Linked.Archi AI Ethics & Governance Extension
type: Ontology
imports: core#
imports: onto#
license: http://creativecommons.org/licenses/by/4.0/
preferred namespace prefix: aigov
creator: Kalin Maldzhanski
description: 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.
abstract: Ontology for AI ethics and governance within the Linked.Archi ecosystem.
created: 2026-05-03
modified: 2026-05-03
publisher: Linked.Archi
publisher: linked.archi
status: draft
version IRI: 0.1.0#
version info: 0.1.0
citation: Linked.Archi AI Ethics & Governance Extension

AI Risk Level
type: Class
definition: Classification of AI system risk according to the EU AI Act (Regulation 2024/1689). Risk levels determine the regulatory obligations that apply to an AI system.

AI Principle
type: Class
definition: A responsible AI principle — an ethical guideline that AI systems should adhere to. Sourced from OECD AI Principles, EU Ethics Guidelines for Trustworthy AI, and organizational AI policies.

Human Oversight Mode
type: Class
definition: The mode of human oversight applied to an AI system. Determines the degree of human involvement in AI decision-making.

Assessment Status
type: Class
definition: Status of a conformity or bias assessment.

AI System
type: Class
subclass of: Element
definition: An AI system subject to governance — the governance wrapper around one or more ML models and their serving infrastructure. An AISystem is the unit of governance: it is what gets risk-classified, assessed for conformity, and monitored for compliance. An AISystem links to the underlying ML components via wrapsMLModel and wrapsServingInfra, connecting the governance layer to the technical layer defined in the ML-Enabled Systems extension. Aligned with the EU AI Act definition: "a machine-based system that is designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments."

Risk Classification
type: Class
definition: A risk level assignment for an AI system. Records the assessed risk level, the rationale for the classification, the assessor, and the date. Risk classification determines which regulatory obligations apply under the EU AI Act.

Conformity Assessment
type: Class
definition: A formal assessment of an AI system against regulatory requirements or organizational AI governance policies. Records which principles were assessed, the assessment result (pass/fail/conditional), findings, and remediation actions.

Bias Assessment
type: Class
definition: An assessment of bias in an AI system — covering training data bias, model output bias, and deployment context bias. Records the bias metrics used, the protected attributes examined, the findings, and any mitigation measures applied or recommended.

Explainability Report
type: Class
definition: Documentation of how an AI system's decisions can be explained to affected persons, operators, and regulators. Covers the explainability method used (SHAP, LIME, attention maps, rule extraction), the level of explanation (local vs global), and the target audience.

Human Oversight Plan
type: Class
definition: A plan for human oversight of an AI system. Specifies the oversight mode (human-in-the-loop, human-on-the-loop, human-in-command), the roles responsible for oversight, escalation procedures, and the conditions under which human intervention is required.

AI Governance Policy
type: Class
definition: An organizational policy governing AI development and deployment. Defines the principles, standards, processes, and roles that apply to AI systems within the organization. May reference external frameworks (EU AI Act, OECD Principles, NIST AI RMF).

AI Incident
type: Class
definition: A record of an incident involving an AI system — bias events, safety failures, drift-induced errors, adversarial attacks, or privacy breaches. Records the incident description, affected parties, root cause analysis, and remediation actions.

Transparency Record
type: Class
definition: Documentation provided to users or affected persons about an AI system's behavior, capabilities, and limitations. Required by the EU AI Act for limited-risk and high-risk AI systems.

Data Governance Record
type: Class
definition: A record of data governance measures applied to training and evaluation data — data quality checks, representativeness analysis, consent verification, anonymization measures, and data retention policies.

AI Regulatory Compliance
type: Concern
definition: Compliance of AI systems with applicable regulations — EU AI Act, GDPR, sector-specific regulations (financial services, healthcare, employment). Includes risk classification, conformity assessment, and ongoing monitoring obligations.

AI Accountability
type: Concern
definition: Clear assignment of responsibility for AI system behavior — who is accountable for decisions made by or with AI assistance, who is responsible for monitoring, and who handles incidents.

AI Transparency
type: Concern
definition: The degree to which AI system behavior, capabilities, and limitations are communicated to users, affected persons, and regulators. Includes disclosure obligations under the EU AI Act.

Human Oversight of AI
type: Concern
definition: Ensuring appropriate human control over AI system decisions — the ability to understand, intervene in, and override AI outputs when necessary.

AI Governance Overview
type: Viewpoint
definition: 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.
targets stakeholder: EthicsOfficer
viewpoint frames concern: AI Regulatory Compliance
viewpoint frames concern: AI Accountability
viewpoint has purpose: Governing
viewpoint has purpose: Informing
includes concept: AI System
includes concept: Risk Classification
includes concept: Conformity Assessment
includes concept: AI Governance Policy
view type: Catalog
view type: Matrix

AI Risk Assessment
type: Viewpoint
definition: 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.
targets stakeholder: EthicsOfficer
targets stakeholder: DataScientist
viewpoint frames concern: AI Regulatory Compliance
viewpoint frames concern: Human Oversight of AI
viewpoint has purpose: Governing
viewpoint has purpose: Deciding
includes concept: AI System
includes concept: Risk Classification
includes concept: Bias Assessment
includes concept: Explainability Report
includes concept: Human Oversight Plan
view type: Matrix
view type: Catalog

AI Transparency & Disclosure
type: Viewpoint
definition: View of transparency obligations — which AI systems require disclosure to users, what transparency records exist, and what information is provided to affected persons.
targets stakeholder: EthicsOfficer
viewpoint frames concern: AI Transparency
viewpoint has purpose: Governing
includes concept: AI System
includes concept: Transparency Record
view type: Catalog

AI Incident Tracking
type: Viewpoint
definition: View of AI incidents — bias events, safety failures, adversarial attacks, and their resolution. Used for post-incident analysis and continuous improvement of AI governance.
targets stakeholder: EthicsOfficer
targets stakeholder: MLEngineer
viewpoint frames concern: AI Accountability
viewpoint frames concern: AI Regulatory Compliance
viewpoint has purpose: Governing
includes concept: AI System
includes concept: AI Incident
view type: Catalog

wraps ML model
type: ObjectProperty
definition: Links an AI system governance wrapper to the ML model it governs.
domain includes: AI System
range includes: MLModel

wraps serving infrastructure
type: ObjectProperty
definition: Links an AI system governance wrapper to the serving infrastructure it governs.
domain includes: AI System
range includes: ServingInfrastructure

governed by
type: ObjectProperty
definition: Links an AI system to the governance policy that applies to it.
domain includes: AI System
range includes: AI Governance Policy

has risk classification
type: ObjectProperty
definition: Links an AI system to its risk classification.
domain includes: AI System
range includes: Risk Classification

classified as
type: ObjectProperty
definition: The risk level assigned in a risk classification.
domain includes: Risk Classification
range includes: AI Risk Level

classification rationale
type: DatatypeProperty
definition: The rationale for the risk classification decision.
domain: Risk Classification
range: string

classification date
type: DatatypeProperty
definition: The date the risk classification was performed.
domain: Risk Classification
range: date

classified by
type: ObjectProperty
definition: The stakeholder who performed the risk classification.
domain includes: Risk Classification
range includes: Stakeholder

has conformity assessment
type: ObjectProperty
definition: Links an AI system to a conformity assessment.
domain includes: AI System
range includes: Conformity Assessment

has bias assessment
type: ObjectProperty
definition: Links an AI system to a bias assessment.
domain includes: AI System
range includes: Bias Assessment

has explainability report
type: ObjectProperty
definition: Links an AI system to its explainability documentation.
domain includes: AI System
range includes: Explainability Report

has human oversight plan
type: ObjectProperty
definition: Links an AI system to its human oversight plan.
domain includes: AI System
range includes: Human Oversight Plan

has transparency record
type: ObjectProperty
definition: Links an AI system to its transparency documentation.
domain includes: AI System
range includes: Transparency Record

has data governance record
type: ObjectProperty
definition: Links an AI system to its data governance documentation.
domain includes: AI System
range includes: Data Governance Record

has incident
type: ObjectProperty
definition: Links an AI system to an incident record.
domain includes: AI System
range includes: AI Incident

assessed against principle
type: ObjectProperty
definition: Links an assessment to the AI principle it evaluates.
domain includes: Conformity Assessment
domain includes: Bias Assessment
range includes: AI Principle

assessment result
type: DatatypeProperty
definition: The result of an assessment — Pass, Fail, or Conditional with rationale.
range: string

assessment date
type: DatatypeProperty
definition: The date the assessment was performed.
range: date

assessed by
type: ObjectProperty
definition: The stakeholder who performed the assessment.
range includes: Stakeholder

assessment findings
type: DatatypeProperty
definition: Detailed findings from the assessment.
range: string

remediation action
type: DatatypeProperty
definition: Required or recommended remediation action based on assessment findings.
range: string

oversight mode
type: ObjectProperty
definition: The mode of human oversight applied to an AI system.
domain includes: Human Oversight Plan
range includes: Human Oversight Mode

oversight responsible
type: ObjectProperty
definition: The stakeholder or role responsible for human oversight.
domain includes: Human Oversight Plan
range includes: Stakeholder

escalation procedure
type: DatatypeProperty
definition: Description of the escalation procedure when human intervention is required.
domain: Human Oversight Plan
range: string

intervention conditions
type: DatatypeProperty
definition: Conditions under which human intervention is required.
domain: Human Oversight Plan
range: string

incident date
type: DatatypeProperty
definition: The date the AI incident occurred.
domain: AI Incident
range: date

incident description
type: DatatypeProperty
definition: Description of the AI incident.
domain: AI Incident
range: string

root cause analysis
type: DatatypeProperty
definition: Root cause analysis of the AI incident.
domain: AI Incident
range: string

incident severity
type: DatatypeProperty
definition: Severity of the AI incident (critical, high, medium, low).
domain: AI Incident
range: string

policy scope
type: DatatypeProperty
definition: The scope of the AI governance policy (organization-wide, business unit, project).
domain: AI Governance Policy
range: string

references framework
type: DatatypeProperty
definition: External framework referenced by the policy (EU AI Act, OECD Principles, NIST AI RMF, ISO 42001).
domain: AI Governance Policy
range: string

policy effective date
type: DatatypeProperty
definition: The date the governance policy takes effect.
domain: AI Governance Policy
range: date

mandates principle
type: ObjectProperty
definition: Links a governance policy to the AI principles it mandates.
domain includes: AI Governance Policy
range includes: AI Principle