Access conditions

metric

ML-A1-01M: Metadata contains access level and access conditions of the ML model. Test: 1) Information about access restrictions or rights can be identified in the metadata. 2) ML model access information is indicated by (not machine readable) standard terms. 3) ML model access information is machine readable. *Note: Use automatic tool to assess this metric and enter the result here.*

Principle: A

Rationale: This metric determines if the metadata includes the level of access to the ML model data, such as public, embargoed, restricted, or metadata-only access, and its access conditions.

FAIR Metrics: A1

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Associated Rubrics (1)

FAIR for Machine Learning Models

This rubric consists of assessment metrics that evaluate the FAIR maturity of ML models. The metrics...

FAIR machine learning model FAIR assessment NFDI4DataScience