Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units

Version 1 : Received: 3 March 2020 / Approved: 5 March 2020 / Online: 5 March 2020 (02:30:06 CET)

A peer-reviewed article of this Preprint also exists.

De Smedt, K.; Koureas, D.; Wittenburg, P. FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units. Publications 2020, 8, 21. De Smedt, K.; Koureas, D.; Wittenburg, P. FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units. Publications 2020, 8, 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).

Keywords

digital object; data infrastructure; research infrastructure; data management; data science; FAIR data; open science; European Open Science Cloud; EOSC; persistent identifier

Subject

Computer Science and Mathematics, Information Systems

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