# CatholicCorpus Roadmap

This document tracks planned releases and their deliverables. Each version has a definition of done. No dates are committed; milestones ship when they are ready.

## v0.9.0 (Current Release)

The foundation release. Contains the full raw corpus, download scripts, provenance sidecars, and a text extraction pipeline (code only, not yet run).

**What shipped:**

- 67,772 content files across 16 collections (35.9 GB)
- Idempotent download scripts for all collections (`download_script.py` per task)
- Provenance tracking via `_source.json` sidecars
- Shared `archive_helpers.py` with circuit breaker, lending-restricted detection, and rate limiting
- `build_manifest.py` for regenerating `master_manifest.json` and `SUMMARY.md`
- Text extraction pipeline in `text_extraction/` (code included for review, not yet executed)
- Project website at catholiccorpus.org
- Full documentation: README, LICENSE_NOTES, ACKNOWLEDGMENTS, BACKLOG, LENDING_RESTRICTED

**Known gaps at this version:**

- No token counts
- No deduplication analysis
- No formal `_source.json` schema documentation
- No Hugging Face dataset card
- No DOI or BibTeX citation
- Text extraction not yet run
- Patrologia Graeca vols 16 and 86 missing (98.8% coverage without them)
- 23 lending-restricted archive.org items not downloadable

## v1.0.0 (Foundation Release)

The first release suitable for citation in academic work. Adds the measurements and metadata that ML/NLP researchers expect.

**Definition of done:**

- [ ] Token counts computed and published (overall, per-collection, per-language)
- [ ] Per-source composition breakdown (files, bytes, tokens, languages, formats)
- [ ] `_source.json` schema formally documented (JSON Schema + human-readable docs)
- [ ] `dataset.json` machine-readable manifest at corpus root
- [ ] Hugging Face dataset card following community conventions
- [ ] BibTeX citation block and DOI (via Zenodo)
- [ ] `CITATION.cff` at repo root
- [ ] LIMITATIONS.md published
- [ ] Corpus published on Hugging Face Datasets

## v1.1.0 (Extracted Text Layer)

A pre-built plain-text layer so researchers do not need to run extraction themselves.

**Definition of done:**

- [ ] `text_extraction/extract_text.py` run across all tasks
- [ ] Per-document extraction quality scores (character count, empty-page ratio)
- [ ] Extracted text published as a separate Hugging Face configuration
- [ ] Quality report comparing extracted text to source (sample-based)

## v1.2.0 (OCR Enhancement)

Re-OCR of low-quality archive.org scans to improve text extraction for older PDFs.

**Definition of done:**

- [ ] OCR engine selected (Tesseract 5 with theological dictionaries, or a vision-language model)
- [ ] Low-quality PDFs identified (by extraction quality scores from v1.1)
- [ ] Re-OCR applied and quality comparison report published
- [ ] Updated extracted text layer published

## v1.3.0 (Critical-Edition Partnerships)

Higher-quality source texts where licensing permits.

**Definition of done:**

- [ ] Outreach to Leonine Commission, Brepols-adjacent OA texts, CUA Press, Editiones Cistercienses
- [ ] At least one critical-edition source integrated
- [ ] Provenance tracking updated for new sources

## v2.0.0 (Aligned Bilingual Editions)

Sentence-aligned Latin-English (and Greek-English) parallel texts for translation NLP research.

**Definition of done:**

- [ ] Alignment methodology documented
- [ ] At least three authors aligned (Aquinas, Bonaventure, Augustine)
- [ ] Published as a separate Hugging Face configuration

## How to Contribute

See [CONTRIBUTING.md](CONTRIBUTING.md) for how to propose new collections, flag OCR errors, or contribute to any of these milestones.