The smashHitCore ontology for GDPR-compliant sensor data sharing in smart cities
The smashHitCore ontology for GDPR-compliant sensor data sharing in smart cities
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.
consent, contracts, data sharing, GDPR, insurance, ontology, sensors, smart cities
Kurteva, Anelia
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Chhetri, Tek Raj
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Tauqeer, Amar
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Hilscher, Rainer
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Fensel, Anna
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Nagorny, Kevin
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Correia, Ana
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Zilverberg, Albert
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Schestakov, Stefan
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Funke, Thorben
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Demidova, Elena
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6 July 2023
Kurteva, Anelia
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Chhetri, Tek Raj
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Tauqeer, Amar
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Hilscher, Rainer
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Fensel, Anna
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Nagorny, Kevin
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Correia, Ana
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Zilverberg, Albert
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Schestakov, Stefan
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Funke, Thorben
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Demidova, Elena
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Kurteva, Anelia, Chhetri, Tek Raj, Tauqeer, Amar, Hilscher, Rainer, Fensel, Anna, Nagorny, Kevin, Correia, Ana, Zilverberg, Albert, Schestakov, Stefan, Funke, Thorben and Demidova, Elena
(2023)
The smashHitCore ontology for GDPR-compliant sensor data sharing in smart cities.
Sensors, 23 (13), [6188].
(doi:10.3390/s23136188).
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.
Text
sensors-23-06188-v2
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More information
Accepted/In Press date: 3 July 2023
Published date: 6 July 2023
Additional Information:
Funding Information:
This work is part of the smashHit H2020 project (grant agreement No 871477). We thank Volkswagen AG, LexisNexis Risk Solutions, Forum Virium Helsinki, Infotripla and ATOS for providing the use cases and supporting our collaboration. Further, we thank the legal team from University of Hannover (LUH/IRI) for their legal advice during the ontology specification.
Publisher Copyright:
© 2023 by the authors.
Keywords:
consent, contracts, data sharing, GDPR, insurance, ontology, sensors, smart cities
Identifiers
Local EPrints ID: 481452
URI: http://eprints.soton.ac.uk/id/eprint/481452
ISSN: 1424-8220
PURE UUID: f2e518f6-db1f-4abd-bffd-cb257e265044
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Date deposited: 29 Aug 2023 16:51
Last modified: 17 Mar 2024 04:21
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Contributors
Author:
Anelia Kurteva
Author:
Tek Raj Chhetri
Author:
Amar Tauqeer
Author:
Rainer Hilscher
Author:
Anna Fensel
Author:
Kevin Nagorny
Author:
Ana Correia
Author:
Albert Zilverberg
Author:
Stefan Schestakov
Author:
Thorben Funke
Author:
Elena Demidova
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