README.md

---
license: cc-by-4.0
language:
- en
tags:
  - earth-science
  - named-entity-recognition
  - natural-language-processing
  - agentic-ai
  - multimodal
  - scientific-workflows
pretty_name: Open Earth Science (OES) via NLP Dataset
---
## Dataset Summary
**Toward Open Earth Science as Fast and Accessible as Natural Language**

This dataset was curated to accompany the EO-via-NLP [code](https://github.com/NASA-IMPACT/EO-via-NLP) and the following paper:

> Ellis, M., Gurung, I., Ramasubramanian, M., & Ramachandran, R. (2025).  
> *Toward Open Earth Science as Fast and Accessible as Natural Language*.  
> [arXiv:2505.15690](https://arxiv.org/abs/2505.15690)

## Supported Tasks 

This dataset was primarily designed for:

- Named Entity Recognition (NER) in earth science contexts.

## Languages

- English (`en`)

## Intended Use

This dataset is intended for:
* Research in agentic AI systems for Earth science,
* Development of natural language interfaces for software and scientific workflows,
* Benchmarking multimodal and task-oriented models in geoscience contexts.

## How to Use

See the EO-via-NLP [repository](https://github.com/NASA-IMPACT/EO-via-NLP).

To simply load it:
```python
from datasets import load_dataset

dataset = load_dataset("nasa-impact/EO-via-NLP")
```

## Dataset Creation

This dataset was curated by the authors of the accompanying paper and EO-via-NLP codebase. All annotations and selections were created by humans.


## License

This dataset is licensed under **Creative Commons Attribution 4.0 International (CC BY 4.0)**.

You are free to:

- **Share** — copy and redistribute the material in any medium or format  
- **Adapt** — remix, transform, and build upon the material for any purpose, even commercially  

**Attribution is required.** Please cite the following work when using this dataset:

## Citation

### BibTeX

```bibtex
@article{ellis2025oes,
  title={Toward Open Earth Science as Fast and Accessible as Natural Language},
  author={Ellis, Marquita and Gurung, Iksha and Ramasubramanian, Muthukumaran and Ramachandran, Rahul},
  journal={arXiv preprint arXiv:2505.15690},
  year={2025},
  month={May},
  doi={10.48550/arXiv.2505.15690},
  url={https://arxiv.org/abs/2505.15690}
}
```

Please open an issue or discussion on the Hugging Face dataset page, or contact the authors via the corresponding author listed in the paper.

## README Attribution
This README was drafted with assistance from Copilot, an AI system based on GPT-4, to ensure clarity, consistency, and alignment with Hugging Face dataset standards.