license: cc-by-4.0
language:
- en
size_categories:
- 10B<n<100B
pretty_name: Scientific Openly-Licensed Publications - Text
Scientific Openly-Licensed Publications
This repository contains companion material for the following publication:
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
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
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 license.