ColPri: Towards a Collaborative Privacy Knowledge Management Ontology for the Internet of Things

Toumia, Amri; Szoniecky, Samuel; Saleh, Imad

doi:10.1109/fmec49853.2020.9144927

Cited by 12 publications

(11 citation statements)

References 13 publications

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“…DPV 27 also models consent (from privacy perspective), but the main focus if on GDPR as a whole. PrOnto [19], ColPri [22] and LloPY [25] are developed from a privacy perspective and view consent as an attribute that helps preserve data privacy. Similarly, CDMM 18 models consent as an entity within a privacy policy and further allows for the capturing of data provenance.…”

Section: Discussionmentioning

confidence: 99%

“…The competency questions were derived by following GDPR requirements for informed consent and already existing sets of competency questions such as the one of GConsent 17 . The ontologies reviewed in this section are CDMM 18 , GConsent 17 , PrOnto [19], LloPY [20], BPR4GDPR 23 , SPL and SPLog [21], ColPri [22] and DPV 27 .…”

Section: Semantic Models For Consentmentioning

confidence: 99%

“…The ontology is utilised by the IoT Resource Management Module of the system presented in [25], which performs data anonymisation, noise addition, etc. In addition to modelling, consent for privacy preservation in smart devices, LloPY reuses the Semantic Sensor Network ontology (SSN) 22 , which provides more detailed privacy properties for sensors and their observations. The ontology can be used when one needs to model consent for sensor data sharing in the IoT, for example, in smart cities.…”

Section: Legal Complaint Ontology To Preserve Privacy For the Internet Of Things (Llopy)mentioning

confidence: 99%

“…Both vocabularies can be used for modelling consent as system logs in privacy policies in order to restrict data usage and processing [21]. The ColPri ontology [22], developed with OWL 6 and using the SKOS 26 vocabulary, aims to provide a collaborative IoT knowledge base which enables one to configure privacy policies. Consent is viewed from a privacy perspective and is modeled as a privacy attribute with two states: given and ungiven.…”

Section: Special's Usage Policy Language (Spl)mentioning

confidence: 99%

“…The SPECIAL vocabularies [21] could be reused as both are aimed at GDPR compliance checking and model consent as an artefact of privacy policies. Other ontologies built for GDPR compliance checking are LloPy [25], ColPri [22] and DPV 27 . Section 1 (Tables 1, 2, 3), Section 3.1, Section 3.4…”

Section: Request Of Consentmentioning

confidence: 99%

See 4 more Smart Citations

Consent through the lens of semantics: State of the art survey and best practices

Kurteva

Chhetri

Pandit

et al. 2024

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The acceptance of the GDPR legislation in 2018 started a new technological shift towards achieving transparency. GDPR put focus on the concept of informed consent applicable for data processing, which led to an increase of the responsibilities regarding data sharing for both end users and companies. This paper presents a literature survey of existing solutions that use semantic technology for implementing consent. The main focus is on ontologies, how they are used for consent representation and for consent management in combination with other technologies such as blockchain. We also focus on visualisation solutions aimed at improving individuals’ consent comprehension. Finally, based on the overviewed state of the art we propose best practices for consent implementation.

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Section: Discussionmentioning

confidence: 99%

Section: Semantic Models For Consentmentioning

confidence: 99%

Section: Legal Complaint Ontology To Preserve Privacy For the Internet Of Things (Llopy)mentioning

confidence: 99%

Section: Special's Usage Policy Language (Spl)mentioning

confidence: 99%

Section: Request Of Consentmentioning

confidence: 99%

See 3 more Smart Citations

Consent through the lens of semantics: State of the art survey and best practices

Kurteva

Chhetri

Pandit

et al. 2024

View full text Add to dashboard Cite

show abstract

Leveraging a Microservice Architecture, Access Control and Interoperability Patterns to Manage Privacy-Related User Consents

Lamari,

Benblidia,

Tibermacine

et al. 2024

Lecture Notes in Computer Science

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Review of the theory, principles, and design requirements of human-centric Internet of Things (IoT)

Ystgaard¹,

Atzori

Palma³

et al. 2023

J Ambient Intell Human Comput

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The rapid evolution of Internet of Things (IoT) technologies, with ever more profound implications for humans and societies, has triggered visions and initiatives to re-align the Next-Generation IoT with what works for humans and humanity first. However, despite the increased push towards “human-centric” IoT, it is still poorly understood what “human-centric” actually means in this context, how it is interpreted and embedded into the design, by whom, and for which purposes. To address these questions, we conducted a systematic literature review (N = 84) on the theory, principles, and design requirements of human-centric IoT. A key observation is that, despite the recent increase in research on humane perspectives for IoT, “human-centredness” often still seems to be used primarily as a label and overarching paradigm, not leading to a profound change in the underlying practices. We found no shared understanding of what “human-centric” implies in this context or common agreement on which principles human-centric IoT should be built upon. Furthermore, our analysis confirmed the predominance of technology-oriented fields, with a traditional approach towards user involvement and limited involvement of other disciplines. Overall, our findings point towards an apparent discrepancy between how contributions are positioned and framed (“human-centric”), the practices and assumptions they are based on, and their actual impact and ability to orient existing efforts towards genuine human-centric outcomes and key values. Based on the results, we formulate directions for future research aimed at building a more human-centric and empowering IoT.

show abstract

ColPri: Towards a Collaborative Privacy Knowledge Management Ontology for the Internet of Things

Cited by 12 publications

References 13 publications

Consent through the lens of semantics: State of the art survey and best practices

Consent through the lens of semantics: State of the art survey and best practices

Leveraging a Microservice Architecture, Access Control and Interoperability Patterns to Manage Privacy-Related User Consents

Review of the theory, principles, and design requirements of human-centric Internet of Things (IoT)

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