分类： 计算机科学 >> 计算机科学的集成理论 提交时间： 2022-11-16 合作期刊: 《数据智能（英文）》
Sustkova, Hana Pergl
Hettne, Kristina Maria
Wittenburg, Peter
Jacobsen, Annika
Kuhn, Tobias
Pergl, Robert
Slifka, Jan
McQuilton, Peter
Magagna, Barbara
Sansone, Susanna-Assunta
Stocker, Markus
Imming, Melanie
Lannom, Larry
Musen, Mark
Schultes, Erik
摘要： 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.
分类： 计算机科学 >> 计算机科学的集成理论 提交时间： 2022-11-16 合作期刊: 《数据智能（英文）》
摘要： We examine the intersection of the FAIR principles (Findable, Accessible, Interoperable and Reusable), the challenges and opportunities presented by the aggregation of widely distributed and heterogeneous data about biological and geological specimens, and the use of the Digital Object Architecture (DOA) data model and components as an approach to solving those challenges that offers adherence to the FAIR principles as an integral characteristic. This approach will be prototyped in the Distributed System of Scientific Collections (DiSSCo) project, the pan-European Research Infrastructure which aims to unify over 110 natural science collections across 21 countries. We take each of the FAIR principles, discuss them as requirements in the creation of a seamless virtual collection of bio/geo specimen data, and map those requirements to Digital Object components and facilities such as persistent identification, extended data typing, and the use of an additional level of abstraction to normalize existing heterogeneous data structures. The FAIR principles inform and motivate the work and the DO Architecture provides the technical vision to create the seamless virtual collection vitally needed to address scientific questions of societal importance.
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