The FAIR Guiding Principles for scientific data management and stewardship
Author
Wilkinson, Mark D.
Dumontier, Michel
Aalbersberg, IJsbrand Jan
Appleton, Gabrielle
Axton, Myles
Baak, Arie
Blomberg, Niklas
Boiten, Jan-Willem
da Silva Santos, Luiz Bonino
Bourne, Philip E.
Bouwman, Jildau
Brookes, Anthony J.
Clark, Tim
Crosas, Mercè
Dillo, Ingrid
Dumon, Olivier
Edmunds, Scott
Evelo, Chris T.
Finkers, Richard
Gonzalez-Beltran, Alejandra
Gray, Alasdair J.G.
Groth, Paul
Goble, Carole
Grethe, Jeffrey S.
Heringa, Jaap
’t Hoen, Peter A.C
Hooft, Rob
Kuhn, Tobias
Kok, Ruben
Kok, Joost
Lusher, Scott J.
Martone, Maryann E.
Mons, Albert
Packer, Abel L.
Persson, Bengt
Rocca-Serra, Philippe
Roos, Marco
van Schaik, Rene
Sansone, Susanna-Assunta
Schultes, Erik
Sengstag, Thierry
Slater, Ted
Strawn, George
Swertz, Morris A.
Thompson, Mark
van der Lei, Johan
van Mulligen, Erik
Velterop, Jan
Waagmeester, Andra
Wittenburg, Peter
Wolstencroft, Katherine
Zhao, Jun
Mons, Barend
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Show full item recordAbstract
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.