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Level 2 - Questions to ask

  • How is data being cataloged within the organization, and what role does metadata play in this process?

  • Do metadata documents contain their own identifiers and other ones  for the data? 

  • Are the protocols for resolution of data and metadata identifiers universally implementable?  Are they open? Are they  free?

  • Is Are there a license document documents for both the data and its associated metadata which is are retrievable by humans?(WIP input needed): questions that speak to other dimensions?

  • What role do champions play in the early stages of FAIR data implementation, and how are teams forming under their leadership?

  • Which efforts are being made to align FAIR implementation with existing data strategies and models within the organization?

  • What efforts are being made to designate and recognize FAIR-related roles within the company?

  • How is the organization conducting needs assessments to structure formal training frameworks for FAIR data practices?

  • In what ways are efforts being made to standardize FAIR data processes and coordinate proof-of-concept projects?

  • How are designated roles shaping the understanding and formalization of FAIR knowledge within the company?

  • What internal and external resources are being utilized to develop FAIR training tailored to the organization's needs?

  • What tools have been introduced to capture and publish metadata within the organization?

  • How is the organization seeking or creating reference tools, such as controlled vocabularies, ontologies, and data standards, to support FAIR data principles implementation?

Level 2 - FAIR data

Data, conformed to a local model, is cataloged (i.e. a metadata record of existence is created), and data resides in a data lake.

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Requires average level technical and subject matter knowledge to use. ( cf. the role : of data scientist).

(Back to the FAIR Matrix).

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