On Data Annotation – From Metadata to Meaning – and how OSCARS and the Science Clusters contribute to it
Year: 2025
Type: article
Abstract: Data annotation is one of the key enablers of Open Science, making datasets intelligible, discoverable, and reusable for both humans and machines. By enriching data with structured metadata and semantic links, annotation allows better interoperability and adherence to FAIR principles. This article provides a background on FAIR data annotation practices and showcases how the Science Clusters (ENVRI, ESCAPE, LS-RI, PaNOSC, SSHOC) are advancing tailored annotation practices, based on community validated standards and tools across disciplines. OSCARS, also through its funded projects, complements these efforts by fostering cross-cluster harmonisation, offering transversal services, and promoting sustainable adoption of well recognized annotation workflows.
Authors: Carboni, Nicoletta, DAVID, Romain, de Jong, Franciska, Ewbank, Jonathan, Fiser, Darja, Grüning, Björn, Thomas, Justine, Schmidt-Tremmel, Friederike
Institutions: Central European Research Infrastructure Consortium, European Research Infrastructure on Highly Pathogenic Agents, Utrecht University, Inserm, University of Ljubljana, University of Freiburg, Centre National de la Recherche Scientifique, Laboratoire d’Annecy de Physique des Particules, Trust IT Services
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: European Commission
OpenAlex ID: W7085121906
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