The FAIR Guiding Principles for scientific data management and stewardship

Abstract

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.

DOI: 10.1038/sdata.2016.18

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@inproceedings{Wilkinson2016TheFG, title={The FAIR Guiding Principles for scientific data management and stewardship}, author={Mark D Wilkinson and Michel Dumontier and I Jsbrand Jan Aalbersberg and Gabrielle Appleton and Myles Axton and Arie Baak and Niklas Blomberg and Jan-Willem Boiten and Luiz Bonino da Silva Santos and Philip E Bourne and Jildau Bouwman and Anthony J Brookes and Tim Clark and Merc{\`e} Crosas and Ingrid Dillo and Olivier Dumon and Scott Edmunds and Chris T Evelo and Richard Finkers and Alejandra Gonzalez-Beltran and Alasdair J G Gray and Paul Groth and Carole Goble and Jeffrey S Grethe and Jaap Heringa and Peter A C 't Hoen and Rob Hooft and Tobias Kuhn and Ruben Kok and Joost Kok and Scott J Lusher and Maryann E Martone and Albert Mons and Abel L Packer and Bengt Persson and Philippe Rocca-Serra and Marco Roos and Rene van Schaik and Susanna-Assunta Sansone and Erik Schultes and Thierry Sengstag and Ted Slater and George Strawn and Morris A Swertz and Mark Thompson and Johan van der Lei and Erik van Mulligen and Jan Velterop and Andra Waagmeester and Peter Wittenburg and Katherine Wolstencroft and Jun Zhao and Barend Mons}, booktitle={Scientific data}, year={2016} }