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 / data-quality-dimension
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.
What this means in practice
Technology-neutral: each dimension has specific test methods (rule-based, statistical, or semantic) whose choice depends on the data and the workload.
Synonyms
data quality attribute , DQ dimension
See also
- 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.
- Bias-relevant variable — A feature whose inclusion, exclusion, or proxy-behavior affects fairness across protected groups — a direct sensitive attribute (race, gender) or an indirect proxy (postal code, device type).
- Readiness scorecard — A structured, dimension-by-dimension artifact summarizing evidence, scores, remediation priorities, and owner assignments for a use-case-scoped data-readiness assessment.