Enhancing Trust in Inter-Organisational Data Sharing: Levels of Assurance for Data Trustworthiness

Florian Zimmer, Janosch Haber, Mayuko Kaneko

2025

Abstract

With data increasingly acknowledged as a valuable asset, much effort has been put into investigating inter-organisational data sharing to unlock the value of previously unused data. Hence, research has identified mutual trust between actors as essential prerequisite for successful data sharing activities. However, existing research oftentimes focuses on trust from a data provider perspective only. Our work, therefore, highlights the unbalanced view of trust and addresses trust barriers from a data consumer perspective. Investigating trust on a data level, i.e. the assessment and assurance of data trustworthiness, we found that existing solutions focused on data trustworthiness do not meet the domain requirements of inter-organisational data sharing. This paper addresses this shortcoming by proposing a new artifact called Levels of Assurance for Data Trustworthiness (Data LoA) based on a design science research approach. Data LoA provides an overarching, standardised framework to assure data trustworthiness in inter-organisational data sharing. Our research suggests that the adoption of this artifact would lead to an increase of data consumer trust. Still, being a first iteration artifact, Data LoA requires further design efforts before it can be deployed.

Paper Citation

in Harvard Style

Zimmer F., Haber J. and Kaneko M. (2025). Enhancing Trust in Inter-Organisational Data Sharing: Levels of Assurance for Data Trustworthiness. In Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-758-0, SciTePress, pages 339-346. DOI: 10.5220/0013461800003967

in Bibtex Style

@conference{data25,
author={Florian Zimmer and Janosch Haber and Mayuko Kaneko},
title={Enhancing Trust in Inter-Organisational Data Sharing: Levels of Assurance for Data Trustworthiness},
booktitle={Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2025},
pages={339-346},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013461800003967},
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 - Enhancing Trust in Inter-Organisational Data Sharing: Levels of Assurance for Data Trustworthiness
SN - 978-989-758-758-0
AU - Zimmer F.
AU - Haber J.
AU - Kaneko M.
PY - 2025
SP - 339
EP - 346
DO - 10.5220/0013461800003967
PB - SciTePress