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

Preprints.org

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

1. Koenraad De Smedt corresponding

   University of Bergen

   Affiliation as printed

   University of Bergen ;

   University of Bergen;

2. Dimitrios Koureas corresponding Aachen Naturalis Biodiversity Center

   Naturalis Biodiversity Center

   Affiliation as printed

   Naturalis Biodiversity Center ;

   Naturalis Biodiversity Center;

3. Peter Wittenburg corresponding

   Max Planck Computing and Data Facility

   Affiliation as printed

   Max Planck Computing and Data Facility;