Knowledge Management Governance

Purpose

Knowledge Management Governance defines the policies, responsibilities, evidence requirements, and decision processes governing how knowledge moves through the OSI/PIA Knowledge Lifecycle.

It governs the evolution of knowledge rather than the operational governance of organizations, software permissions, security controls, or institutional authority.

Scope

Knowledge Management Governance applies to any artifact that carries project knowledge, including:

  • research notes
  • datasets
  • graph models
  • ontologies
  • architecture
  • ADRs
  • methodologies
  • software components
  • component contracts
  • AI outputs
  • participant materials
  • educational content
  • governance protocols

Core Questions

Knowledge Management Governance answers:

  1. What lifecycle state is this knowledge in?
  2. What evidence supports that classification?
  3. What criteria must be met before transition?
  4. Who may recognize or authorize the transition?
  5. How is the decision recorded?
  6. What becomes canonical after promotion?
  7. Who is responsible for stewardship?
  8. How are revisions, deprecation, replacement, and retirement handled?

Governing Principles

Knowledge Is Not Promoted by Repetition

Frequency of use, confidence of presentation, or repeated AI generation does not by itself justify promotion.

Promotion Represents Justified Confidence

Promotion indicates increased justified confidence, not certainty or permanence.

Provenance Must Be Preserved

Promoted knowledge should retain traceable relationships to its evidence, reasoning, contributors, decisions, and prior versions.

Authority Must Be Proportionate

The significance and reach of a transition should determine the level of review and authority required.

Stewardship Is Part of Promotion

Knowledge should not be promoted without an identified means of maintenance, review, and correction.

Reversibility Must Be Possible

Knowledge may return to exploration, formulation, congruence, or validation when new evidence or contradiction appears.

Roles

Roles may be performed by one person in early project stages and distributed among maintainers as the ecosystem grows.

Contributor

Introduces observations, evidence, analysis, formulations, implementations, or revisions.

Reviewer

Evaluates evidence quality, internal coherence, congruence, risks, and readiness for transition.

Maintainer

Manages the integrity of a documentation, architecture, component, ontology, or methodology domain.

Promotion Authority

Recognizes that required evidence and review have been satisfied and authorizes a change in status.

Steward

Maintains promoted knowledge, monitors continuing validity, records changes, and initiates revision or retirement when necessary.

Transition Governance

Observation to Exploration

Requires a recorded observation or question with enough context to support meaningful inquiry.

Exploration to Formulation

Requires sufficient evidence, comparison, or reasoning to construct an explicit and examinable proposition, model, method, or design.

Formulation to Congruence

Requires a coherent formulation with defined terms, assumptions, scope, relationships, and intended use.

Congruence to Validation

Requires completion of relevant congruence review with contradictions resolved, bounded, or explicitly recorded.

Validation to Promotion

Requires evidence appropriate to the claim and artifact, review proportionate to risk, and a recorded rationale for promotion.

Promotion to Stewardship

Requires designation of canonical location, version or status, responsible steward, review expectations, and provenance.

Promotion Authority

Promotion authority should reflect the type and consequence of the knowledge being promoted.

Examples:

  • research note: author or domain contributor
  • architectural reference: architecture maintainer or recorded design decision
  • methodology: domain review and evidence of successful use
  • ontology or graph schema: architecture and implementation review
  • software component: validated testing and maintainer approval
  • public educational material: content review and project steward approval
  • ecosystem-wide principle: explicit project-level decision and durable record

These examples establish direction rather than a complete authority matrix. Detailed authority may be defined in future ADRs or domain-specific governance documents.

Evidence Requirements

Evidence should be proportionate to the claim, risk, scope, and reversibility of the transition.

Evidence may include:

  • source documentation
  • participant evidence
  • empirical results
  • reproducible analysis
  • comparison with alternative explanations
  • implementation results
  • assurance reports
  • test results
  • expert or maintainer review
  • repeated successful use
  • recorded limitations and uncertainty

Absence of contradiction is not sufficient evidence of truth. Congruence and validation serve different purposes.

Canonical Knowledge

Canonical knowledge is the current authoritative project reference after completing the required promotion process.

Canonical status should identify:

  • authoritative location
  • current version or status
  • promotion rationale
  • provenance
  • responsible steward
  • known limitations
  • superseded material when applicable

Canonical does not mean immutable. It means authoritative until revised, superseded, deprecated, or retired through governance.

Versioning and Change

Material changes to canonical knowledge should preserve:

  • prior versions or meaningful history
  • rationale for change
  • evidence supporting the revision
  • affected dependencies
  • migration or interpretation guidance where needed

Minor editorial changes may not require renewed validation. Changes affecting meaning, scope, structure, claims, or implementation obligations should re-enter the lifecycle at the appropriate stage.

Deprecation, Supersession, and Retirement

Deprecation

Knowledge remains available but is no longer recommended for new reliance or implementation.

Supersession

A newer reference replaces the prior canonical reference while preserving traceability between them.

Retirement

Knowledge is removed from active project use because it is obsolete, invalid, harmful, unsupported, or outside project scope.

Every deprecation, supersession, or retirement should record the reason, authority, date, and replacement when one exists.

AI Responsibilities

AI systems participating in OSI/PIA work should:

  • distinguish source-derived knowledge from inference and generation
  • avoid presenting exploratory material as canonical
  • preserve uncertainty and provenance where available
  • identify contradictions rather than silently resolving them
  • avoid promoting knowledge without required human or architectural authority
  • support lifecycle classification, retrieval, comparison, and documentation
  • treat AI generation as contribution, not validation

Human Responsibilities

Human contributors and maintainers should:

  • label working status clearly
  • preserve evidence and decision rationale
  • apply review proportionate to consequence
  • avoid premature canonicalization
  • maintain promoted knowledge
  • correct or retire knowledge when evidence changes
  • ensure governance supports learning rather than bureaucracy

Relationship to the Congruence Protocol

The Knowledge Lifecycle defines knowledge states.

The Congruence Protocol evaluates compatibility and contradiction across relevant domains.

Knowledge Management Governance defines policy, authority, evidence expectations, and decision records for transitions.

Assurance supplies structured evaluation that may support congruence, validation, promotion, and stewardship.

Initial Implementation

During the early project stage, governance may be implemented through:

  • explicit document status labels
  • canonical repository locations
  • ADRs for significant decisions
  • commit history
  • glossary maintenance
  • review notes
  • change logs
  • named stewardship responsibility

Automation may later assist with lifecycle metadata, transition checklists, dependency review, stale-document detection, provenance, and canonical reference indexing.

Status

This document establishes the initial Knowledge Management Governance framework. Detailed authority matrices, transition checklists, metadata standards, and automated enforcement remain subjects for future formulation, validation, and promotion.