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COMPEL Body of Knowledge

COMPEL Glossary / GL-30

Data Governance Plan

A system-specific plan that defines data lineage, quality standards, access controls, retention policies, consent requirements, and bias monitoring obligations for every dataset used by an AI system.

What this means in practice

It ensures that data-layer governance is as rigorous as model-layer governance and that data issues cannot silently degrade AI system integrity.

Context in the COMPEL framework

Produced in the Model stage for each AI system in scope. Data governance gaps identified here become remediation actions that must be resolved before the Produce stage begins.

Where you see this

Data Governance Plan is most commonly referenced when teams work across the Model , Produce and Evaluate stages — especially within the Operational Readiness layer . It appears in governance artifacts, assessment instruments, and delivery playbooks wherever COMPEL is operationalized.

Related COMPEL stages

Related domains

Synonyms

data management plan , AI data governance , dataset governance specification

Related Terms Network

This diagram shows how Data Governance Plan connects to other concepts in the COMPEL body of knowledge. Each linked node is a term you can explore in turn.

Related terms for Data Governance Plan Network graph showing 3 related glossary terms connected to Data Governance Plan. Data Governanc… Policy Bas… Control Re… Evidence C…
3 related concepts connected to Data Governance Plan.
Accessible list of related terms
  • Policy Baseline Document — A structured inventory and gap analysis of all existing organizational policies relevant to AI — covering data, security, privacy, ethics, procurement, and acceptable use — that identifies which policies need to be created, updated, or retired to support the AI transformation program.
  • Control Requirements Matrix — A comprehensive mapping of every governance control required for each AI system — specifying the control type (preventive, detective, corrective), the risk or policy it addresses, the evidence required to prove effectiveness, the owner, and the testing frequency.
  • Evidence Collection Setup — The documented configuration of all evidence collection processes — defining what evidence is gathered, from which systems, on what schedule, in what format, and how it is stored and linked to governance controls — so that the Evidence Pack can be assembled continuously and automatically rather than scrambled together before audit.

See also

  • Policy Baseline Document — A structured inventory and gap analysis of all existing organizational policies relevant to AI — covering data, security, privacy, ethics, procurement, and acceptable use — that identifies which policies need to be created, updated, or retired to support the AI transformation program.
  • Control Requirements Matrix — A comprehensive mapping of every governance control required for each AI system — specifying the control type (preventive, detective, corrective), the risk or policy it addresses, the evidence required to prove effectiveness, the owner, and the testing frequency.
  • Evidence Collection Setup — The documented configuration of all evidence collection processes — defining what evidence is gathered, from which systems, on what schedule, in what format, and how it is stored and linked to governance controls — so that the Evidence Pack can be assembled continuously and automatically rather than scrambled together before audit.

Related Terms

Other glossary terms mentioned in this entry's definition and context.