A Review on the Use of Large Language Models in the Context of Open Government Data

Daniel Staegemann, Christian Haertel, Matthias Pohl, Klaus Turowski

2025

Abstract

Since ChatGPT was released to the public in 2022, large language models (LLM) have drawn enormous interest from academia and industry alike. Their ability to create complex texts based on provided inputs positions them to be a valuable tool in many domains. Moreover, since some time, many governments want to increase transparency and enable the offering of new services by making their data freely available. However, these efforts towards Open Government Data (OGD) face various challenges with many being related to the question how the data can be made easily findable and accessible. To address this issue, the use of LLMs appears to be a promising solution. To provide an overview of the corresponding research, in this work, the results of a structured literature review on the use of LLMs in the context of OGD are presented. Hereby, numerous application areas as well as challenges were identified and described, providing researchers and practitioners alike with a synoptic overview of the domain.

Paper Citation

in Harvard Style

Staegemann D., Haertel C., Pohl M. and Turowski K. (2025). A Review on the Use of Large Language Models in the Context of Open Government Data. In Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-758-0, SciTePress, pages 651-660. DOI: 10.5220/0013642600003967

in Bibtex Style

@conference{data25,
author={Daniel Staegemann and Christian Haertel and Matthias Pohl and Klaus Turowski},
title={A Review on the Use of Large Language Models in the Context of Open Government Data},
booktitle={Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2025},
pages={651-660},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013642600003967},
isbn={978-989-758-758-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - A Review on the Use of Large Language Models in the Context of Open Government Data
SN - 978-989-758-758-0
AU - Staegemann D.
AU - Haertel C.
AU - Pohl M.
AU - Turowski K.
PY - 2025
SP - 651
EP - 660
DO - 10.5220/0013642600003967
PB - SciTePress