Diagnostic domain
Semantic Reliability
The reliability domain focused on whether models, metrics, joins, and definitions continue to preserve intended business meaning over time.
ARF layer: semantic-integrityARF layer: context-stabilityARF layer: analytical-explainabilityARF layer: ai-readiness-interoperability
Failure mode: metric-definition-driftFailure mode: intent-mismatchFailure mode: silent-data-corruption
What this domain covers
Semantic reliability focuses on whether the analytical meaning of the system remains intact as data, models, business logic, and questions evolve.
A dashboard or agent can return a result successfully while still being semantically wrong. That is why this domain matters. It captures the failures that traditional refresh monitoring and infrastructure health checks do not catch.
How it breaks ARF layers
Semantic Integrityfails when the platform no longer maintains one clear meaning per metric or business conceptContext Stabilityfails when filter and relationship behavior changes the meaning of the questionAnalytical Explainabilityfails when the reported number cannot be justified in business termsAI Readiness & Interoperabilityfails when systems cannot reliably infer the intended meaning behind a prompt or metric
High-value controls
- canonical metrics and controlled variants
- strong naming and description conventions
- semantic change review
- lineage and driver modeling that support explanation
Where this matters most
This domain sits at the center of the expanded ARF because it is the place where trustworthy analytics and trustworthy AI most often converge or fail together.