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Donny Winston

Donny Winston
Made as simple as possible, but not simpler.
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What conveys that data has been validated or is yet to be validated? How do you identify the nature and process of validation for a given digital object? Who is involved? What auxiiary resources are involved? Is the process: Do-it-yourself, with (implicit or explicit) references to validation assets? Do-it-with-you, with references to validation services? Do-it-for-you, with references to validation results and/or signoffs?

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At a base level, an identifier is simple to trace – it is the sequence (modulo concurrency) of assertions of which it is a part. In fact, this can be the basis for tracing the representation of a “thing” as the flock of relationships between identifiers, i.e. metadata, that waxes and wanes in association with “the” identifier of the thing.

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Good identifiers are opaque, so translation is by association – owl:sameAs, skos:exactMatch, or some other relationship. Translation doesn’t follow from reading a sign, but from retrieving a sense. If metadata is relationships between identifiers, 1 then metadata is the medium of conceptual convergence.

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Yesterday, I proposed that a strategy for implementing the FAIR principles for research data management can focus on ensuring five FAIR-enabling services , which in turn will prompt tactical choices of FAIR-enabling resources that may satisfactorily address each question and thereby produce a comprehensive implementation profile.

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Here are some identifier services listed as such by FIP Wizard, a free-to-signup online tool to guide a user in creating and publishing a machine-actionable FAIR Implementation Profile (FIP): Old IGSN International Generic Sample Number before integration with DataCite SDN CDI PID | SeaDataNet CDI PID SeaDataNet Common Data Persistent Identifier U.S. Department of Energy Office of Scientific and Technical Information (OSTI) Data ID Service