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Summary Profile: Level 3 “Pretty FAIR”
Level 3 - Capabilities
(WIP/ input needed)
Level 3 - Business value
Department-level data reuse and insight generation; increased effectiveness and efficiency of data resources available in the organization. Reuse of data reduces procurement costs and the need for data generation.
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Are the identifiers for data and metadata persistent?
Does the data and metadata identifier resolution support authentication and authorisation for access?
Does the metadata contain “structured” elements?
Is there a policy for persistence of metadata?
Does the metadata provide a pointer to disclose the owner or license to the data which is readable by machine?
Is a knowledge representation language being used that has ontological machine-resolvable formats?
(WIP input needed): questions that speak to other dimensions
Level 3 - FAIR data
One can find “FAIR” data in local environments such as a organization’s departments, divisions or functions.
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Initial FAIR data sets are in production and proving value. There is a company-wide supported plan to make all (relevant) data FAIR. More data sets are bornFAIR while the company's budget and competencies grow. There is evidence of local reusability and, to some extent, interoperability.
(Back to the FAIR Matrix).
Level 3 - FAIR leadership
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For example, leadership starts engaging outside the organization's boundaries to enable convergence standards.
(Back to the FAIR Matrix).
Level 3 - FAIR strategy
A refined version of the vision, strategy and plans for implementation exist.
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The data strategy accommodates federated domain-specific FAIR data, and there is an operating model, set of procedures, and defined models to harmonize, align, and connect functional domain data to expand and scale FAIR data beyond single or simple domain-specific use cases.
(Back to the FAIR Matrix).
Level 3 - FAIR roles
Key Roles are data standard expert, data curator, semantic web expert, knowledge engineer, data steward, and data strategist.
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For example, IT and business functions collaborate in creating Knowledge Graphs, scientific domain experts and data architects for data mesh
(Back to the FAIR Matrix).
Level 3 - Processes for FAIR
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A "FAIR implementation plan" to enact the strategy is in place.
(Back to the FAIR Matrix).
Level 3 - FAIR knowledge
FAIR data is part of the training curriculum, with some materials and experts available company-wide.
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A community of knowledgeable FAIR practitioners have met and have started sharing experiences in making data FAIR, at least at the department level.
(Back to the FAIR Matrix).
Level 3 - FAIR tools and infrastructures
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It becomes easier to make data FAIR company-wide, using the well-supported off-the-shelf tools than in the previous maturity level.
(Back to the FAIR Matrix).
Findability:
Tool(s) or infrastructure component which contributes, enhances or enriches Findability:
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