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 / ai-data-lifecycle
AI data lifecycle
The nine-stage progression from sourcing through retirement used as the reference frame for data readiness: acquisition, preparation, labeling, governance, training use, validation, deployment use, monitoring, retention and retirement.
What this means in practice
Derived from ISO/IEC 8183:2023; serves as the scaffold that data-readiness assessments map evidence against.
Synonyms
AI-data lifecycle , data lifecycle for AI
See also
- Provenance — The record of origin and custody for a data asset — who collected it, from whom, under what legal basis, and through which hands it passed — required for auditability of high-risk AI under EU AI Act Article 10.
- Readiness scorecard — A structured, dimension-by-dimension artifact summarizing evidence, scores, remediation priorities, and owner assignments for a use-case-scoped data-readiness assessment.