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Judicial Support Systems: Ideas for a Privacy Ontology-Based Case Analyzer

Judicial Support Systems: Ideas for a Privacy Ontology-Based Case Analyzer. Yan Tang VUB STAR lab 1 st Nov. 2005. Overviews. Introduction and Backgrounds Law and Privacy Ontology Construct Privacy Ontology Capture Methodology Discussion and Future Work Conclusion.

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Judicial Support Systems: Ideas for a Privacy Ontology-Based Case Analyzer

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  1. Judicial Support Systems: Ideas for a Privacy Ontology-Based Case Analyzer Yan Tang VUB STAR lab 1st Nov. 2005

  2. Overviews • Introduction and Backgrounds • Law and Privacy Ontology Construct • Privacy Ontology Capture Methodology • Discussion and Future Work • Conclusion

  3. 1. Introduction and Backgrounds • Privacy • Definition: • The ability of an individual or group to prevent information about themselves from becoming known to people • Mainly deal with Data Privacy • Privacy Applications: • Identity Management Systems • Location Based Services Application • E-Science • E-Shopping • Etc.

  4. 2. Privacy Ontology Construct

  5. 2.1. Privacy Ontology in DOGMA framework • DOGMA (Developing Ontology-Guided Mediation for Agents) • Ontology Base • Sets of lexons that represent the entities of conceptualization • <γ, t1, r1, r2, t2>, where γ∈Γ, t1, t1∈T, r1, r2∈R. • Ontological Commitments • contain the lexon selection, organization, instantiation and system context • Privacy Ontology • Fact Lexons • Privacy Directives Commitments

  6. 2.2. Principle Meta-Ontology

  7. 2.3. Application Design • Application based on privacy ontology: • E-court • E-science • E-shopping • E-government • Disaster management systems • Etc. • Applications based on legal ontology • Law retrieval systems • Legal abstractor • Case parser • Etc.

  8. 2.3.1 Applications based on legal ontology • Legal Abstractor (under research) • An expert system to help to extract cases into facts • Privacy Case Describing Standards (still under research in PRIME) • Classical manual way: abstraction by lawyers • Case Parser (under research) • A tool still under developing • Functionality: • General: to parse a case into sets of lexons and commitment relations with the aide of legal abstractor (an intelligent agent) • More details: need to be discovered • Law retrieval system • A system uses legal abstractor and case parser

  9. 3. Privacy Ontology Capture Methodology Project Management Formulate Vision Statement Conduct Feasibility study Preparation and Scoping Application Specification Domain Conceptualization Meta-lexons are still under extraction Construct lexon and meta-lexon layer Construct commitment layer

  10. 4. Conclusion, Discussion and Future Work • Conclusion: • how to build legal ontology in DOGMA framework and how it can be contributed into many sub legal domains, such as privacy. • Future work: • Legal ontology capture methodology (might be based on Privacy ontology capture methodology) • Case parser (an assistant tool, or expert system) development • Abstractor (an assistant tool, or expert system) development • Rule based and case based reasoning will be visualized in meta-lexon Layer (or commitment layer if it’s possible) • XML based law retrieval system development • Discussion: • How to build a general legal ontology • How to mount legal applications based on legal ontology • How to capture legal ontology from lawyers in different law domains • How to bring privacy ontology as an entrance to the whole legal ontology realm

  11. References • 1. T. R. Gruber. A translation approach to portable ontologies. Knowledge Acquisition, 5(2):199-220, 1993. • 2. T. R. Gruber. Toward principles for the design of ontologies used for knowledge sharing. Workshop on Formal Ontology, Padova, Italy, 1992. • 3. P. De Leenheer & A. De Moor, Context-driven Disambiguation in Ontology Elicitation. In, P. Shvaiko & J. Euzenat,(eds.), Context and Ontologies: Theory, Practice and Applications, AAAI Technical Report WS-05-01, pp. 17 - 24, AAAI Press, 2005. • 4. R. Meersman, Ontologies and Databases: More than a Fleeting Resemblance. In, A.D'Atri & M. Missikoff,(eds.), OES/SEO 2001 Rome Workshop, Luiss Pub., 2001. • 5. J. A. Holland, J. S. Webb, Learning legal rules, Oxford university press, 2003 • 6. L. Woolf, substantial change of civil court rule in UK, 1999. • 7. R. Summers, Two types of substantive reasons: the core of a theory of common law justification, 63 Cornell Law Review 707, 1978. • 8. P. Verheyden, J. De Bo & R. Meersman, Semantically unlocking database content through ontology-based mediation . In, C. Bussler, V. Tannen & I. Fundulaki,(eds.), Semantic Web and Databases: 2nd Int’l Workshop, SWDB 2004, Toronto ,Canada, 2004, Revised Selected Papers, LNCS 3372, pp. 109 - 126, Springer Verlag, 2005. • 9. P. De Leenheer & R. Meersman, Towards a formal foundation of DOGMA Ontology Part I: Lexon Base and Concept Definition Server. Technical Report STAR-2005-06, STARLab, Brussel, 2005. • 10. J. Dumortier, C. Goemans, Roadmap for European legal research in privacy and identity management, K.U. Leuven, 2003. • 11. T. A. Halpin. Information Modeling and Relational Databases: From Conceptual Analysis to Logical Design, San Francisco, California, Morgan Kaufman Publishers, 2001. • 12. A. Valente, J. Breuker, Ontology: the missing link between legal theory and AI & law, in A. Soeteman (eds.), Legal knowledge based systems JURIX 94: Lelystad, Koninklijke Vermande, 1994. • 13. B. Niblett, computer science and law: an introductory discussion, in B. Niblett (ed.), computer science and law: an advanced course, Cambridge: Cambridge University Press, 1980.

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