--- license: cc-by-4.0 language: - en size_categories: - 10B 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. Please cite this paper if using the dataset, and direct any questions regarding the dataset to [Tim Tarsi](mailto:tim.tarsi@gmail.com) ## Summary 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. **Note: This repository only contains the textual data of SciOL. For the figures and captions see:** [SciOL-CI](https://huggingface.co/datasets/Timbrt/SciOL-CI) ## Data Format 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. ## Annotation Schema Annotations are structured as in the following schema: ``` { "$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": { "doi": { "type": "string" }, "keywords": { "type": "array", "items": { "type": "string" } }, "license": { "type": "string" }, "article": { "type": "object", "properties": { "title": { "type": "string" }, "authors": { "type": "array", "items": { "type": "string" } }, "abstract": { "type": "string" }, "body_text": { "type": "string" }, "bibliography": { "type": "string" } } } } } ``` ## Citation If you use our dataset in your scientific, please cite our paper: ``` TBD ``` ## License The SciOL corpus is released under the [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) license.