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User consent modeling for ensuring transparency and compliance in smart cities

  • Javier D. FernándezEmail author
  • Marta Sabou
  • Sabrina Kirrane
  • Elmar Kiesling
  • Fajar J. Ekaputra
  • Amr Azzam
  • Rigo Wenning
original Article

Abstract

Smart city infrastructures such as transportation and energy networks are evolving into so-called cyber physical social systems (CPSSs), which collect and leverage citizens’ data in order to adapt services to citizens’ needs. The privacy implications of such systems are, however, significant and need to be addressed. Current systems either try to escape the privacy challenge via anonymization or use very rigid, hard-coded workflows that have been agreed with a data protection authority. In the case of the latter, there is a severe impact on data quality and richness, whereas in the former, only these hard-coded flows are permitted resulting in diminished functionality and potential. We address these limitations via user modeling in terms of investigating how to model and semantically represent user consent, preferences, and data usage policies that will guide the processing of said data in the data lake. Data protection is a horizontal field and consequently very wide. Therefore, we focus on a concrete setting where we extend the domain-agnostic SPECIAL policy language for a smart mobility use case supplied by Vienna’s largest utility provider. To that end, (1) we create an extension of SPECIAL in terms of a core CPSS vocabulary that lowers the semantic gap between the domain agnostic terms of SPECIAL and the vocabulary of the use case; (2) we propose a workflow that supports defining domain-specific vocabularies for complex CPSSs; and (3) show that these two contributions allow successfully achieving the goals of our setting.

Keywords

Cyber physical (social) systems Smart mobility User consent modeling Privacy GDPR Linked data 

Notes

Funding information

This work has been supported by the European Union’s Horizon 2020 research and innovation programme under grant 731601 (SPECIAL) and by the Austrian Research Promotion Agency (FFG): grant no. 861213 (CitySPIN).

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2020

Authors and Affiliations

  1. 1.Vienna University of Economics and BusinessViennaAustria
  2. 2.Technical University of ViennaViennaAustria
  3. 3.Christian Doppler Laboratory for Security and Quality Improvement in the Production System Lifecycle (CDL-SQI)Technical University of ViennaViennaAustria
  4. 4.ERCIM/W3CSophia-AntipolisFrance

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