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Personal Data Engine (Data Connect Framework) (Public Template)

This repository contains the public, privacy-safe framework for the Personal Data Engine: schema-driven ingestion, normalization, canonical entity modeling, and export lanes across heterogeneous personal datasets.

It intentionally excludes runtime databases, exported archives, logs, and private account artifacts.

Safe By Default

  • Includes contracts, schemas, and ingestion/normalization scripts.
  • Includes empty scaffold folders for local runtime.
  • Excludes personal data and generated outputs via .gitignore.

Documentation

  • Data Workflow: what the platform builds, how data is collected/processed, and how personal data is kept out of this public template.
  • Case Study: what was learned building the ingestion and processing system.

Data Connect Platform

This repository uses meta/ as the current workspace root.

Workspace Products

  • meta/raw/: immutable source artifacts and indexes
  • meta/working/: extracted archives and temporary staging
  • meta/normalized/: source-shaped normalized records
  • meta/canonical/: cross-source entities, events, relationships, artifacts
  • meta/views/: app- and SDK-facing derived datasets
  • meta/manifests/: build manifests, source freshness, source health
  • meta/schemas/: canonical, view, and manifest contracts
  • meta/scripts/: platform build and compatibility scripts
  • meta/lanes/: lane-specific outputs for connector, local, and full-export
  • runtime/: ephemeral indexes, sqlite databases, state, and logs
  • personal-server/: adjacent personal server state and exported connector data

Compatibility

Scripts accept CLI args and environment overrides. In docs, prefer repository-relative paths.

Contracts

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Privacy-first personal data engine — schema-driven ingestion, canonical entity modeling, and local-first data pipelines

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