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FAIR Convergence Matrix:Optimizing the Reuse of Existing FAIR-Related Resources

Data Intelligence 2020年第1期2卷 158-170,313页

作者： hana pergl sustkova Kristina Maria Hettne 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 GO FAIR International Support and Coordination Office LeidenThe Netherlands Centre for Digital Scholarship Leiden University LibrariesLeidenThe Netherlands Max Planck Computing and Data Facility Gießenbachstraße 285748 GarchingGermany Leiden University Medical Center Leiden2333 ZAThe Netherlands Department of Computer Science Vrije Universiteit AmsterdamDe Boelelaan 11051081 HV AmsterdamThe Netherlands Czech Technical University in Prague Faculty of Information Technology(FIT CTU)16000 Prague 6Czech Republic Oxford e-Research Centre Department of Engineering SciencesUniversity of OxfordOxford OX13PJUK Environment Agency Austria A-1090 ViennaAustria TIB Leibniz Information Centre for Science and Technology HannoverGermany SURF Utrecht 3511 EPThe Netherlands Corporation for National Research Initiatives(CNRI) RestonVirginia 20191USA Stanford Center for Biomedical Informatics Research StanfordCA 94305USA

The FAIR principles articulate the behaviors expected from digital artifacts that are Findable,Accessible,Interoperable and Reusable by machines and by *** by now widely accepted,the FAIR Principles by design do not explicitly consider actual implementation choices enabling FAIR *** 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 *** an effort to accelerate broad community convergence on FAIR implementation options,the GO FAIR community has launched the development of the FAIR Convergence *** Matrix is a platform that compiles for any community of practice,an inventory of their self-declared FAIR implementation choices and *** 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.

关键词： FAIR Implementation Choices and Challenges Convergence FAIR Communities

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