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FAIR Principles:Interpretations and Implementation Considerations 被引量:27
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作者 Annika Jacobsen Ricardo de Miranda Azevedo +41 位作者 Nick Juty Dominique Batista Simon Coles Ronald Cornet Melanie Courtot Merce 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 GKersloot Christine R.Kirkpatrick Tobias Kuhn Ignasi Labastida barbara magagna PeterMcQuilton 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 《Data Intelligence》 2020年第1期10-29,293-302,322,共31页
The FAIR principles have been widely cited,endorsed and adopted by a broad range of stakeholders since their publication in 2016.By intention,the 15 FAIR guiding principles do not dictate specific technological implem... The FAIR principles have been widely cited,endorsed and adopted by a broad range of stakeholders since their publication in 2016.By intention,the 15 FAIR guiding principles do not dictate specific technological implementations,but provide guidance for improving Findability,Accessibility,Interoperability and Reusability of digital resources.This has likely contributed to the broad adoption of the FAIR principles,because individual stakeholder communities can implement their own FAIR solutions.However,it has also resulted in inconsistent interpretations that carry the risk of leading to incompatible implementations.Thus,while the FAIR principles are formulated on a high level and may be interpreted and implemented in different ways,for true interoperability we need to support convergence in implementation choices that are widely accessible and(re)-usable.We introduce the concept of FAIR implementation considerations to assist accelerated global participation and convergence towards accessible,robust,widespread and consistent FAIR implementations.Any self-identified stakeholder community may either choose to reuse solutions from existing implementations,or when they spot a gap,accept the challenge to create the needed solution,which,ideally,can be used again by other communities in the future.Here,we provide interpretations and implementation considerations(choices and challenges)for each FAIR principle. 展开更多
关键词 FAIR guiding principles FAIR implementation FAIR convergence FAIR communities choices and challenges
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FAIR Convergence Matrix:Optimizing the Reuse of Existing FAIR-Related Resources 被引量:4
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作者 Hana Pergl Sustkova Kristina Maria Hettne +12 位作者 Peter Wittenburg Annika Jacobsen Tobias Kuhn Robert Pergl Jan Slifka Peter McQuilton barbara magagna Susanna-Assunta Sansone Markus Stocker Melanie Imming Larry Lannom Mark Musen Erik Schultes 《Data Intelligence》 2020年第1期158-170,313,共14页
The FAIR principles articulate the behaviors expected from digital artifacts that are Findable,Accessible,Interoperable and Reusable by machines and by people.Although by now widely accepted,the FAIR Principles by des... The FAIR principles articulate the behaviors expected from digital artifacts that are Findable,Accessible,Interoperable and Reusable by machines and by people.Although by now widely accepted,the FAIR Principles by design do not explicitly consider actual implementation choices enabling FAIR behaviors.As different communities have their own,often well-established implementation preferences and priorities for data reuse,coordinating a broadly accepted,widely used FAIR implementation approach remains a global challenge.In an effort to accelerate broad community convergence on FAIR implementation options,the GO FAIR community has launched the development of the FAIR Convergence Matrix.The Matrix is a platform that compiles for any community of practice,an inventory of their self-declared FAIR implementation choices and challenges.The Convergence Matrix is itself a FAIR resource,openly available,and encourages voluntary participation by any self-identified community of practice(not only the GO FAIR Implementation Networks).Based on patterns of use and reuse of existing resources,the Convergence Matrix supports the transparent derivation of strategies that optimally coordinate convergence on standards and technologies in the emerging Internet of FAIR Data and Services. 展开更多
关键词 FAIR Implementation Choices and Challenges CONVERGENCE FAIR Communities
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