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

Yan TangVUB STAR lab

1st Nov. 2005

Overviews

• Introduction and Backgrounds

• Law and Privacy Ontology Construct

• Privacy Ontology Capture Methodology

• Discussion and Future Work

• Conclusion

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.

2. Privacy Ontology Construct

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

2.2. Principle Meta-Ontology

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.

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

3. Privacy Ontology Capture Methodology

Formulate VisionStatement

Conduct Feasibility study

ProjectManagement

Preparation and Scoping

Domain ConceptualizationApplication Specification

Construct lexon and

meta-lexon layer

Construct commitment

layer

Meta-lexons are still under extraction

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

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.