Experiences From FAIRifying Community Data and FAIR Infrastructure in Biomedical Research Domains
Abstract: FAIR data is considered good data. However, it can be difficult to quantify data FAIRness objectively, without appropriate tooling. To address this issue, FAIR metrics were developed in the early days of the FAIR era. However, to be truly informative, these metrics must be carefully interpreted in the context of a specific domain, and sometimes even of a project. Here, we share our experience with FAIR assessments and FAIRification processes in the biomedical domain. We aim to raise the awareness that “being FAIR” is not an easy goal, neither the principles are easily implemented. FAIR goes far beyond technical implementations: it requires time, expertise, communication and a shift in mindset. . https://www.tib-op.org/ojs/index.php/CoRDI/article/view/415
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Experiences From FAIRifying Community Data and FAIR Infrastructure in Biomedical Research Domains ; volume:1 ; year:2023
Proceedings of the conference on research data infrastructure ; 1 (2023)
- Urheber
- DOI
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10.52825/cordi.v1i.415
- URN
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urn:nbn:de:101:1-2023120114210490265986
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:28 MESZ
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Beteiligte
- Waltemath, Dagmar
- Inau, Esther
- Michaelis, Lea
- Satagopam, Venkata
- Balaur, Irina
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