Linked.Archi

Linked.Archi AI Ethics & Governance Extension

Viewpoint Definitions

https://meta.linked.archi/ai-governance/onto#

v0.1.0 draft aigov: Kalin Maldzhanski Linked.Archi Modified: 2026-05-03 License

Extension ontology for AI ethics and governance. Provides element types, properties, and reference data for managing AI system risk classification, conformity assessment, bias assessment, explainability documentation, human oversight plans, and governance policies. Builds on the ML-Enabled Systems extension (mlsys:) by adding the governance layer that connects ML components to regulatory frameworks (EU AI Act), ethical principles (OECD AI Principles), and organizational AI governance policies. Motivated by Gartner 2025 Leadership Vision identifying AI ethics and governance as a critical gap in EA teams, and by the EU AI Act (Regulation 2024/1689) requiring formal risk classification and conformity assessment for high-risk AI systems.

Contents

AI Regulatory Compliance

AI Governance Overview

High-level overview of AI governance across the organization — which AI systems exist, their risk classifications, conformity assessment status, and governing policies. The entry point for AI governance stakeholders.
Purpose: Governing, Informing
Concerns: AI Regulatory Compliance, AI Accountability
View type: Catalog, Matrix
Included concepts:
AISystem RiskClassification ConformityAssessment AIGovernancePolicy

AI Risk Assessment

Detailed view of AI system risk — risk classification rationale, bias assessments, explainability reports, and human oversight plans. Used for conformity assessment preparation and regulatory reporting.
Purpose: Governing, Deciding
Concerns: AI Regulatory Compliance, Human Oversight of AI
View type: Matrix, Catalog
Included concepts:
AISystem RiskClassification BiasAssessment ExplainabilityReport HumanOversightPlan

AI Accountability

AI Incident Tracking

View of AI incidents — bias events, safety failures, adversarial attacks, and their resolution. Used for post-incident analysis and continuous improvement of AI governance.
Purpose: Governing
Concerns: AI Accountability, AI Regulatory Compliance
View type: Catalog
Included concepts:
AISystem AIIncident

AI Transparency

AI Transparency & Disclosure

View of transparency obligations — which AI systems require disclosure to users, what transparency records exist, and what information is provided to affected persons.
Purpose: Governing
Concerns: AI Transparency
View type: Catalog
Included concepts:
AISystem TransparencyRecord
Source: linked-archi-meta • Linked.Archi