Canonical technical pattern for systems that train, adapt, or aggregate models across multiple sites, devices, tenants, or organizations without centralizing raw data, often with privacy-preserving aggregation, site-local training, and interpretable or explainable outputs. Map only when distributed model training or federated learning is explicit; do not map distributed dashboards, multi-site reporting, or generic enterprise platforms.