Data Qualification

Purpose

This page documents how source material is evaluated and qualified before it is admitted into the system. This layer exists to establish authoritative boundaries and prevent unreliable or out-of-scope material from shaping downstream behavior.

In practice, this is the difference between allowing any available document into a system and explicitly deciding which sources are trusted to shape answers.

It defines how authority, relevance, and suitability are determined prior to any extraction, enrichment, or generation.

Scope

Includes criteria for source selection, exclusion rules, handling of conflicting material, and treatment of incomplete, ambiguous, or degraded data. Excludes ingestion mechanics, storage implementation details, normalization techniques, and any assumptions about data completeness or correctness.

Constraints

• Only sources that meet explicitly defined authority and relevance criteria are eligible for use.
• Conflicting sources are not reconciled implicitly and must remain distinguishable throughout the system.
• Unqualified, unverifiable, or out-of-scope material is excluded rather than inferred or repaired.
• Qualification rules are explicit, inspectable, and stable so downstream behavior remains predictable.

These constraints establish the permissible knowledge boundary of the system. Relaxing them increases ambiguity and shifts error detection to later layers where correction is limited.

Notes

Data qualification defines the upper bound of system reliability. Errors introduced at this layer propagate silently and cannot consistently be corrected by later extraction, metadata, retrieval, or audit controls.