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--- |
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license: cc-by-4.0 |
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language: |
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- en |
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size_categories: |
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- 10B<n<100B |
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pretty_name: Scientific Openly-Licensed Publications - Text |
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--- |
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# Scientific Openly-Licensed Publications |
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This repository contains companion material for the following [publication](https://openaccess.thecvf.com/content/WACV2024/papers/Tarsi_SciOL_and_MuLMS-Img_Introducing_a_Large-Scale_Multimodal_Scientific_Dataset_and_WACV_2024_paper.pdf): |
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> Tim Tarsi, Heike Adel, Jan Hendrik Metzen, Dan Zhang, Matteo Finco, Annemarie Friedrich. **SciOL and MuLMS-Img: Introducing A Large-Scale Multimodal Scientific Dataset and Models for Image-Text Tasks in the Scientific Domain.** WACV 2024. |
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Please cite this paper if using the dataset, and direct any questions regarding the dataset |
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to [Tim Tarsi](mailto:tim.tarsi@gmail.com) |
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## Summary |
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Scientific Openly-Licensed Publications (SciOL) is the largest openly-licensed pre-training corpus for multimodal models in the scientific domain, covering multiple sciences including materials science, physics, and computer science. It consists of over 2.7M scientific scientific publications converted into semi-structured data. SciOL contains over 14 Billion tokens of extracted and structured text. |
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**Note: This repository only contains the textual data of SciOL. For the figures and captions see:** |
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[SciOL-CI](https://huggingface.co/datasets/Timbrt/SciOL-CI) |
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## Data Format |
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We provide the annotations of our dataset in the JSON format. Files are grouped and compressed as zip files. We provide a basic index to find annotations by DOI, PMID or DOAJ id and keywords. |
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## Annotation Schema |
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Annotations are structured as in the following schema: |
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``` |
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{ |
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"$schema": "http://json-schema.org/draft-07/schema#", |
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"type": "object", |
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"properties": { |
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"doi": { |
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"type": "string" |
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}, |
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"keywords": { |
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"type": "array", |
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"items": { |
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"type": "string" |
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} |
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}, |
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"license": { |
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"type": "string" |
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}, |
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"article": { |
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"type": "object", |
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"properties": { |
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"title": { |
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"type": "string" |
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}, |
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"authors": { |
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"type": "array", |
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"items": { |
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"type": "string" |
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} |
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}, |
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"abstract": { |
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"type": "string" |
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}, |
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"body_text": { |
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"type": "string" |
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}, |
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"bibliography": { |
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"type": "string" |
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} |
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} |
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} |
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} |
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} |
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``` |
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## Citation |
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If you use our dataset in your scientific, please cite our paper: |
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``` |
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@InProceedings{Tarsi_2024_WACV, |
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author = {Tarsi, Tim and Adel, Heike and Metzen, Jan Hendrik and Zhang, Dan and Finco, Matteo and Friedrich, Annemarie}, |
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title = {SciOL and MuLMS-Img: Introducing a Large-Scale Multimodal Scientific Dataset and Models for Image-Text Tasks in the Scientific Domain}, |
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booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)}, |
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month = {January}, |
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year = {2024}, |
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pages = {4560-4571} |
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} |
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``` |
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## License |
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The SciOL corpus is released under the [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) license. |
