data_provenance_initiative

# Data Provenance Initiative

## Description
The [Data Provenance Initiative](https://www.dataprovenance.org) is a digital library of supervised datasets that have been manually annotated with their source and license information [ 104, 107 ].
We leverage their tooling to filter HuggingFace datasets, based on a range of criteria, including their licenses.
Specifically, we filter the data according to these criteria: contains English language or code data, the text is not model-generated, the dataset’s audit yielded a open license and the original sources of the data are only from recognized public domain sources.
Per-document license information is available in the `license` entry of the `metadata` field of each example.
Code for collecting, processing, and preparing this dataset is available in the [common-pile GitHub repo](https://github.com/r-three/common-pile).

## Dataset Statistics
| Documents | UTF-8 GB |
|-----------|----------|
| 9,688,211 | 7 |

## License Issues
While we aim to produce datasets with completely accurate licensing information, license laundering and inaccurate metadata can cause us to erroneously assign the incorrect license to some documents (for further discussion of this limitation, please see [our paper](https://huggingface.co/papers/2506.05209)). If you believe you have found an instance of incorrect licensing in this dataset, please [start a discussion](https://github.com/r-three/common-pile/discussions/new) on this repository.

## Other Versions
This is the "raw" version of the Data Provenance Initiative dataset. If you are looking for the filtered version used to train [Comma v0.1](https://huggingface.co/common-pile/comma-v0.1), you can find it [here](https://huggingface.co/datasets/common-pile/data_provenance_initiative_filtered).

## Citation
If you use this dataset, please cite:
```bibtex
@article{kandpal2025common,
title={{The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text}},
author={Nikhil Kandpal and Brian Lester and Colin Raffel and Sebastian Majstorovic and Stella Biderman and Baber Abbasi and Luca Soldaini and Enrico Shippole and A. Feder Cooper and Aviya Skowron and Shayne Longpre and Lintang Sutawika and Alon Albalak and Zhenlin Xu and Guilherme Penedo and Loubna Ben and Elie Bakouch and John David and Honglu Fan and Dashiell Stander and Guangyu Song and Aaron Gokaslan and John Kirchenbauer and Tom Goldstein and Brian R and Bhavya Kailkhura and Tyler Murray},
journal={arXiv preprint},
year={2025}
}
```

# 数据溯源倡议（Data Provenance Initiative）

## 描述
[数据溯源倡议（Data Provenance Initiative）](https://www.dataprovenance.org) 是一个收录经人工标注来源与许可信息的监督式数据集的数字图书馆[104, 107]。
我们依托其工具链，基于包括许可协议在内的多项筛选标准对HuggingFace数据集进行筛选。
具体而言，我们按照以下标准过滤数据：包含英文文本或代码数据、文本非模型生成、该数据集经审核后采用开放许可协议，且数据原始来源仅来自公认的公共领域资源。
单文档许可信息可在每条样本的`metadata`字段下的`license`条目获取。
用于收集、处理与整理本数据集的代码可在[common-pile GitHub 仓库](https://github.com/r-three/common-pile)中获取。

## 数据集统计信息
| 文档数量 | UTF-8 吉字节 |
|-----------|----------|
| 9,688,211 | 7 |

## 许可相关问题
尽管我们致力于打造许可信息完全准确的数据集，但许可洗白与元数据不准确问题可能导致我们错误地为部分文档分配了错误的许可协议（关于此局限性的进一步讨论，请参阅[我们的论文](https://huggingface.co/papers/2506.05209)）。若您认为本数据集存在许可信息错误的情况，请在本仓库[发起讨论](https://github.com/r-three/common-pile/discussions/new)。

## 其他版本
此为数据溯源倡议数据集的“原始”版本。若您正在寻找用于训练[Comma v0.1](https://huggingface.co/common-pile/comma-v0.1)的过滤版数据集，可在此处获取：[common-pile/data_provenance_initiative_filtered](https://huggingface.co/datasets/common-pile/data_provenance_initiative_filtered)。

## 引用
若您使用本数据集，请引用如下文献：
bibtex
@article{kandpal2025common,
title={{The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text}},
author={Nikhil Kandpal and Brian Lester and Colin Raffel and Sebastian Majstorovic and Stella Biderman and Baber Abbasi and Luca Soldaini and Enrico Shippole and A. Feder Cooper and Aviya Skowron and Shayne Longpre and Lintang Sutawika and Alon Albalak and Zhenlin Xu and Guilherme Penedo and Loubna Ben and Elie Bakouch and John David and Honglu Fan and Dashiell Stander and Guangyu Song and Aaron Gokaslan and John Kirchenbauer and Tom Goldstein and Brian R and Bhavya Kailkhura and Tyler Murray},
journal={arXiv preprint},
year={2025}
}