Enabling Trusted Data Sharing in Data Spaces: PROTON - A Privacy-by-Design Approach to Data Products

Laura Schuiki, Christoph Stach, Corinna Giebler, Eva Hoos, Bernhard Mitschang

2025

Abstract

In the current era of data-driven innovation, the value of data can be significantly enhanced by facilitating its dissemination. In this context, the data mesh concept has gained popularity in recent years. Data Mesh includes domain experts who design so-called data products. It is imperative that all parties involved have trust in these data products. This applies in particular to data subjects who share their data, data owners who create the data products, and data consumers who use them. To establish such trust, privacy approaches are key. Due to the decentralized and distributed nature of data mesh, however, traditional privacy strategies cannot be applied. To address this issue, we present PROTON, a concept that facilitates the handling of PRivacy-cOmpliant daTa prOducts by desigN. PROTON is based on three pillars: a comprehensive description model for privacy requirements, an extended creation process that adheres to these requirements when compiling data products, and a refined access process for verifying compliance prior to data sharing. The practical applicability of PROTON is illustrated by means of a real-world application scenario that has been devised in collaboration with domain experts from our industry partner.

Paper Citation

in Harvard Style

Schuiki L., Stach C., Giebler C., Hoos E. and Mitschang B. (2025). Enabling Trusted Data Sharing in Data Spaces: PROTON - A Privacy-by-Design Approach to Data Products. In Proceedings of the 11th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP; ISBN 978-989-758-735-1, SciTePress, pages 95-106. DOI: 10.5220/0013372900003899

in Bibtex Style

@conference{icissp25,
author={Laura Schuiki and Christoph Stach and Corinna Giebler and Eva Hoos and Bernhard Mitschang},
title={Enabling Trusted Data Sharing in Data Spaces: PROTON - A Privacy-by-Design Approach to Data Products},
booktitle={Proceedings of the 11th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP},
year={2025},
pages={95-106},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013372900003899},
isbn={978-989-758-735-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP
TI - Enabling Trusted Data Sharing in Data Spaces: PROTON - A Privacy-by-Design Approach to Data Products
SN - 978-989-758-735-1
AU - Schuiki L.
AU - Stach C.
AU - Giebler C.
AU - Hoos E.
AU - Mitschang B.
PY - 2025
SP - 95
EP - 106
DO - 10.5220/0013372900003899
PB - SciTePress