SPIRIT: A Semantic Transparency and Compliance Stack

Westphal, Patrick and Fernandez Garcia, Javier David ORCID: https://orcid.org/0000-0002-2683-827X and Kirrane, Sabrina ORCID: https://orcid.org/0000-0002-6955-7718 and Lehmann, Jens (2018) SPIRIT: A Semantic Transparency and Compliance Stack. In: Proceedings of the 14th International Conference on Semantic Systems. CEUR Workshop Proceedings, Aachen. p. 1.

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Abstract

The European General Data Protection Regulation (GDPR) sets new precedents for the processing of personal data. In this paper, we propose an architecture that provides an automated means to enable transparency with respect to personal data processing and sharing transactions and compliance checking with respect to data subject usage policies and GDPR legislative obligations.

Item Type: Book Section
Additional Information: This work is partially funded by the European Union's Horizon 2020 research and innovation programme grants 732194 (QROWD) and 731601 (SPECIAL), and the Austrian Research Promotion Agency (FFG) grant 861213 (CitySPIN)
Divisions: Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft > Polleres
Version of the Document: Accepted for Publication
Variance from Published Version: Minor
Depositing User: Javier David Fernandez Garcia
Date Deposited: 06 Sep 2018 07:53
Last Modified: 04 Dec 2019 10:04
FIDES Link: https://bach.wu.ac.at/d/research/results/86868/
URI: https://epub.wu.ac.at/id/eprint/6491

References

J. Lehmann, G. Sejdiu, L. Bühmann, P. Westphal, C. Stadler, I. Ermilov, S. Bin, N. Chakraborty, M. Saleem, and A.-C. N. Ngomo. Distributed semantic analytics using the sansa stack. In Proceedings of the 16th International Semantic Web Conference (ISWC). Springer, 2017.

M. Nickel, K. Murphy, V. Tresp, and E. Gabrilovich. A review of relational machine learning for knowledge graphs. Proceedings of the IEEE, 104(1):11-33, 2016.

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