What would a practical Change Control workflow look like for a hub-and-spoke Digital Twin, including versioning, approvals, and rollback steps?

Define a minimal Change Control for hub-and-spoke Digital Twins: 1) assign roles (Content Owner, Approver, Auditor) and a formal Request-Change workflow; 2) require versioning with updates tied to affected data streams; 3) mandate approvals before propagating changes to AI-facing outputs; 4) implement a rollback plan to revert to a prior version if issues arise; 5) maintain an auditable Change Log and conduct staging tests before production updates. All local spokes should reference central facts to maintain global consistency, with governance gates ensuring taxonomy and evidence links remain stable. This creates a reliable, auditable path from change request to AI-visible output.