How can we design a hub-and-spoke Digital Twin governance pattern to keep local facts aligned with hub content when multiple locations update?

Architect the hub as the canonical source of facts (fact_id) and proofs, with each spoke carrying localized signals that reference those hub fact_ids through language-aware mappings. Enforce Change Control: local updates must be approved, mapped to hub facts, and versioned in a central Change Log before propagation. Use drift checks to detect deviations, and apply a rollback plan if misalignment is found. Regular cross-locale audits ensure local content remains aligned with core hub facts, maintaining global consistency while preserving local relevance in AI outputs.