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:books: :microscope: :unlock: :mag: A curated list of resources, data, tools, scholarship related to Open Access, Data and Open Science :books: :microscope: :unlock: :mag:
https://github.com/ZoranPandovski/awesome-open-science

List: awesome-open-science

data-science hacktoberfest open-access open-data open-data-science open-scholarship open-science open-source research research-data science-publishing science-research

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:books: :microscope: :unlock: :mag: A curated list of resources, data, tools, scholarship related to Open Access, Data and Open Science :books: :microscope: :unlock: :mag:

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README

        

# Awesome Open Science [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)

> A curated list of resources, data, tools, scholarship related to Open Access, Data and Open Science

# Note: this list is still under development :wrench: :construction_worker:

## Table of Contents

- [Research Data](#research-data)
- [Tools](#tools)
- [Organizations](#organizations)
- [Courses](#courses)
- [Events](#events)
- [Books](#books)
- [Fundings](#fundings)
- [Similar Awesome Lists](#similar-awesome-lists)

## Research Data

- [E-learning platform](http://www.researchdatamanagement.ch/)
- [Finnish Social Science Data Archive](https://www.fsd.uta.fi/en/)
- [BASE](https://www.base-search.net/) - Biefeld academic search engine
- [Academia](https://www.academia.edu/) - Academia.edu is a platform for academics to share research papers
- [Research Gate](https://www.researchgate.net/) - ResearchGate is the professional network for scientists and researchers

## Research Articles and Reports

- [Research Objects: Towards Exchange and Reuse of Digital Knowledge](http://precedings.nature.com/documents/4626/version/1) - Bechhofer et al., 2010
- [The Enduring Value of Social Science Research: The Use and Reuse of Primary Research Data](https://deepblue.lib.umich.edu/handle/2027.42/78307) - Pienta et al., 2010
- [The data paper: a mechanism to incentivize data publishing in biodiversity science](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-12-S15-S2) - Chavan and Penev, 2011
- [The Dataverse Network: An Open-Source Application for Sharing, Discovering and Preserving Data](http://www.dlib.org/dlib/january11/crosas/01crosas.html) - Crosas, 2011
- [Data sharing in neuroimaging research](https://www.frontiersin.org/articles/10.3389/fninf.2012.00009/full) - Poline et al., 2012
- [Toward interoperable bioscience data](https://www.nature.com/articles/ng.1054) - Sansone et al., 2012
- [Making data sharing count: a publication-based solution](https://www.frontiersin.org/articles/10.3389/fnins.2013.00009/full), Gorgolewski et al., 2013
- [EUDAT: A New Cross-Disciplinary Data Infrastructure for Science](http://www.ijdc.net/article/view/8.1.279) - Lecarpentier et al., 2013
- [Data reuse and the open data citation advantage](https://peerj.com/articles/175/) - Piwowar and Vision, 2013
- [Nine simple ways to make it easier to (re)use your data](https://peerj.com/preprints/7/) - White et al., 2013
- [The data sharing advantage in astrophysics](https://arxiv.org/abs/1511.02512) - Dorch et al., 2015
- [What Drives Academic Data Sharing?](http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0118053) - Fecher et al., 2015
- [From Peer-Reviewed to Peer-Reproduced in Scholarly Publishing: The Complementary Roles of Data Models and Workflows in Bioinformatics](http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0127612) - Gonzalez-Beltran et al., 2015
- [Making data count](https://www.nature.com/articles/sdata201539) - Kratz and Strasser, 2015
- [The center for expanded data annotation and retrieval](https://academic.oup.com/jamia/article/22/6/1148/2357598) - Musen et al., 2015
- [Public Data Archiving in Ecology and Evolution: How Well Are We Doing?](http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002295) - Roche et al., 2015
- [Achieving human and machine accessibility of cited data in scholarly publications](https://peerj.com/articles/cs-1/) - Starr et al., 2015
- [The State of Open Data Report](https://figshare.com/articles/The_State_of_Open_Data_Report/4036398) - Treadway et al., 2016
- [The FAIR Guiding Principles for scientific data management and stewardship](https://www.nature.com/articles/sdata201618) - Wilkinson et al., 2016
- [Towards coordinated international support of core data resources for the life sciences](https://www.biorxiv.org/content/early/2017/04/27/110825) - Anderson et al., 2017
- [A reputation economy: how individual reward considerations trump systemic arguments for open access to data](https://www.nature.com/articles/palcomms201751) - Fecher et al., 2017
- [Cloudy, increasingly FAIR; revisiting the FAIR Data guiding principles for the European Open Science Cloud](https://content.iospress.com/articles/information-services-and-use/isu824) - Mons et al., 2017
- [Code of practice for research data usage metrics release 1](https://peerj.com/preprints/26505/) - Fenner et al., 2018
- [Open Data as Open Educational Resources: Towards Transversal Skills and Global Citizenship](http://dx.doi.org/10.5944/openpraxis.7.4.233) - Atenas, Havemann, Priego, 2015
- [Reproducibility, Virtual Appliances, and Cloud Computing](https://osf.io/sp2vg/), Howe,2012
- [The Ironic Effect of Significant Results on the Credibility of Multiple-Study Articles](http://datacolada.org/wp-content/uploads/2014/06/3644-Schimmack-PM-2012-the-ironic-effect-of-significant-results-on-the-credibilit-of-multiple-study-articles.pdf), Schimmack, 2012
- [Power failure: why small sample size undermines the reliability of neuroscience](https://www.nature.com/articles/nrn3475), Button et al., 2013
- [Git can facilitate greater reproducibility and increased transparency in science](https://scfbm.biomedcentral.com/articles/10.1186/1751-0473-8-7). Ram, 2013
- [Ten simple rules for reproducible computational research](http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003285), Sandve et al., 2013
- [Investigating Variation in Replicability: A "Many Labs" Replication Project](https://econtent.hogrefe.com/doi/abs/10.1027/1864-9335/a000178), Klein et al., 2014
- [An introduction to Docker for reproducible research](https://arxiv.org/pdf/1410.0846.pdf), Boettiger, 2015
- [Opinion: Reproducible research can still be wrong: Adopting a prevention approach](http://www.pnas.org/content/112/6/1645), Leek and Peng, 2015
- [Replicability vs. reproducibility -- or is it the other way around?](http://languagelog.ldc.upenn.edu/nll/?p=21956), Liberman, 2015
- [The GRIM test: A simple technique detects numerous anomalies in the reporting of results in psychology](https://peerj.com/preprints/2064v1/), Brown and Heathers, 2016
- [What does research reproducibility mean?](http://stm.sciencemag.org/content/8/341/341ps12), Goodman et al., 2016
- [Tools and techniques for computational reproducibility](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4940747/), Piccolo and Frampton, 2016
- [Transparency, Reproducibility, and the Credibility of Economics Research](https://osf.io/preprints/bitss/9a3rw/), Christensen and Miguel, 2017
- [A trust approach for sharing research reagents](http://stm.sciencemag.org/content/9/392/eaai9055.full), Edwards et al., 2017
- [Estimating the Reproducibility of Psychological Science](https://osf.io/447b3/), Nosek et al., 2017
- [Digital Open Science -- Teaching digital tools for reproducible and transparent research](https://osf.io/fbvep/), Toelch and Ostwald, 2017
- [Terminologies for reproducible research](https://arxiv.org/abs/1802.03311), Barba, 2018
- [An introduction to statistical and data sciences via R](https://ismayc.github.io/moderndiver-book/), Ismay and Kim, 2018
- [The practice of reproducible research: case studies and lessons from the data-intensive sciences](https://www.practicereproducibleresearch.org/), Kitzes et al., 2018
- [bookdown: Authoring Books and Technical Documents with R Markdown](https://bookdown.org/yihui/bookdown/), Xie, 2018
- [Our path to better science in less time using open data science tools](https://www.nature.com/articles/s41559-017-0160), Lowndes et al. 2017
- [Haves and Have nots must find a better way: The case for Open Scientific Hardware](https://osf.io/uh682/), Chagas, 2018
- [Computational Reproducibility via Containers in Social Psychology](https://psyarxiv.com/mf82t), Green and Clyburne-Sherin, 2018
- [Developer Survey Results 2019](https://insights.stackoverflow.com/survey/2019), stackoverflow, 2019

## Tools

- [Sci-Hub](https://sci-hub.tw/) - Research Paper File Sharing Platform
- [EOSC](https://eosc-portal.eu/)
- [Journal of Open Research Software](https://openresearchsoftware.metajnl.com/) and the [Journal of Open Source Software](https://joss.theoj.org/)
- [InsideDNA](https://insidedna.me/)
- [Galaxy](https://galaxyproject.org/) - Reproducible Research environments
- [Google Compute Engine](https://cloud.google.com/compute/) (GCE)
- [Amazon Web Services](https://aws.amazon.com/) - (AWS), Cloud-based software environments
- [Software Citation Tools](https://github.com/mozillascience/software-citation-tools) - Mozilla Science Lab
- [Open Science, Open Data, Open Source](https://pfern.github.io/OSODOS/gitbook/) - Fernandes and Vos, 2017
- [Choose an open source license](https://choosealicense.com/)
- Open Science Framework (COS)
- [Reproducibility Project: Cancer Biology](https://osf.io/e81xl/wiki/home/)
- [Reproducibility Project: Psychological Science](https://osf.io/ezcuj/wiki/home/)
- [Registered Reports](https://cos.io/rr/)
- Existing reproducible research workshops/practical resources:
- [Reproducible Research, Workshop](https://docs.google.com/presentation/d/1QfJVeim797fLBBAE003W6cqtahkGdJqa2GSsmm-t89s/edit?usp=sharing) - CC-BY, April Clyburne-Sherin & Courtney Soderberg
- [Initial steps towards reproducible research](http://kbroman.org/steps2rr/) - Karl Broman
- [The Open Science and Reproducible Research course](https://github.com/cbahlai/OSRR_course) - CC-BY, Christie Bahlai
- [Reproducibility Workshop](https://codeocean.com/workshop/caltech) - Best practices and easy steps to save time for yourself and other researchers, [Code Ocean](https://codeocean.com/)
- [Reproducibility in Science: A guide to enhancing reproducibility in scientific results and writing](http://ropensci.github.io/reproducibility-guide/),ROpenSci
- [Reproducible Research using Jupyter Notebooks workshop](https://reproducible-science-curriculum.github.io/workshop-RR-Jupyter/), The Carpentries
- [R markdown workshop](https://github.com/libscie/rmarkdown-workshop), (Liberate Science)
- [rrtools: Tools for Writing Reproducible Research in R](https://github.com/benmarwick/rrtools) - Ben Marwick
- [ReproZip](https://reprozip.org/), an Open source tool for full computational reproducibility
- [Software Carpentry](https://software-carpentry.org/lessons/) and [Data Carpentry](http://www.datacarpentry.org/lessons/) lessons
- [Jupyter notebooks](http://jupyter.org/) and [JupyterLab](https://blog.jupyter.org/jupyterlab-is-ready-for-users-5a6f039b8906), [R Markdown](https://www.rstudio.com/resources/webinars/getting-started-with-r-markdown/), [Stencila](https://stenci.la/)
- Virtual Machines:
- [Docker](https://www.docker.com/)
- [Vagrant](https://www.vagrantup.com/)
- [BinderHub](https://github.com/jupyterhub/binderhub)
- [nteract.io](https://nteract.io/)
- [Binder Documentation](https://mybinder.readthedocs.io/en/latest/) - for creating custom computing environments that can be shared and used by multiple remote users
- [Statcheck](http://statcheck.io/), GRIM
- [Scienceroot](https://www.scienceroot.com/) - the first blockchain-based scientific ecosystem
- [Lando](https://lando.dev/) - A local development and DevOps tool for all your projects
- [Podman](https://podman.io/) - Podman is a daemonless container engine for developing, managing, and running OCI Containers on your Linux System
- Online repositories for open hardware:
- [PLOS open source toolkit channel](https://channels.plos.org/open-source-toolkit)
- [Open Neuroscience](http://www.openeuroscience.com/)
- [Open Plant Science](http://openplant.science/)
- [Appropedia](http://www.appropedia.org/Welcome_to_Appropedia)
- [DocuBricks](http://www.docubricks.com/)
- [Hackaday.io](https://hackaday.io/submissions/prize2016_citizen/list)
- [Bio-protocol](https://bio-protocol.org/Default.aspx) - a peer reviewed protocol journal
- [BMJ Open Science](http://openscience.bmj.com/) - a new journal that aims to improve the transparency, integrity and reproducibility of biomedical research
- [Evernote](https://evernote.com/)
- [Labguru](https://www.labguru.com/)
- [sciNote](https://scinote.net/)
- [AsPredicted](https://aspredicted.org/)
- [The Sci-Gaia Open Science Platform](http://www.sci-gaia.eu/osp/)
- [Improving your statistical inferences](https://www.coursera.org/learn/statistical-inferences) - Daniel Lakens
- [Open Stats Lab](https://sites.trinity.edu/osl/data-sets-and-activities) - Kevin McIntyre
- [R for Data Science](http://r4ds.had.co.nz/)
- [R tutorial: Introduction to cleaning data with R](https://www.youtube.com/watch?v=6PVMJE3HBN0) - DataCamp
- [Nextflow](https://www.nextflow.io/) - open source tool than enables reproducible and portable computational workflows across cloud and clusters

## Organizations

- [OpenScienceMOOC](https://opensciencemooc.eu/) - Community organisation for the development of an Massive Open Online Community for Open Science
- [Eclipse Science](https://science.eclipse.org) - Open source and collaboration for computational science.
- [Mozilla Science](https://science.mozilla.org) - A community of researchers, developers, and librarians making research open and accessible.
- [Research Data Alliance](https://www.rd-alliance.org/) - (RDA) is a community-driven organization supported by the European Commission, the United States Government's National Science Foundation and National Institute of Standards and Technology, and the Australian Government’s Department of Innovation with the goal of building the social and technical infrastructure to enable open sharing of data.
- [The Software Sustainability Institute](https://www.software.ac.uk/) - Cultivate better, more sustainable, research software to enable world-class research.
- [Openscience.org](http://openscience.org) - Supports the development of open scientific software, in particular for cheminformatics.
- [NumFOCUS](https://www.numfocus.org/) - Open-code, better science. Non-profit organization that promotes sustainable high-level programming languages, open code development, and reproducible scientific research.
- [Center for Open Science](https://cos.io/) - Community for open science that also provides research and data software tools

## Courses
- [Open Science MOOC](https://eliademy.com/opensciencemooc)
- [Module 1: Open Principles](https://eliademy.com/catalog/oer/module-1-open-principles.html)
- [Module 5: Open Research Software and Open Source](https://eliademy.com/catalog/catalog/product/view/sku/02d7338a7e)

- [Open Computer Science Courses](https://www.edx.org/course/subject/computer-science)

## Events

## Books

- [Opening Science](http://book.openingscience.org.s3-website-eu-west-1.amazonaws.com/) - The Evolving Guide on How the Web is Changing Research, Collaboration and Scholarly
- [Top 10 Must-Read Books for Computer Science Majors](https://www.computersciencedegreehub.com/top-10-mustread-books-computer-science-majors/)

## Fundings

## Similar Awesome Lists

- [Open Science Software](https://github.com/INRIA/awesome-open-science-software)
- [Data Science](https://github.com/bulutyazilim/awesome-datascience)
- [Open Science](https://github.com/silky/awesome-open-science)
- [Data Visualization](https://github.com/fasouto/awesome-dataviz)
- [Public Datasets](https://github.com/awesomedata/awesome-public-datasets)
- [Free Programming Books](https://github.com/EbookFoundation/free-programming-books/blob/master/free-courses-en.md#machine-learning)

## Contribute

Contributions welcome! Read the [contribution guidelines](contributing.md) first.

## License

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