title: “Evidence Schema” description: “Machine-readable representation of governance evidence.”
Evidence Schema
The Evidence Schema provides a structured representation of evidence supporting AI governance activities, assessments, controls, decisions, and assurance.Purpose
Evidence provides the basis for demonstrating that governance activities have been performed and that relevant controls, decisions, assessments, and other governance claims are supported. The schema helps establish consistent representation and traceability of evidence records.Evidence relationships
Evidence records can be associated with: * AI systems * risks * controls * assessments * approvals * monitoring activities * incidents * changes * assurance activities * governance decisions * improvement activities This enables evidence to participate in broader governance traceability. A typical relationship can be represented as: requirement / risk → control → evidence → assessment → assurance Where machine-readable evaluation applies, evidence may also provide input to defined evaluation conditions.Evidence quality
The existence of an evidence record does not automatically establish that the evidence is sufficient. Organizations should consider factors such as: * relevance * completeness * accuracy * authenticity * currency * provenance * scope * applicability * retention * accessibility * relationship to the control or governance claim being supported Evidence should be evaluated in context.Evidence and assessment
Evidence can support assessment conclusions by demonstrating implementation, operation, review, or other relevant governance activity. This creates traceability between: control → evidence → assessment finding → remediation → verificationEvidence and assurance
Assurance activities may review evidence to determine whether governance processes and controls are appropriately designed, implemented, and operating as intended. Evidence therefore serves both operational governance and independent or structured assurance activities.Machine-readable evaluation
The AIGO repository includes a machine-readable evaluation layer that can evaluate defined governance rules against applicable data. Evidence may form part of the information used to determine whether a defined governance condition can be evaluated. Automated evaluation should not be interpreted as a universal substitute for human evidence review or governance judgment.Validation
Evidence structures participate in the repository’s broader validation and traceability model. Validation can identify structural or reference problems in machine-readable governance content. A repository validation result demonstrates the status of the validated repository content within the relevant validation scope. It does not establish legal compliance, certification, accreditation, or regulatory conformity.Canonical source
schemas/10-evidence/10-AIGO-Evidence-Schema-v0.1.json
Documentation:
schemas/10-evidence/10-AIGO-Evidence-Schema-Documentation-v0.1.md