Interpreting FAIR
The interpretation of the FAIR Guiding Principles by the GO FAIR community, and adopted by the GO FAIR Foundation as a reference for guiding FAIR implementation.
Interpretations
The FAIR Guiding Principles [1] provide guidance when improving Findability, Accessibility, Interoperability and Reusability of digital resources. But they do not dictate specific technological implementations. The GO FAIR Foundation believes that what ever FAIR implementation choices are made, they should always ensure, as much as possible, interoperability, machine-actionability, global participation and convergence towards accessible, robust, widespread and consistent FAIR implementations. Towards this end, the GO FAIR Foundation has consolidated from the community of FAIR experts, explicit interpretations of the FAIR Principles and implementation considerations. The aim is to provide a reference for continuing coherent dialogue on "what FAIR is" and a target, with minimal guarantees on machine-actionability, to which the community can confidently build towards. Following closely Jacobsen et al [2], the GO FAIR Foundation's interpretations are provided here as referenceable webpages:
Criteria
Based on the interpretations of the FAIR Guiding Principles, and other implementation considerations, the GO FAIR Foundation has defined a set of criteria as targets when making data FAIR. The GO FAIR Foundation criteria are described on the following pages:
References
[1] The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18 Mark Wilkinson, Michel Dumontier, IJsbrand Jan Aalbersberg, Gabrielle Appleton, Myles Axton, Arie Baak, Niklas Blomberg, Jan-Willem Boiten, Luiz Bonino da Silva Santos, Philip E. Bourne, Jildau Bouwman, Anthony J. Brookes, Tim Clark, Mercè Crosas, Ingrid Dillo, Olivier Dumon, Scott Edmunds, Chris T. Evelo, Richard Finkers, Alejandra Gonzalez-Beltran, Alasdair J.G. Gray, Paul Groth, Carole Goble, Jeffrey S. Grethe, Jaap Heringa, Peter A.C ’t Hoen, Rob Hooft, Tobias Kuhn, Ruben Kok, Joost Kok, Scott J. Lusher, Maryann E. Martone, Albert Mons, Abel L. Packer, Bengt Persson, Philippe Rocca-Serra, Marco Roos, Rene van Schaik, Susanna-Assunta Sansone, Erik Schultes, Thierry Sengstag, Ted Slater, George Strawn, Morris A. Swertz, Mark Thompson, Johan van der Lei, Erik van Mulligen, Jan Velterop, Andra Waagmeester, Peter Wittenburg, Katherine Wolstencroft, Jun Zhao & Barend Mons
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[2] FAIR Principles: Interpretations and Implementation Considerations. Data Intelligence 2020; 2 (1-2): 10–29.doi: https://doi.org/10.1162/dint_r_00024 Annika Jacobsen, Ricardo de Miranda Azevedo, Nick Juty, Dominique Batista, Simon Coles, Ronald Cornet, Mélanie Courtot, Mercè Crosas, Michel Dumontier, Chris T. Evelo, Carole Goble, Giancarlo Guizzardi, Karsten Kryger Hansen, Ali Hasnain, Kristina Hettne, Jaap Heringa, Rob W.W. Hooft, Melanie Imming, Keith G. Jeffery, Rajaram Kaliyaperumal, Martijn G. Kersloot, Christine R. Kirkpatrick, Tobias Kuhn, Ignasi Labastida, Barbara Magagna, Peter McQuilton, Natalie Meyers, Annalisa Montesanti, Mirjam van Reisen, Philippe Rocca-Serra, Robert Pergl, Susanna-Assunta Sansone, Luiz Olavo Bonino da Silva Santos, Juliane Schneider, George Strawn, Mark Thompson, Andra Waagmeester, Tobias Weigel, Mark D. Wilkinson, Egon L. Willighagen, Peter Wittenburg, Marco Roos, Barend Mons, Erik Schultes
