The smashHitCore Ontology for GDPR-Compliant Sensor Data Sharing in Smart Cities

Author:

Kurteva Anelia12ORCID,Chhetri Tek Raj1ORCID,Tauqeer Amar13ORCID,Hilscher Rainer14ORCID,Fensel Anna135ORCID,Nagorny Kevin6,Correia Ana6ORCID,Zilverberg Albert6ORCID,Schestakov Stefan7,Funke Thorben7ORCID,Demidova Elena8

Affiliation:

1. Semantic Technology Institute (STI), Department of Computer Science, Universität Innsbruck, 6020 Innsbruck, Austria

2. Industrial Design Engineering, Delft University of Technology, 2628 CE Delft, The Netherlands

3. Consumption and Healthy Lifestyles Chair Group, Wageningen University & Research, 6706 KN Wageningen, The Netherlands

4. RTI International, Research Triangle Park, NC 27709, USA

5. Wageningen Data Competence Center, Wageningen University & Research, 6708 PB Wageningen, The Netherlands

6. Institut für Angewandte Systemtechnik Bremen GmbH (ATB), 28359 Bremen, Germany

7. L3S Research Center, Leibniz University Hannover, 30167 Hannover, Germany

8. Data Science and Intelligent Systems Group (DSIS), University of Bonn, 53115 Bonn, Germany

Abstract

The adoption of the General Data Protection Regulation (GDPR) has resulted in a significant shift in how the data of European Union citizens is handled. A variety of data sharing challenges in scenarios such as smart cities have arisen, especially when attempting to semantically represent GDPR legal bases, such as consent, contracts and the data types and specific sources related to them. Most of the existing ontologies that model GDPR focus mainly on consent. In order to represent other GDPR bases, such as contracts, multiple ontologies need to be simultaneously reused and combined, which can result in inconsistent and conflicting knowledge representation. To address this challenge, we present the smashHitCore ontology. smashHitCore provides a unified and coherent model for both consent and contracts, as well as the sensor data and data processing associated with them. The ontology was developed in response to real-world sensor data sharing use cases in the insurance and smart city domains. The ontology has been successfully utilised to enable GDPR-complaint data sharing in a connected car for insurance use cases and in a city feedback system as part of a smart city use case.

Funder

smashHit H2020 project

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference79 articles.

1. (2016). Regulation (EU) 2016/679 of the European Parliamentand of the Council of 27 April 2016 on the Protectionof Natural Persons with Regard to the Processing of Per-Sonal Data and on the Free Movement of Such Data, Andrepealing Directive 95/46/EC (General Data ProtectionRegulation), Official Journal of the European Union, L119.

2. Information Commissioner’s Office (ICO) (2021, November 11). Lawful Basis for Processing. Available online: https://ico.org.uk/media/for-organisations/guide-to-the-general-data-protection-regulation-gdpr/lawful-basis-for-processing-1-0.pdf.

3. Freire, N., and de Valk, S. (2019, January 9–12). Automated interpretability of linked data ontologies: An evaluation within the cultural heritage domain. Proceedings of the IEEE International Conference on Big Data (Big Data), Los Angeles, CA, USA.

4. The smashHit Project (2023, March 10). Public Report D1.3 Public Innovation Concept. Available online: https://www.smashhit.eu/wp-content/uploads/2021/03/smashHit_D1.3_Public_Innovation_Concept_v100.pdf.

5. An ontology-based approach to support for requirements traceability in agile development;Murtazina;Procedia Comput. Sci.,2019

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