DataOps-platform/docs/superpowers/plans/2026-07-22-data-research-v60-v65-delivery-plan.md

Data Research V60-V65 Implementation Plan

For agentic workers: REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (- [ ]) syntax for tracking.

Goal: Upgrade DataOps data research into a tested, evidence-backed ingestion, data-element governance, and multi-domain ontology platform through V60-V65.

Architecture: PostgreSQL is the control-plane source of truth for jobs, evidence, candidates, reviews, immutable versions, and publication state. MinIO stores source artifacts, while Neo4j stores the active semantic projection; existing Outbox processing provides idempotent cross-store publication. A new /api/development/v1 boundary orchestrates existing datasource, metadata, business-domain, knowledge, and graph capabilities without removing legacy APIs.

Tech Stack: Python 3.11, Flask, Flask-SQLAlchemy, Alembic, PostgreSQL JSONB, Neo4j, MinIO, SQLAlchemy inspector/catalog queries, pandas/openpyxl, python-docx, pdfplumber, pluggable OCR, Vue 2/Vuetify, pytest.

Global Constraints

• Use TDD for every production behavior: add one failing test, verify the expected failure, implement minimally, then rerun the focused and phase suites.
• Preserve /api/meta, /api/bd, /api/datasource, DataMeta, and BusinessDomain-[:INCLUDES]->DataMeta during compatibility migration.
• Use stable UUID strings for all new cross-store references; Neo4j integer IDs are legacy compatibility only.
• Database collection is read-only through DataSourceConnectionManager.connect(uid, "metadata_collection"); never accept arbitrary metadata SQL from the client.
• AI/OCR output is always a candidate with confidence and evidence; it cannot directly publish a data element or ontology.
• Credentials, connection strings, tokens, and unredacted sensitive samples must not appear in API responses, logs, model requests, or evidence previews.
• app/ is primary source. Update deployment/app/ only through deployment/sync_release.sh at V65 release preparation.
• Every phase ends with focused tests, the complete Python suite, frontend production build when frontend changes exist, and git diff --check.

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V60 — Unified model and ingestion foundation

Task 1: Add ingestion control-plane schema and models

Files:

• Create: migrations/versions/20260722_100_data_research_ingestion.py
• Create: app/models/data_research.py
• Modify: app/models/__init__.py
• Modify: tests/test_database_migrations.py
• Test: tests/data_research/test_ingestion_models.py

Interfaces:

• Produces: IngestionSource, IngestionJob, SourceArtifact, EvidenceFragment, ExtractionCandidate SQLAlchemy models.

• Produces: job statuses created, queued, extracting, normalizing, matching, awaiting_review, published, partial, failed, cancelled.

• [x] Write migration contract tests asserting the five tables, UUID foreign keys, content-hash/parser-version idempotency key, JSONB evidence locator, status checks, and non-destructive downgrade.

• [x] Run PYTHONPATH=. .venv/bin/pytest -q tests/test_database_migrations.py tests/data_research/test_ingestion_models.py and verify failure because the migration and models do not exist.

• [x] Implement the additive migration and SQLAlchemy models with to_dict() methods that never serialize storage credentials or internal MinIO secrets.

• [x] Rerun the focused tests and verify they pass.

Task 2: Implement ingestion state machine and idempotent job service

Files:

• Create: app/core/data_research/__init__.py
• Create: app/core/data_research/errors.py
• Create: app/core/data_research/models.py
• Create: app/core/data_research/repository.py
• Create: app/core/data_research/ingestion.py
• Test: tests/data_research/test_ingestion_service.py

Interfaces:

• Produces: IngestionService.create_job(payload, actor_uid), transition(job_uid, target_status, statistics=None, error=None), retry(job_uid), and cancel(job_uid).

• Produces: IngestionJobSpec, JobTransition, and typed errors InvalidJobTransition, IngestionJobNotFound, IngestionPayloadInvalid.

• [x] Write tests for deterministic idempotency keys, same-input job reuse, force-rerun behavior, allowed/forbidden transitions, retry from failed, cancellation, and redacted error serialization.

• [x] Run PYTHONPATH=. .venv/bin/pytest -q tests/data_research/test_ingestion_service.py and verify failure because the service is absent.

• [x] Implement pure transition rules and repository-injected orchestration; keep Flask globals out of the core service.

• [x] Rerun the focused tests and verify they pass.

Task 3: Add the development API boundary, permissions, and task contracts

Files:

• Create: app/api/data_development/__init__.py
• Create: app/api/data_development/routes.py
• Modify: app/__init__.py
• Modify: app/core/system/permissions.py
• Create: frontend/src/api/dataDevelopment.js
• Test: tests/data_research/test_development_api.py
• Test: tests/data_research/test_development_frontend_contract.py
• Modify: tests/test_permission_matrix.py

Interfaces:

• Produces: POST/GET /api/development/v1/ingestion-jobs, GET /ingestion-jobs/<uid>, POST /<uid>/retry, and POST /<uid>/cancel.

• Produces: permissions ingestion:run, ingestion:admin, evidence:download, data-elements:edit, data-elements:publish, ontologies:edit, ontologies:publish.

• [x] Write API and permission tests for 401, 403, editor create/list, owner cancellation, admin retry, stable response envelopes, and secret-free payloads.

• [x] Run the focused API/permission tests and verify missing blueprint/permissions failures.

• [x] Register the blueprint, add monotonic role permissions, inject the service through a testable factory, and add frontend API wrappers.

• [x] Run focused tests, regenerate docs/architecture/OPENAPI.yaml, then rerun architecture artifact tests.

V60 gate

• Run PYTHONPATH=. .venv/bin/pytest -q tests/data_research tests/test_database_migrations.py tests/test_permission_matrix.py tests/test_architecture_artifacts.py.
• Run PYTHONPATH=. .venv/bin/pytest -q and git diff --check.
• Record evidence in docs/validation/data-research-v60.md and commit V60.

V61 — Database catalog and structured files

Task 4: Add deterministic SQL, CSV, and Excel extractors

Files:

• Create: app/core/data_research/extractors/base.py
• Create: app/core/data_research/extractors/sql.py
• Create: app/core/data_research/extractors/csv.py
• Create: app/core/data_research/extractors/excel.py
• Create: app/core/data_research/extractors/registry.py
• Test: tests/data_research/test_structured_extractors.py

Interfaces:

• Produces: Extractor.can_handle(media_type, filename), extract(stream, context) -> ExtractionBatch, and evidence locators sql.statement, csv.header, excel.sheet/cell_range.

• Consumes: existing DDLParser only as SQL fallback; deterministic extraction runs first.

• [x] Write tests for dialect-preserving DDL, multi-table SQL, BOM/delimiter CSV, empty/header-only CSV, multi-sheet Excel, parser version, content hash, and exact evidence positions.

• [x] Run the extractor tests and verify missing-registry failures.

• [x] Implement bounded streaming extractors and registry selection without reading arbitrary large files into unbounded memory.

• [x] Rerun focused tests and existing tests/test_ddl_parser_view.py.

Task 5: Add PostgreSQL and MySQL catalog collectors with snapshot diff

Files:

• Create: app/core/data_research/catalog/base.py
• Create: app/core/data_research/catalog/postgresql.py
• Create: app/core/data_research/catalog/mysql.py
• Create: app/core/data_research/catalog/service.py
• Test: tests/data_research/test_catalog_collectors.py
• Test: tests/integration/test_data_research_catalog.py

Interfaces:

• Produces: CatalogCollectionService.collect(data_source_uid, scope) -> CatalogSnapshot and diff(previous, current) -> CatalogDiff.

• Consumes: DataSourceConnectionManager.connect(uid, "metadata_collection") and allowlisted schema/table filters.

• [x] Write unit tests for generated allowlisted catalog statements, schema/table exclusions, stable field keys, no business-row reads, add/remove/type/rename diffs, and query timeout propagation.

• [x] Run unit tests and verify missing collector failures.

• [x] Implement dialect collectors and pure snapshot differ; never concatenate untrusted identifiers into SQL.

• [x] Run unit tests and, when source containers are available, the integration catalog test.

Task 6: Implement data-element lifecycle and candidate decisions

Files:

• Create: app/core/data_research/data_elements.py
• Create: app/core/data_research/candidate_decisions.py
• Create: app/core/data_research/graph_projection.py
• Modify: app/api/data_development/routes.py
• Modify: app/models/data_research.py
• Create: tests/data_research/test_data_element_lifecycle.py
• Create: tests/data_research/test_candidate_decisions.py

Interfaces:

• Produces: lifecycle candidate -> draft -> in_review -> published -> deprecated -> retired.

• Produces: batch decisions reuse, create, map, ignore, and outbox event data_element.version_published.

• [x] Write tests for required definitions, stable UID/version increments, optimistic concurrency, invalid lifecycle moves, batch decision atomicity, evidence retention, and no direct candidate publication.

• [x] Run focused tests and verify missing service failures.

• [x] Implement lifecycle/version services, extend API endpoints, and emit outbox events within the PostgreSQL transaction.

• [x] Rerun focused tests plus outbox and cross-store consistency tests.

V61 gate

• Run all V61-focused tests and tests/core/data_source.
• Run the complete Python suite and git diff --check.
• Record evidence in docs/validation/data-research-v61.md and commit V61.

V62 — Documents, scanned PDFs, and images

Task 7: Add DOCX and text-PDF evidence extractors

Files:

• Create: app/core/data_research/extractors/docx.py
• Create: app/core/data_research/extractors/pdf.py
• Modify: app/core/data_research/extractors/registry.py
• Test: tests/data_research/test_document_extractors.py

Interfaces:

• Produces evidence locators docx.paragraph/table/row/cell and pdf.page/table/bbox.

• [x] Write in-memory fixture tests for paragraphs, tables, repeated headers, empty documents, page ordering, and exact evidence locations.

• [x] Run focused tests and verify missing extractors.

• [x] Implement structured extraction using python-docx and pdfplumber; return OCR-required classification when a PDF page has no usable text.

• [x] Rerun focused tests and existing DDL document parser tests.

Task 8: Add pluggable OCR and scanned-document processing

Files:

• Create: app/core/data_research/ocr/base.py
• Create: app/core/data_research/ocr/http_provider.py
• Create: app/core/data_research/ocr/service.py
• Create: app/core/data_research/extractors/image.py
• Test: tests/data_research/test_ocr_service.py
• Test: tests/data_research/test_image_extractor.py

Interfaces:

• Produces: OcrProvider.extract(image_bytes) -> list[OcrBlock] with text, normalized bounding box, page, and confidence.

• Produces: a fail-closed HTTP provider with configured endpoint, timeout, TLS verification, response-size limit, and no implicit external default.

• [x] Write tests with a local fake provider for PNG/JPEG, multi-page scanned PDF page ordering, normalized boxes, low-confidence review flags, provider timeout, malformed response, and disabled-provider failure.

• [x] Run tests and verify missing OCR interfaces.

• [x] Implement provider abstraction, fail-closed configuration, image extractor, and scanned-PDF page handoff.

• [x] Rerun focused tests and verify no source bytes or tokens appear in errors/logs.

Task 9: Unify file policy, artifact storage, and evidence preview

Files:

• Create: app/core/data_research/file_policy.py
• Create: app/core/data_research/artifacts.py
• Modify: app/api/data_development/routes.py
• Modify: app/config/config.py
• Test: tests/data_research/test_file_policy.py
• Test: tests/data_research/test_evidence_api.py

Interfaces:

• Produces: one allowlist for SQL, XLS/XLSX, CSV, DOCX, PDF, PNG, JPG/JPEG; legacy DOC returns a deterministic conversion-required error.

• Produces: POST /sources/files and permission-filtered GET /evidence/<uid>; full download requires evidence:download.

• [x] Write tests for extension/MIME/magic agreement, size/page limits, legacy DOC rejection, hash deduplication, unsafe filenames, evidence redaction, and download permissions.

• [x] Run focused tests and verify failures against current split policies.

• [x] Implement the unified policy, MinIO gateway abstraction, artifact hash reuse, and redacted preview endpoint.

• [x] Rerun focused tests plus datasource/file security regression tests.

V62 gate

• Run all V62-focused tests, the complete Python suite, and git diff --check.
• Record evidence in docs/validation/data-research-v62.md and commit V62.

V63 — Ontology MVP

Task 10: Add ontology control-plane schema and repository

Files:

• Create: migrations/versions/20260722_110_data_research_ontology.py
• Extend: app/models/data_research.py
• Create: app/core/data_research/ontology/models.py
• Create: app/core/data_research/ontology/repository.py
• Test: tests/data_research/test_ontology_schema.py
• Test: tests/data_research/test_ontology_repository.py

Interfaces:

• Produces: Ontology, immutable OntologyVersion, OntologyChangeSet, and OntologyPublishRun.

• Produces graph document fields classes, properties, relations, constraints, domain_links, and element_mappings.

• [ ] Write schema and repository tests for unique ontology codes, immutable published versions, parent version, content hash, many-domain role links, and optimistic draft revisions.

• [ ] Run focused tests and verify missing schema/repository failures.

• [ ] Implement additive migration, dataclasses, canonical graph hashing, and repository operations.

• [ ] Rerun focused and migration tests.

Task 11: Implement ontology validation, publication, projection, and rollback

Files:

• Create: app/core/data_research/ontology/validation.py
• Create: app/core/data_research/ontology/publication.py
• Create: app/core/data_research/ontology/projection.py
• Test: tests/data_research/test_ontology_validation.py
• Test: tests/data_research/test_ontology_publication.py

Interfaces:

• Produces validation codes for duplicate names, dangling edges, inheritance cycles, invalid cardinality, ownerless ontology, and unmapped required property.

• Produces events ontology.version_published and ontology.rollback_version_created.

• [ ] Write tests for every validation code, publish idempotency, outbox atomicity, active-version projection, retryable Neo4j failure, version diff, and rollback-as-new-version behavior.

• [ ] Run focused tests and verify missing service failures.

• [ ] Implement pure validation, publish transaction, UID-based Neo4j projection, diff, and rollback version creation.

• [ ] Rerun focused tests plus cross-store/outbox tests.

Task 12: Add ontology APIs and Vue 2 ontology center

Files:

• Modify: app/api/data_development/routes.py
• Modify: frontend/src/api/dataDevelopment.js
• Create: frontend/src/views/dataGovernance/ontology/index.vue
• Create: frontend/src/views/dataGovernance/ontology/workbench.vue
• Modify: frontend/src/router/routes.js
• Test: tests/data_research/test_ontology_api.py
• Test: tests/data_research/test_ontology_frontend_contract.py

Interfaces:

• Produces ontology CRUD, graph patch, validate, publish, diff, and rollback endpoints under /api/development/v1.

• Produces permission-gated ontology list and workbench routes.

• [ ] Write API tests for editor drafts, publisher release, multi-domain roles, ETag conflicts, validation errors, and viewer read-only behavior; write source contract tests for routes and secret-free rendering.

• [ ] Run focused tests and verify missing endpoints/pages.

• [ ] Implement API handlers and Vue pages with graph JSON editing/preview, validation panel, version diff, and publish confirmation.

• [ ] Run focused tests and frontend production build.

V63 gate

• Run all ontology tests, complete Python suite, frontend build, and git diff --check.
• Record evidence in docs/validation/data-research-v63.md and commit V63.

V64 — Dynamic ontology and knowledge services

Task 13: Generate and review explainable ontology change sets

Files:

• Create: app/core/data_research/ontology/suggestions.py
• Create: app/core/data_research/ontology/change_sets.py
• Modify: app/api/data_development/routes.py
• Test: tests/data_research/test_ontology_suggestions.py
• Test: tests/data_research/test_ontology_change_sets.py

Interfaces:

• Produces deterministic suggestions from business domains, published data elements, foreign-key evidence, and aliases before optional AI suggestions.

• Produces decisions accept, reject, edit with actor, reason, evidence UIDs, confidence, and model/prompt version.

• [ ] Write tests for deterministic class/property/relation proposals, evidence-required AI proposals, confidence ordering, conflict detection, partial decisions, and the guarantee that undecided suggestions never publish.

• [ ] Run focused tests and verify missing services.

• [ ] Implement rule suggestions, injected AI suggestion port, immutable decision audit, and accepted-change application to a draft version.

• [ ] Rerun focused tests and ontology publication regressions.

Task 14: Add JSON/RDF/OWL exchange and governance knowledge synchronization

Files:

• Create: app/core/data_research/ontology/exchange.py
• Create: app/core/data_research/ontology/knowledge_sync.py
• Modify: app/api/data_development/routes.py
• Test: tests/data_research/test_ontology_exchange.py
• Test: tests/data_research/test_ontology_knowledge_sync.py

Interfaces:

• Produces deterministic JSON export and bounded RDF/OWL XML export/import with stable platform UIDs.

• Consumes: app/core/knowledge/document_builder.py; produces versioned governance documents only for published ontology versions.

• [ ] Write round-trip tests for classes/properties/relations/domain links, unsafe XML rejection, import size limits, deterministic hashes, secret redaction, and knowledge-document version/hash behavior.

• [ ] Run focused tests and verify missing exchange/sync modules.

• [ ] Implement bounded import/export, canonical namespaces, publication-triggered knowledge documents, and idempotent chunk sync.

• [ ] Rerun focused tests plus governance document builder tests.

Task 15: Expose read-only semantic queries and MCP context

Files:

• Create: app/core/data_research/ontology/query.py
• Modify: app/api/data_development/routes.py
• Modify: app/core/mcp/context.py
• Test: tests/data_research/test_semantic_query.py
• Test: tests/mcp/test_data_research_context.py

Interfaces:

• Produces bounded read-only queries from ontology property to data element, physical field, source evidence, and business domain.

• Produces MCP context tools that return published data only and enforce permission scope.

• [ ] Write tests for bounded traversal, unpublished exclusion, permission filtering, stable pagination, no arbitrary Cypher input, and MCP result redaction.

• [ ] Run focused tests and verify missing query/tool behavior.

• [ ] Implement allowlisted query methods and MCP context adapters.

• [ ] Rerun focused tests and existing MCP security/runtime suites.

V64 gate

• Run all V64-focused, governance knowledge, MCP, complete Python, and frontend build tests.
• Record evidence in docs/validation/data-research-v64.md and commit V64.

V65 — Production hardening and acceptance

Task 16: Add limits, metrics, reconciliation, and recovery

Files:

• Create: app/core/data_research/operations.py
• Create: app/commands/reconcile_data_research.py
• Modify: app/core/system/health.py
• Test: tests/data_research/test_operations.py
• Test: tests/integration/test_data_research_reconciliation.py

Interfaces:

• Produces metrics for job states/duration, failure stage, candidate acceptance, review time, ontology coverage, and projection lag.

• Produces reconciliation reports for PostgreSQL versions, Neo4j active projections, MinIO artifacts, and governance documents.

• [ ] Write tests for concurrency/resource limits, stale-job recovery, dead-letter reporting, projection mismatch repair plans, artifact-missing detection, and secret-free health output.

• [ ] Run focused tests and verify missing operations module.

• [ ] Implement bounded counters, recovery transitions, read-only audit, explicit repair mode, and health component.

• [ ] Rerun focused tests plus health/outbox tests.

Task 17: Complete task center, ingestion, data-element, and ontology UX

Files:

• Create: frontend/src/views/dataGovernance/development/index.vue
• Create: frontend/src/views/dataGovernance/development/ingestion.vue
• Create: frontend/src/views/dataGovernance/development/tasks.vue
• Create: frontend/src/views/dataGovernance/development/review.vue
• Modify: frontend/src/views/dataGovernance/metadata/index.vue
• Modify: frontend/src/router/routes.js
• Test: tests/data_research/test_data_research_frontend_contract.py

Interfaces:

• Produces source selection, scope configuration, upload, progress, evidence preview, batch decisions, data-element lifecycle, ontology generation, validation, publish, and rollback navigation.

• [ ] Write frontend source-contract tests for every required route/API/permission, supported format copy, evidence navigation, status labels, no credential fields, and viewer read-only controls.

• [ ] Run focused tests and verify missing pages/contracts.

• [ ] Implement Vue 2 pages using existing list/dialog/form patterns and permission metadata.

• [ ] Run focused tests and npm --prefix frontend run build with Node 24.

Task 18: Release parity, documentation, and end-to-end acceptance

Files:

• Create: tests/acceptance/test_data_research_v60_v65.py
• Create: docs/validation/data-research-v60-v65-acceptance.md
• Modify: docs/architecture/ARCHITECTURE_OVERVIEW.md
• Modify: docs/architecture/DATA_MODEL.md
• Modify: docs/architecture/NEXT_ITERATION_ROADMAP.md
• Modify: docs/architecture/OPENAPI.yaml
• Modify: deployment/app/ via deployment/sync_release.sh

Interfaces:

• Produces one acceptance entry point covering source ingestion, evidence, data-element publication, two-domain ontology, dynamic change set, publish, rollback, knowledge sync, RBAC, reconciliation, and redaction.

• [ ] Write acceptance tests that initially fail on any missing V60-V65 capability and use deterministic fixtures/fake OCR/AI ports while exercising real Flask services and persistence contracts.

• [ ] Run PYTHONPATH=. .venv/bin/pytest -q tests/acceptance/test_data_research_v60_v65.py and verify requirement-specific failures before final wiring.

• [ ] Complete release wiring, regenerate OpenAPI, run deployment/sync_release.sh, and verify diff -qr app deployment/app is empty for application source.

• [ ] Run the final acceptance matrix below and record exact commands, counts, skips, build output, and environment-limited checks in the acceptance document.

V65 and final acceptance gate

• PYTHONPATH=. .venv/bin/pytest -q tests/data_research tests/acceptance/test_data_research_v60_v65.py
• PYTHONPATH=. .venv/bin/pytest -q
• npm --prefix frontend run build
• python scripts/generate_openapi.py --output docs/architecture/OPENAPI.yaml followed by PYTHONPATH=. .venv/bin/pytest -q tests/test_architecture_artifacts.py.
• diff -qr app deployment/app and git diff --check.
• When Docker is available, run catalog, reconciliation, RBAC, MCP, and migration integration tests against deploy/docker/docker-compose.yml.
• Mark V60-V65 complete only if every non-environment-limited requirement has fresh passing evidence and every skipped external check is explicitly listed with its blocker.