That there is provenance information associated with the data, covering at least two primary types of provenance information


- Who/what/When produced the data (i.e. for citation) - Why/How was the data produced (i.e. to understand context and relevance of the data) Reusability is not only a technical issue; data can be discovered, retrieved, and even be machine-readable, but still not be reusable in any rational way. Reusability goes beyond “can I reuse this data?” to other important questions such as “may I reuse this data?”, “should I reuse this data”, and “who should I credit if I decide to use it?” Several IRIs - at least one of these points to one of the vocabularies used to describe citational provenance (e.g. dublin core). At least one points to one of the vocabularies (likely domain-specific) that is used to describe contextual provenance (e.g. EDAM) IRI 1 should resolve to a recognized citation provenance standard such as Dublin Core. IRI 2 should resolve to some vocabulary that itself passes basic tests of FAIRness

FAIR Metrics: R1.2


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Associated Rubrics (1)

Repositive Discover datasets rubric

Rubric for the Repositive Discover datasets This rubric is cons...

DCPPC genomics data