Towards Semantic Data Management Plans for Efficient Review Processing and Automation
Jana Martínková, Marek Suchánek
2024
Abstract
In recent times, Data Management Planning has become increasingly crucial. Effective practices in data management ensure more precise data collection, secure storage, proper handling, and utilization beyond the primary project. However, existing DMPs often suffer from complex structures that impede accessibility for humans and machines. This project aims to address these challenges by converting DMPs into formats that are both machine-actionable and human-readable. Leveraging established DMP templates and relevant ontologies, our methodology involves analyzing diverse approaches to achieve this dual functionality. We assess machine-actionability through comparative evaluations using AI and NLP tools. Furthermore, we identify gaps in ontologies, laying the groundwork for future enhancements in this critical area of research.
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in Harvard Style
Martínková J. and Suchánek M. (2024). Towards Semantic Data Management Plans for Efficient Review Processing and Automation. In Proceedings of the 13th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-707-8, SciTePress, pages 543-550. DOI: 10.5220/0012837900003756
in Bibtex Style
@conference{data24,
author={Jana Martínková and Marek Suchánek},
title={Towards Semantic Data Management Plans for Efficient Review Processing and Automation},
booktitle={Proceedings of the 13th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2024},
pages={543-550},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012837900003756},
isbn={978-989-758-707-8},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 13th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - Towards Semantic Data Management Plans for Efficient Review Processing and Automation
SN - 978-989-758-707-8
AU - Martínková J.
AU - Suchánek M.
PY - 2024
SP - 543
EP - 550
DO - 10.5220/0012837900003756
PB - SciTePress