Task: Create Data Quality infrastructure
This page documents a task in the Data Quality subsystem and Data Librarian story. It captures the goal, current status, acceptance, and any notes or results.
Goal
Lay out the conceptual foundations for the data-quality subsystem: how the project will manage curated sample data with full lineage and provenance.
Status
| Field | Value |
|---|---|
| State | DONE |
| Parent story | Data Quality subsystem and Data Librarian |
| Now | Completed 2026-01-15. |
| Waiting on | None. |
| Next | None. |
| Last touched | 2026-01-15 |
Acceptance
- Concept model documented: dataset, record, provenance, classification, lineage, temporal context, data passport.
- Metadata-attribute schema covering provenance + classification, lineage + derivation, temporal metadata.
- Granularity options (dataset vs record level) decided.
- Validation constraints captured (e.g. synthetic ⇒ generation_method required).
Plan
Captured during execution; cleared into the parent story on close.
Notes
Heavy use of LLM (Qwen) for the conceptual model; this is the design step ahead of the implementation tasks.
Result
DQ concept model documented; implementation can follow.