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Implementing Informed Consent with Knowledge Graphs

Part of the Lecture Notes in Computer Science book series (LNISA,volume 12739)


The GDPR legislation has brought to light one’s rights and has highlighted the importance of consent, which has caused a major shift in how data processing and sharing are handled. Data sharing has been a popular research topic for many years, however, a unified solution for the transparent implementation of consent, in compliance with GDPR that could be used as a standard, has not been presented yet. This research proposes a solution for implementing informed consent for sensor data sharing in compliance with GDPR with semantic technology, namely knowledge graphs. The main objectives are to model the life cycle of informed consent (i.e. the request, comprehension, decision and use of consent) with knowledge graphs so that it is easily interpretable by machines, and to graphically visualise it to individuals in order to raise legal awareness of what it means to consent and the implications that follow.


  • Knowledge graph
  • Knowledge graph visualisation
  • GDPR
  • Informed consent
  • Sensor data
  • Data sharing
  • Legal comprehension

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  • DOI: 10.1007/978-3-030-80418-3_28
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This research is supported by the smashHit project funded under Horizon 2020 (grant 871477) and CampaNeo project funded by FFG (grant 873839). The main supervisor of this thesis is Assoc. Prof. Dr. Anna Fensel. I would like to thank Antonio Roa Valverde, Christof Bless, Lukas Dötlinger, Manuel Penz, Markus Reiter, Michael Kaltschmid, Petraq Nako, Stephanie Widauer, Sven Rasmusen for their support in the CampaNeo project.

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Correspondence to Anelia Kurteva .

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Kurteva, A. (2021). Implementing Informed Consent with Knowledge Graphs. In: , et al. The Semantic Web: ESWC 2021 Satellite Events. ESWC 2021. Lecture Notes in Computer Science(), vol 12739. Springer, Cham.

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