ML model content specification

metric

ML-R1-01M: Metadata specifies the content of the ML model. Test: 1) Minimal information about available data content is given in metadata (resource type, links). 2) Verifiable data descriptors (file info (size, type), measured variables or observation types) are specified in metadata. 3) Data content matches measured variables or file type and size specified in metadata. *Note: Use automatic tool to assess this metric and enter the result here.*

Principle: R

Rationale: This metric evaluates if the content of the dataset is specified in the metadata, and it should be an accurate reflection of the actual data deposited.

FAIR Metrics: R1

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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