Governance Ontology and Decision Graph
The governance ontology is the canonical semantic model for governed AI assets, evaluation evidence, experiment decisions, jobs, replay investigation, drift analysis, and MCP write audit records.
Overview
The ontology is the authoritative business model of Kavach; all storage models, APIs, graph projections, UI views, and AI reasoning are derived representations. It is intentionally independent of a graph database, relational schema, API transport, or UI. Storage engines project the ontology; they do not define it.
Kavach governance ontology graph
Selecting a node highlights its connected nodes and relationships, making the web of relationships easier to visualise.
Entity Taxonomy
Every first-class entity has stable identity, ownership, lifecycle state, and versioning rules.
Actor
External identity provider, human operator, service account, or MCP agent. Lifecycle: active, disabled, unknown.
Prompt & PromptVersion
A Prompt is a logical family; changes to content create a new PromptVersion. Lifecycle: DRAFT, ACTIVE, DEPRECATED, ARCHIVED.
Model & ModelVersion
Model metadata changes that affect reproducibility create a new ModelVersion. Lifecycle: DRAFT, ACTIVE, DEPRECATED, ARCHIVED.
Dataset
Versioned dataset metadata for governed evaluation use. Lifecycle: DRAFT, ACTIVE, DEPRECATED, ARCHIVED.
Experiment & ExperimentCandidate
An Experiment defines a comparison space. An ExperimentCandidate is an immutable AI configuration binding prompt, model, dataset, evaluation provider, and runtime parameters.
EvaluationResult & EvaluationRun
EvaluationResult is metric evidence for a single execution. EvaluationRun links an experiment candidate to a governed evaluation attempt.
GovernanceDecision
Captures the decision type, status, ontology-aligned target, evidence references, policy references, provenance, confidence, and supersession metadata.
GovernancePolicy
A versioned, deterministic policy definition for producing governance-oriented outcomes from structured evidence. Evaluated by GovernancePolicyEvaluator.
Relationships
Relationships are directed and named from source to target. They describe durable semantics; events describe temporal facts.
SUBMITS → EvaluationResult DEPENDS_ON → PromptVersion, ModelVersion, Dataset CONTAINS → ExperimentCandidate EVALUATED_BY → EvaluationProvider PRODUCES → GovernanceDecision GOVERNED_BY → GovernancePolicy SUPERSEDES → GovernanceDecision (older) EVIDENCE_FOR → GovernanceDecision
Actions and Events
Actions are imperative (e.g., CreateExperiment, EvaluateDecision). Events are past-tense (e.g., ExperimentCreated, EvaluationCompleted).
ExperimentCreated → Experiment EvaluationCompleted → EvaluationResult DecisionFinalized → GovernanceDecision DriftDetected → DriftAnalysis JobQueued → Job MCPAuditStarted → MCPAuditRecord
Deterministic Projection
The graph is a projection of relational state, not a second source of truth. Given the same relational records, projection always produces the same nodes and relationships. This determinism is what makes the graph safe to rebuild and verify.
Hashing & Reconciliation
Each projected entity carries a projection hash computed from its canonical fields. Alongside the node hash, Kavach hashes the full set of a node's relationships. A change in either hash marks the node for reconciliation, allowing incremental repair instead of full re-projection.
Ontology Versioning
The ontology version follows SemVer. Patch changes clarify wording or add non-normative examples. Minor changes add optional entities, relationships, attributes, actions, or events without changing existing semantics. Major changes rename or remove entities, relationships, required fields, or lifecycle meanings.
Existing entity and relationship names remain valid for the full major version. Deprecated concepts must remain documented with replacement guidance for at least one major version.
