FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units
Publications, vol. 8, pp. 21
Abstract
Data science is facing the following major challenges: (1) developing scalable cross-disciplinary capabilities, (2) dealing with the increasing data volumes and their inherent complexity, (3) building tools that help to build trust, (4) creating mechanisms to efficiently operate in the domain of scientific assertions, (5) turning data into actionable knowledge units and (6) promoting data interoperability. As a way to overcome these challenges, we further develop the proposals by early Internet pioneers for Digital Objects as encapsulations of data and metadata made accessible by persistent identifiers. In the past decade, this concept was revisited by various groups within the Research Data Alliance and put in the context of the FAIR Guiding Principles for findable, accessible, interoperable and reusable data. The basic components of a FAIR Digital Object (FDO) as a self-contained, typed, machine-actionable data package are explained. A survey of use cases has indicated the growing interest of research communities in FDO solutions. We conclude that the FDO concept has the potential to act as the interoperable federative core of a hyperinfrastructure initiative such as the European Open Science Cloud (EOSC).
Authors 3
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Koenraad De Smedt corresponding
Affiliation as printed
Department of Linguistic, Literary and Aesthetic Studies, University of Bergen, P.O Box 7800, 5020 Bergen, Norway
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Affiliation as printed
International Biodiversity Infrastructures, Naturalis Biodiversity Center, P.O. Box 9517, 2300 RA Leiden, The Netherlands
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Max Planck Computing and Data Facility
Affiliation as printed
Max Planck Computing and Data Facility, Max-Planck-Gesellschaft, Gießenbachstraße 2, 85748 Garching, Germany
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