Papers
Topics
Authors
Recent
Search
2000 character limit reached

OPPO: An Ontology for Describing Fine-Grained Data Practices in Privacy Policies of Online Social Networks

Published 27 Sep 2023 in cs.CR | (2309.15971v1)

Abstract: Privacy policies outline the data practices of Online Social Networks (OSN) to comply with privacy regulations such as the EU-GDPR and CCPA. Several ontologies for modeling privacy regulations, policies, and compliance have emerged in recent years. However, they are limited in various ways: (1) they specifically model what is required of privacy policies according to one specific privacy regulation such as GDPR; (2) they provide taxonomies of concepts but are not sufficiently axiomatized to afford automated reasoning with them; and (3) they do not model data practices of privacy policies in sufficient detail to allow assessing the transparency of policies. This paper presents an OWL Ontology for Privacy Policies of OSNs, OPPO, that aims to fill these gaps by formalizing detailed data practices from OSNS' privacy policies. OPPO is grounded in BFO, IAO, OMRSE, and OBI, and its design is guided by the use case of representing and reasoning over the content of OSNs' privacy policies and evaluating policies' transparency in greater detail.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (25)
  1. F. H. Cate, The limits of notice and choice, IEEE Security & Privacy 8 (2010) 59–62.
  2. A. M. McDonald, L. F. Cranor, The cost of reading privacy policies, Isjlp 4 (2008) 543.
  3. Automating the extraction of rights and obligations for regulatory compliance, in: International Conference on Conceptual Modeling, Springer, 2008, pp. 154–168.
  4. A systematic review of transformation approaches between user requirements and analysis models, RE 16 (2011).
  5. Pronto: privacy ontology for legal reasoning, in: International Conference on Electronic Government and the Information Systems Perspective, Springer, 2018, pp. 139–152.
  6. Creating a vocabulary for data privacy, in: Proceedings of the OTM 2019 Confederated Intern. Conf., Springer, 2019, pp. 714–730.
  7. PrivOnto: A semantic framework for the analysis of privacy policies, Semantic Web 9 (2018) 185–203.
  8. GDPR compliance made easier: the BPR4GDPR project, ARIS2 - Advanced Research on Information Systems Security 1 (2021) 5–23.
  9. Compliance through informed consent: Semantic based consent permission and data management model., PrivOn@ ISWC 1951 (2017) 1–16.
  10. Methontology: from ontological art towards ontological engineering, in: Proceedings of the Ontological Engineering AAAI-97 Spring Symposium Series, AAAI, 1997.
  11. IAO-Intel: an ontology of information artifacts in the intelligence domain (2013).
  12. The ontology for biomedical investigations, PloS one 11 (2016) e0154556.
  13. The ontology of medically related social entities: recent developments, Journal of Biomedical Semantics 7 (2016) 1–4.
  14. HermiT: an OWL 2 reasoner, Journal of Automated Reasoning 53 (2014) 245–269.
  15. M. Grüninger, M. S. Fox, The role of competency questions in enterprise engineering, in: IFIP WG5.7 Workshop on Benchmarking – Theory and Practice, Trondheim, Norway, Springer, 1994, pp. 22–31.
  16. An ontology for the south african protection of personal information act, in: Proceedings of the 19th European Conf. on Cyber Warfare and Security, Virtual Conf.  University of Chester, UK, 2020, pp. 158–166.
  17. B. Esteves, V. Rodríguez-Doncel, Analysis of ontologies and policy languages to represent information flows in GDPR, Semantic Web (2022) 1–35.
  18. Consent through the lens of semantics: State of the art survey and best practices, Semantic Web (2021 (Preprint)).
  19. A scalable consent, transparency and compliance architecture, in: European Semantic Web Conference, Springer, 2018, pp. 131–136.
  20. R. Ianella, Open digital rights language (ODRL), Open Content Licensing: Cultivating the Creative Commons (2007).
  21. LegalRuleML: Design principles and foundations, in: Reasoning Web International Summer School, Springer, 2015, pp. 151–188.
  22. H.-P. Lam, M. Hashmi, Enabling reasoning with LegalRuleML, Theory and Practice of Logic Programming 19 (2019) 1–26.
  23. Time Ontology in OWL, 2006. URL: http://www.w3.org/TR/owl-time.
  24. PHIN: a privacy protected heterogeneous IoT network, in: Intern. Conf. on Research Challenges in Information Science, Springer, 2021, pp. 124–141.
  25. OOPS! (OntOlogy Pitfall Scanner!): An On-line Tool for Ontology Evaluation, International Journal on Semantic Web and Information Systems (IJSWIS) 10 (2014) 7–34.
Citations (2)
View on Semantic Scholar

Summary

No one has generated a summary of this paper yet.

Sign Up to Summarize

Paper to Video (Beta)

No one has generated a video about this paper yet.

Sign Up to Generate All Videos Subscribe on YouTube

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Sign Up to Generate

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Generate Now

Continue Learning

We haven't generated follow-up questions for this paper yet.

Generate Now

Collections

Sign up for free to add this paper to one or more collections.

Sign Up