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FAIR data and services in biodiversity science and geoscience

Lannom, Larry, Koureas, Dimitris and Hardisty, Alex 2019. FAIR data and services in biodiversity science and geoscience. Data Intelligence 2 , pp. 122-130. 10.1162/dint_a_00034

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Abstract

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.

Item Type: Article
Date Type: Published Online
Status: In Press
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QH Natural history
Uncontrolled Keywords: Digital Object Architecture (DOA); FAIR; DiSSCo; Biodiversity; Geoscience
Publisher: MIT Press
ISSN: 2641-435X
Funders: Horizon 2020 Framework Programme of the European Union, H2020-INFRADEV-2016-2017 Grant Agreement No. 777483
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Date of First Compliant Deposit: 7 November 2019
Date of Acceptance: 21 June 2019
Last Modified: 11 Nov 2019 13:45
URI: http://orca-mwe.cf.ac.uk/id/eprint/126631

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