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---
license: cc0-1.0
task_categories:
- text-generation
- token-classification
language:
- en
tags:
- funding
- research-funding
- scholarly-metadata
- preprints
- arxiv
size_categories:
- 1K<n<10K
configs:
- config_name: default
data_files:
- split: train
path: train.jsonl
- split: test
path: test.jsonl
---
# Preprint Funding Metadata
A dataset of funding statements extracted from arXiv preprints with structured funder and award annotations.
## Dataset Description
This dataset contains funding statements from scientific preprints along with manually annotated structured metadata identifying funders and their associated awards.
### Data Fields
- `doi`: The DOI of the preprint (e.g., "10.48550/arxiv.2303.07677")
- `funding_statement`: The raw funding acknowledgment text extracted from the paper
- `funders`: Array of funder objects containing:
- `funder_name`: Name of the funding organization (may be null if only a program is mentioned)
- `awards`: Array of award objects containing:
- `funding_scheme`: Array of funding program/scheme names
- `award_ids`: Array of grant/award identifiers
- `award_title`: Array of award titles (if available)
### Dataset Statistics
| Split | Examples |
|-------|----------|
| Train | 1,388 |
| Test | 347 |
## Usage
```python
from datasets import load_dataset
dataset = load_dataset("cometadata/preprint-funding")
# Access train split
train_data = dataset["train"]
# Access test split
test_data = dataset["test"]
```
## Example
```json
{
"doi": "10.48550/arxiv.2303.07677",
"funding_statement": "This work was supported in part by the Key R&D Program of Zhejiang under Grant 2022C01018, and by the National Natural Science Foundation of China under Grants U21B2001 and 61973273.",
"funders": [
{
"funder_name": null,
"awards": [
{
"funding_scheme": ["Key R&D Program of Zhejiang"],
"award_ids": ["2022C01018"],
"award_title": []
}
]
},
{
"funder_name": "National Natural Science Foundation of China",
"awards": [
{
"funding_scheme": [],
"award_ids": ["U21B2001", "61973273"],
"award_title": []
}
]
}
]
}
```
## License
This dataset is released under CC0 (Public Domain).
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