Assessing FAIRness of Citizen Science Data in the Context of the Green Deal Data Space

Abstract

As part of the European Data Strategy, the European Commission is working on common European data spaces, including a Green Deal Data Space (GDDS) that covers issues such as climate change, circular economy, pollution, biodiversity, and deforestation. The successful development of the EU GDDS will depend on the availability of FAIR (findable, accessible, interoperable, and reusable) data sources, including FAIR citizen science data. While the importance of FAIR principles is increasingly acknowledged within the field of citizen science, sources of FAIR data outside the biodiversity domain are generally scarce. This is contributed by the lack of end-to-end technical solutions, readily available semantic resources to support data interoperability, and centralised data repositories suited for citizen science data. To investigate the current state of play with citizen science data FAIR compliance, we conducted a review to elicit platforms, tools and standards either used by or indicated as suitable for facilitating stages of the citizen science project lifecycle. We report on the results of our review and discuss gaps that still exist to achieve citizen science data FAIRness. We also examine three data aggregation platforms identified in our review which closely align with FAIR, namely: the Global Biodiversity Information Facility, OpenStreetMap, and Sensor.Community.

Publication DOI: https://doi.org/10.1080/17538947.2024.2344587
Divisions: College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies > Applied AI & Robotics
College of Engineering & Physical Sciences > Aston Centre for Artifical Intelligence Research and Application
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies
College of Engineering & Physical Sciences
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Aston University (General)
Funding Information: This work has been co-funded by the European Union, Switzerland and the United Kingdom under the AD4GD project.
Additional Information: Copyright © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
Uncontrolled Keywords: citizen science,FAIR guiding principles,open data,Green Deal Data Space
Publication ISSN: 1753-8955
Data Access Statement: Data sharing is not applicable to this article, as no new data were created or analyzed in this study.
Last Modified: 27 Nov 2024 08:19
Date Deposited: 13 May 2024 12:43
Full Text Link:
Related URLs: https://www.tan ... 47.2024.2344587 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Review article
Published Date: 2024
Published Online Date: 2024-05-09
Accepted Date: 2024-04-14
Authors: Lush, Victoria (ORCID Profile 0000-0003-3248-9608)
Bastin, Lucy (ORCID Profile 0000-0003-1321-0800)
Otsu, Kaori
Masó, Joan

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