metadata

pretty_name: HALvest-Geometric
license: cc-by-4.0
configs:
  - config_name: en
    data_files: en/*.gz
  - config_name: fr
    data_files: fr/*.gz
language:
  - en
  - fr
size_categories:
  - 100K<n<1M
task_categories:
  - text-generation
  - fill-mask
task_ids:
  - language-modeling
  - masked-language-modeling
tags:
  - academia
  - research
  - graph
annotations_creators:
  - no-annotation
multilinguality:
  - multilingual
source_datasets:
  - HALvest

HALvest-Geometric

Citation Network of Open Scientific Papers Harvested from HAL

Dataset Description

Repository: GitHub

Dataset Summary

overview:

This dataset is comprised of fulltext from open papers found on Hyper Articles en Ligne (HAL). Our dump is mostly english/french but gather papers written in 34 languages across 13 domains.

You can download the dataset using Hugging Face datasets:

from datasets import load_dataset

ds = load_dataset("Madjakul/HALvest-Geometric", "en")

Details

TODO

Languages

ISO-639	Language	# Documents	# mT5 Tokens
en	English	442,892	7,606,895,258
fr	French	193,437	8,728,722,255

Graph

TODO

Considerations for Using the Data

The corpus is extracted from the HAL's open archive which distributes scientific publications following open access principles. The corpus is made up of both creative commons licensed and copyrighted documents (distribution authorized on HAL by the publisher). This must be considered prior to using this dataset for any purpose, other than training deep learning models, data mining etc. We do not own any of the text from which these data has been extracted.

Citation

TODO

Dataset Copyright

The licence terms for HALvest strictly follows the one from HAL. Please refer to the below license when using this dataset.

HAL license

@misc{kulumba2024harvestingtextualstructureddata,
      title={Harvesting Textual and Structured Data from the HAL Publication Repository}, 
      author={Francis Kulumba and Wissam Antoun and Guillaume Vimont and Laurent Romary},
      year={2024},
      eprint={2407.20595},
      archivePrefix={arXiv},
      primaryClass={cs.DL},
      url={https://arxiv.org/abs/2407.20595}, 
}