Abstract
We present results on a quantitative analysis of publications in the NLP domain on collecting, publishing and availability of research data. We find that a wide range of publications rely on data crawled from the web, but few give details on how potentially sensitive data was treated. Additionally, we find that while links to repositories of data are given, they often do not work even a short time after publication. We put together several suggestions on how to improve this situation based on publications from the NLP domain, but also other research areas.- Anthology ID:
- W17-1603
- Volume:
- Proceedings of the First ACL Workshop on Ethics in Natural Language Processing
- Month:
- April
- Year:
- 2017
- Address:
- Valencia, Spain
- Editors:
- Dirk Hovy, Shannon Spruit, Margaret Mitchell, Emily M. Bender, Michael Strube, Hanna Wallach
- Venue:
- EthNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 23–29
- Language:
- URL:
- https://aclanthology.org/W17-1603
- DOI:
- 10.18653/v1/W17-1603
- Cite (ACL):
- Margot Mieskes. 2017. A Quantitative Study of Data in the NLP community. In Proceedings of the First ACL Workshop on Ethics in Natural Language Processing, pages 23–29, Valencia, Spain. Association for Computational Linguistics.
- Cite (Informal):
- A Quantitative Study of Data in the NLP community (Mieskes, EthNLP 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/W17-1603.pdf