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Short
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description
`Generating a semantic model is often the most time-consuming step of data FAIRification. However, we expect the modelling effort to diminish as more and more models are made available for reuse over time, especially if such models are treated as FAIR digital objects themselves. Thus, it is important to first check whether a semantic model already exists for the data and the metadata that may be reused. For cases where no semantic model is available a new one needs to be generated.` (Generic)
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In the BEAT-COVID project, the ontological models were evaluated using competency questions that are based on realistic questions posed by data model users which are proposed as means to verify the scope (e.g.,what is relevant to solve the challenges) and the relationships between concepts (e.g., check for missing or redundant relationships). A preliminary set of CQs from meetings with domain experts is available on Github: https://github.com/LUMC-BioSemantics/beat-covid/tree/master/fair-data-model/cytokine/competency-questions
Practical
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examples from the
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community
This section should show the step applied in a real project. Links to demonstrator projects.
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Ana Konrad; Hannah Neikes; Milou de Jong; Sander de Ridder
Tools and resources on this page
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Training
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