Practical guidelines for taxonomy, content lifecycle, roles, compliance, risk controls, and reusable governance patterns.
A practical, ready-to-adapt toolkit of policy templates and guidance to govern taxonomy, content lifecycle, learning-data access, retention, and vendor risk — plus clear steps for tailoring, ownership, and review so teams use governance instead of being blocked by it.
A practical, easy-to-adopt starter guide that explains lightweight taxonomy goals, a simple category + tag model, a canonical starter tag list, owner and stewardship rules, naming conventions, lifecycle signals, examples for decisions/experiments/playbooks, and a short governance calendar you can copy and run.
A practical, ready-to-adopt template that defines how knowledge artifacts are created, approved, reviewed, versioned, archived, and retired — with clear roles, metadata requirements, sample retention rules by artifact criticality, and a short policy adoption checklist.
Practical, actionable guidance for designing and operating a sustainable tag and taxonomy system: naming rules, ownership, canonical tags and aliases, migration patterns, review cadences, quick audit queries, and an ownership model that keeps discoverability usable over time.
A pragmatic, phased playbook that helps teams design, operate, and scale a lightweight taxonomy and governance regime. Includes principles, a four-phase starter plan, lifecycle templates, a quarterly pruning checklist, a contributor governance-council template, role definitions, and measurable success signals.
A practical, action-oriented checklist to evaluate privacy, consent, retention, access, bias, provenance, and operational risks when datasets are repurposed for organizational learning, analytics, or AI. Includes guidance on how to use the checklist, suggested mitigations, and a simple action template for assignment and follow-up.
An actionable, savable audit checklist to evaluate whether taxonomy and tagging support discoverability, reuse, and analytics — with built-in remediation suggestions and place to record evidence and next steps.
A compliance-focused checklist covering retention policies, DSAR handling, vendor risk, and knowledge system controls.
An actionable, fillable checklist to assess dataset readiness for learning and experiments. Covers classification, PII, consent/legal basis, anonymization, permitted uses, retention, DSAR risk, auditability, mitigations, and a lightweight approval workflow.