README.md

---
license: cc0-1.0
task_categories:
- text-generation
language:
- fr
tags:
- ocr
pretty_name: French-Public Domain-Newspapers
---
**French-Public Domain-Newspapers** or **French-PD-Newpapers** is a large collection aiming to agregate all the French newspapers and periodicals in the public domain. 

The collection has been originally compiled by Pierre-Carl Langlais, on the basis of a large corpus curated by Benoît de Courson, Benjamin Azoulay for [Gallicagram](https://shiny.ens-paris-saclay.fr/app/gallicagram). Gallicagram is leading cultural analytics project giving access to word and ngram search on very large cultural heritage datasets in French and other languages.

## Content
As of January 2024, the collection contains nearly three million unique newspaper and periodical editions (69,763,525,347 words) from the French National Library (Gallica). Each parquet file has the full text of a few thousand selected at random and, when available, a few core metadatas (Gallica id, title, author, word counts…). The metadata can be easily expanded thanks to the BNF API.

This initial agregation was made possible thanks to the open data program of the French National Library and the consolidation of public domain status for cultural heritage works in the EU with the 2019 Copyright Directive (art. 14)

The composition of the dataset adheres to the French criteria for public domain of collective works (any publication older than 70 years ago) and individual works (any publication with an author dead for more than 70 years). In agreement with the shorter term rules, the dataset is in the public domain everywhere.

## Uses
The primary use of the collection is for cultural analytics project on a wide scale.

The collection also aims to expand the availability of open works for the training of Large Language Models. The text can be used for model training and republished without restriction for reproducibility purposes.

## Future developments
This dataset is not a one time work but will continue to evolve significantly on two directions:
* Correction of computer generated errors in the text. All the texts have been transcribed automatically through the use of Optical Character Recognition (OCR) software. The original files have been digitized over a long time period (since the mid-2000s) and some documents should be. Future versions will strive either to re-OCRize the original text or use experimental LLM models for partial OCR correction.
* Enhancement of the structure/editorial presentation of the original text. Some parts of the original documents are likely unwanted for large scale analysis or model training (header, page count…). Additionally, some advanced document structures like tables or multi-column layout are unlikely to be well formatted. Major enhancements could be experted through applying new SOTA layout recognition models (like COLAF) on the original PDF files.
* Expansion of the collection to other cultural heritage holdings, especially coming from Hathi Trust, Internet Archive and Google Books.