits to non-private organizations. It can also be run through third-party analytics, which shares data with data stewards to run analysis and share those findings with external actors, providing the outcomes of the data without exposing the sensitive information. Data Pooling: Multi-sectoral stakeholders join "data pools" to share data resources. Public data pools allow partners to openly access and independently use the data, while private data pools limit access and contribution to the information. Research and Analysis Partnership: Organizations share data and "proprietary data assets" with public and academic institutions


