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  license: cc-by-4.0
 
 
 
 
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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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  ---
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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:
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+
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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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+
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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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+
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+
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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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+
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+
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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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+
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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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+
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+ ## Annotation Schema
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+
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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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+
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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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+ TBD
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+
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+ ```
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+
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+ ## License
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+
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+ The SciOL corpus is released under the [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) license.