French-PD-Newspapers

# 🇫🇷 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) and in cooperation with OpenLLMFrance. 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.

## License
The entire collection is in the public domain everywhere. This means that the patrimonial rights of each individual or collective rightholders have expired.

The French National Library claims additional rights in its terms of use and restrict commercial use: "La réutilisation commerciale de ces contenus est payante et fait l'objet d'une licence. Est entendue par réutilisation commerciale la revente de contenus sous forme de produits élaborés ou de fourniture de service ou toute autre réutilisation des contenus générant directement des revenus."

There has been a debate for years in Europe over the definition of public domain and the possibility to restrict its use. Since 2019, the EU Copyright Directive state that "Member States shall provide that, when the term of protection of a work of visual art has expired, any material resulting from an act of reproduction of that work is not subject to copyright or related rights, unless the material resulting from that act of reproduction is original in the sense that it is the author's own intellectual creation."(art. 14)

## 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.

## Acknowledgements
The corpus was stored and processed with the generous support of Scaleway. It was built up with the support and concerted efforts of the state start-up LANGU:IA (start-up d’Etat), supported by the French Ministry of Culture and DINUM, as part of the prefiguration of the service offering of the Alliance for Language technologies EDIC (ALT-EDIC).

Corpus collection has been largely facilitated thanks to the open science LLM community insights and cooperation (Occiglot, Eleuther AI, Allen AI).

<div style="text-align: center;">
<img src="https://github.com/mch-dd/datasetlogo/blob/main/scaleway.jpeg?raw=true" style="width: 33%; margin: 0 auto; display: inline-block;"/>
<img src="https://github.com/mch-dd/datasetlogo/blob/main/ministere.png?raw=true" style="width: 33%; margin: 0 auto; display: inline-block;"/>
<img src="https://github.com/mch-dd/datasetlogo/blob/main/occiglot.jpg?raw=true" style="width: 33%; margin: 0 auto; display: inline-block;"/>
</div>

# 🇫🇷 法国公有领域报纸集 🇫🇷

**French-Public Domain-Newspapers**（简称**French-PD-Newpapers**）是旨在收录全部公有领域法国报纸与期刊的大型数据集。

本数据集最初由皮埃尔-卡尔·朗格莱（Pierre-Carl Langlais）编纂，其基础是贝努瓦·德·库松（Benoît de Courson）、本杰明·阿祖莱（Benjamin Azoulay）为**Gallicagram**（<https://shiny.ens-paris-saclay.fr/app/gallicagram>）遴选的大型语料库，并与OpenLLMFrance合作完成。Gallicagram是一款领先的文化分析工具，支持对法语及其他语言的大型文化遗产数据集进行词汇与n元语法（ngram）检索。

## 内容
截至2024年1月，本数据集收录来自法国国家图书馆（Bibliothèque nationale de France，简称BNF）旗下Gallica平台的近300万份独特报纸与期刊刊次，总词量达69763525347词。每个Parquet文件包含随机选取的数千条出版物的完整文本，若有可用元数据则附带部分核心字段（如Gallica编号、标题、作者、词数等）。依托BNF API可便捷扩展元数据维度。

本次初始汇编得以完成，得益于法国国家图书馆的开放数据计划，以及欧盟2019年《版权指令》（第14条）对文化遗产作品公有领域身份的明确固化。

本数据集的构成符合法国公有领域判定标准：集体作品需满足出版时长超过70年，个人作品需满足作者逝世超过70年。依据欧盟更短版权保护期的相关规则，本数据集在全球范围内均属于公有领域。

## 应用场景
本数据集的核心用途为大规模文化分析项目。同时，本数据集旨在为大语言模型（Large Language Model，简称LLM）的训练提供更多开放可用文本。数据集文本可用于模型训练，且为确保可复现性，可无限制地重新发布。

## 授权许可
本数据集整体在全球范围内均属于公有领域，即所有个人或集体权利持有人的著作财产权均已过期。但法国国家图书馆在其使用条款中声明了额外权利，并对商业使用作出限制："商业复用这些内容需付费并获得授权许可。商业复用是指将内容以加工产品形式转售、提供服务，或以其他直接产生收益的方式复用内容。"

欧洲学界与业界多年来围绕公有领域的定义以及限制其使用的可能性存在争议。自2019年起，欧盟《版权指令》第14条明确规定："各成员国应确保，当视觉艺术作品的保护期届满后，对该作品进行复制所产生的任何材料不受版权或相关权利约束，除非该复制材料具有独创性，属于作者的原创智力成果。"

## 未来发展规划
本数据集并非一次性项目，后续将在三大方向持续优化：
* 修正文本中的自动转录错误：所有文本均通过光学字符识别（Optical Character Recognition，简称OCR）软件自动转录而来。原始文件自2000年代中期起历经多年数字化，部分文档存在识别误差。未来版本将致力于对原始文本重新进行OCR处理，或借助实验性大语言模型（LLM）完成部分OCR错误修正。
* 优化原始文本的结构与排版呈现：部分原始文档内容（如页眉、页码等）可能不适合大规模分析或模型训练，且部分复杂文档结构（如表格、多栏布局）的格式效果欠佳。通过在原始PDF文件上应用前沿的布局识别模型（如COLAF），可实现大幅优化。
* 扩充数据集收录范围，纳入更多文化遗产馆藏，尤其是来自Hathi Trust、Internet Archive与Google Books的资源。

## 致谢
本语料库的存储与处理得到了Scaleway的慷慨支持。数据集的构建依托于国有初创企业LANGU:IA的协作与投入，该企业由法国文化部与DINUM支持，是语言技术联盟EDIC（ALT-EDIC）服务预研项目的组成部分。此外，开放科学领域的大语言模型社区（包括Occiglot、Eleuther AI与Allen AI）提供的见解与合作，极大推动了语料库的收集工作。

<div style="text-align: center;">
<img src="https://github.com/mch-dd/datasetlogo/blob/main/scaleway.jpeg?raw=true" style="width: 33%; margin: 0 auto; display: inline-block;"/>
<img src="https://github.com/mch-dd/datasetlogo/blob/main/ministere.png?raw=true" style="width: 33%; margin: 0 auto; display: inline-block;"/>
<img src="https://github.com/mch-dd/datasetlogo/blob/main/occiglot.jpg?raw=true" style="width: 33%; margin: 0 auto; display: inline-block;"/>
</div>