README.md

---
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).