- adapt meta-/code-/obs- rules to the local Python benchmark pipeline - replace db-sql-ddl, code-config-env-scope, test-e2e-pytest with pipeline equivalents - add code-python-style, data-determinism, data-naming-units, bench-methodology, build-pipeline-tasks - normalize specs and README typography to ASCII per code-data-formatting - rewrite root CLAUDE.md trigger table; add .cursorrules and .gitignore - specs: pipeline plan and task specs 00-11 - rules: 19 binding rule files adapted for this project - docs: CLAUDE.md rule-trigger table - config: .cursorrules commit convention, .gitignore excluding out/ and .venv/ - docs: rewrite README.md with pipeline diagrams, setup guide, result placeholders - config: requirements.txt for the closed dependency list - datagen: make_lab_config.py writes out/config/lab_config.yaml and .done marker
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Task 08 — Ontology: Relational Schema, Data Dictionary, Instruments Repository
Goal
Formal, versioned data model driving cleansing and all exports. Iterates with Tasks 07/09/10.
Input
- ERD (project artifact
Mary_G__LabResults__ERD.txt),schema/ontology_escalations.md.
Actions
- Generate
schema/ddl_postgresql.sqlfrom the ERD: full hierarchyptau_data_notes → batches → coupons → samples, four measurement branches,atmosphereslookup,measurement_types+column_definitions. - Generate
schema/data_dictionary.csv: per measurement type — column name, unit, dtype, ordinal, description (source: the mappings of Task 07). - Create
schema/instruments_repository.csv: instrument id, type, measurement type produced, measured quantities, units, valid min/max ranges, resolution. Populate incrementally from tokens + column signatures; ranges feed Task 09 anomaly rules. - Maintain
schema/ontology_notes.md: every schema change with rationale (append-only). - Version the DDL (
-- schema_version: Nheader); bump on each iteration.
Intermediate Result (done when)
- DDL, data dictionary, and Instruments Repository are mutually consistent and cover all mapped fingerprints.
- No open items in
ontology_escalations.md.