Experiences From FAIRifying Community Data and FAIR Infrastructure in Biomedical Research Domains
Dagmar Waltemath,
Esther Inau,
Lea Michaelis
et al.
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 F… Show more
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