The COMPEL Glossary Graph visualizes relationships between framework terminology, showing how concepts interconnect across domains, stages, and pillars. Term nodes cluster by pillar affiliation while cross-references reveal semantic dependencies — for example, how risk appetite connects to control effectiveness, model governance, and assurance requirements. This network representation helps practitioners navigate the framework vocabulary and understand that COMPEL terminology forms a coherent conceptual system rather than isolated definitions.
COMPEL Glossary / fitness-for-purpose
Fitness for purpose
The determination that a specific dataset is appropriate for a specific AI use case given the task, risk tier, and intended deployment context.
What this means in practice
A governance judgment, not a technical metric — two datasets with identical quality scores can differ in fitness because the use cases impose different representation, recency, or legal-basis requirements.
Synonyms
fit-for-purpose , dataset fitness
See also
- Data quality dimension — A measurable attribute of data integrity — accuracy, completeness, consistency, timeliness, validity, uniqueness, representativeness — used as a scoring axis in a data-readiness rubric.
- Third-party data readiness — The extension of data-readiness assessment to data supplied by vendors, partners, open-source corpora, or scraped sources — covering provenance, legal basis, contractual terms, known bias profile, and re-use constraints.