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README.md

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+---
+pretty_name: Data Provenance Initiative
+language:
+- en
+---
+# 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 | Tokens | Times seen during training|
+------------|----------|--------|---------------------------|
+| 3,508,518 |      3.4 |   5.1B |                        6x |
+
+## 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](TODO link)). 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 "filtered" version of the Data Provenance Initiative dataset. If you are looking for the raw version, you can find it [here](https://huggingface.co/datasets/common-pile/data_provenance_initiative).
+
+## 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}
+}
+```