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| 1 | FAIR Principles:Interpretations and Implementation Considerations显示文摘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. | Annika Jacobsen Ricardo de Miranda Azevedo 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 | 2020 | Data Intelligence2020，2，1： | 26 |
| 2 | 国内外科学数据管理FAIR原则研究进展及应用综述显示文摘[目的/意义]科学数据管理FAIR原则从2016年正式发布到目前为止引起了国内外学者的广泛关注和重视,围绕FAIR原则开展了诸多探索和研究,有力地推动了FAIR原则的实施和推广,本文旨在对相关学术成果进行系统梳理和深入总结。[方法/过程]通过文献调研和内容分析,从FAIR原则组织保障、FAIR的4个基本原则、FAIR原则的实践探索、FAIR原则的学科应用及FAIR原则的区域应用5个角度梳理国内外对FAIR原则的研究进展和实践,总结研究现状和已有成果。[结果/结论]国外对于FAIR原则的研究集中在理论、实施策略、评估方法等方面,并已在医学等学科领域展开了深入探索,相比之下,国内的研究尚在起步状态,亟需国家的政策支持和相关组织的跟进。 | 陈书贤 刘桂锋 刘琼 | 2022 | 农业图书情报学报2022，34，8： | 6 |
| 3 | Helping the Consumers and Producers of Standards,Repositories and Policies to Enable FAIR Data显示文摘Thousands of community-developed(meta)data guidelines,models,ontologies,schemas and formats have been created and implemented by several thousand data repositories and knowledge-bases,across all disciplines.These resources are necessary to meet government,funder and publisher expectations of greater transparency and access to and preservation of data related to research publications.This obligates researchers to ensure their data is FAIR,share their data using the appropriate standards,store their data in sustainable and community-adopted repositories,and to conform to funder and publisher data policies.FAIR data sharing also plays a key role in enabling researchers to evaluate,re-analyse and reproduce each other’s work.We can map the landscape of relationships between community-adopted standards and repositories,and the journal publisher and funder data policies that recommend their use.In this paper,we show how the work of the GO-FAIR FAIR Standards,Repositories and Policies(StRePo)Implementation Network serves as a central integration and cross-fertilisation point for the reuse of FAIR standards,repositories and data policies in general.Pivotal to this effort,the FAIRsharing,an endorsed flagship resource of the Research Data Alliance that maps the landscape of relationships between community-adopted standards and repositories,and the journal publisher and funder data policies that recommend their use.Lastly,we highlight a number of activities around FAIR tools,services and educational efforts to raise awareness and encourage participation. | Peter McQuilton Dominique Batista Oya Beyan Ramon Granell Simon Coles Massimiliano Izzo Allyson L.Lister Robert Pergl Philippe Rocca-Serra Ben Schaap Hugh Shanahan Milo Thurston Susanna-Assunta Sansone | 2020 | Data Intelligence2020，2，1： | 5 |
| 4 | The FAIR Principles:First Generation Implementation Choices and Challenges显示文摘“FAIR enough”?...A question asked on a daily basis in the rapidly evolving field of open science and the underpinning data stewardship profession.After the publication of the FAIR principles in 2016,they have sparked theoretical debates,but some communities have already begun to implement FAIR-guided data and services.No-one really argues against the idea that data,as well as the accompanying workflows and services should be findable,accessible under well-defined conditions,interoperable without data munging,and thus optimally reusable.Being FAIR is not a goal in itself;FAIR Data and Services are needed to enable data intensive research and innovation and(thus)have to be“AI-ready”(=future proof for machines to optimally assist us).However,the fact that science and innovation becomes increasingly“machine-assisted”and hence the central role of machines,is still overlooked in some cases when people claim to implement FAIR. | Barend Mons Erik Schultes Fenghong Liu Annika Jacobsen | 2020 | Data Intelligence2020，2，1： | 2 |
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