Artificial Intelligence and Law

, Volume 15, Issue 2, pp 171–186 | Cite as

OPJK and DILIGENT: ontology modeling in a distributed environment

  • Pompeu Casanovas
  • Núria Casellas
  • Christoph Tempich
  • Denny Vrandečić
  • Richard Benjamins
Article

Abstract

In the legal domain, ontologies enjoy quite some reputation as a way to model normative knowledge about laws and jurisprudence. This paper describes the methodology followed when developing the ontology used by the second version of the prototype Iuriservice, a web-based intelligent FAQ for judicial use. This modeling methodology has had two important requirements: on the one hand, the ontology needed to be extracted from a repository of professional judicial knowledge (containing nearly 800 questions regarding daily practice). Thus, the construction of ontologies of professional judicial knowledge demanded the description of this knowledge as it is perceived by the judge. On the other hand, due to the distributiveness of the environment, there was a need for controlled discussion and traceability of the arguments used in favor or against the introduction of a concept X as part of the domain ontology. This paper presents the Ontology of Professional Judicial Knowledge (OPJK), extracted manually from the selection of relevant terms from judicial practice questions and modeled according to the DILIGENT methodology. We will show that DILIGENT has proved to be a methodology that facilitates the ontology engineering in a distributed environment, although appropriate tool support needs to be developed.

Keywords

legal ontologies methodology ontology modeling professional knowledge rhetorical structure theory 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ayuso, M., Becue, M., and et al. (2003). Jueces jóvenes en españa, 2002, análisis estadístico de las encuestas a los jueces en su primer destino (promociones 48/49 y 50). Sec-2001-2581-C02-01/02 informe interno, Consejo General del Poder Judicial.Google Scholar
  2. Benjamins V. R., Contreras J., Blázquez M., Rodrigo L., Casanovas P., Poblet M. (2004a). The sekt use legal case components: ontology and architecture. In: Gordon T. B. (eds) Legal Knowledge and Information Systems Jurix 2004. IOS Press, Amsterdam, The Netherlands, pp 69–77Google Scholar
  3. Benjamins, V. R., Contreras, J., Casanovas, P., Ayuso, M., Becue, M., Lemus, L., and Urios, C. (2004b). Ontologies of professional legal knowledge as the basis for intelligent it support for judges. Artificial Intelligence and Law (in press)Google Scholar
  4. Blázquez, M., Rodridgo, L., Casanovas, P., and Poblet, M. (2004). Legal case study – before analysis – SEKT IST-2003-506826 deliverable 10.1.1, Intelligent Software Components S.A. and Universitat Autònoma de Barcelona.Google Scholar
  5. Breuker J., Valente A., Winkels R. (2005). Use and reuse of legal ontologies in knowledge engineering and information management. Springer, London Berlin, pp 35–64Google Scholar
  6. Breuker, J. and Winkels, R. (2003). Use and reuse of legal ontologies in knowledge engineering and information management. In ICAIL03 Wks on Legal Ontologies and Web-based Information Management, Edinburgh, UK. Available at http://www.lri.jur.uva.nl/ winkels/legontICAIL2003.html.Google Scholar
  7. Casanovas, P., Casellas, N., Vallbé, J., Poblet, M., Ramos, F., Gorroñogointia, J., Contreras, J., Blázquez, M., and Benjamins, R. (2005a). Iuriservice II: Ontology development and architectural design. In Proceedings of the Internacional Conference on Artificial Intelligence and Law, ICAIL-05,AAAI-ACM, 188–195, Bologna, ItalyGoogle Scholar
  8. Casanovas P., Poblet M., Casellas N., Contreras J., Benjamins R., Blázquez M. (2005b). Supporting newly-appointed judges: a legal knowledge management case study. Journal of Knowledge Management 9(5):7–27CrossRefGoogle Scholar
  9. Casellas, N., Blázquez, M., Kiryakov, A., Casanovas, P., and Benjamins, R. (2005). OPJK into PROTON: legal domain ontology integration into an upper-level ontology. In Meersman, R., Tari, Z., Herrero, P., et al. OTM Workshops 2005, LNCS 3762, 846–855. Springer-Verlag, Berlin, HeidelbergGoogle Scholar
  10. Clancey W. J., Sachs P., Sierhus M., Hoof R. (1998). Brahms. simulating practice for work systems design. International Journal of Human-Computer Studies 49:831–865CrossRefGoogle Scholar
  11. de Moor, A. and Aakhus, M. (2003). Argumentation support: From technologies to tools. In␣Proceedings of the 8th International Working Conference on the Language-Action Perspective on Communication Modelling (LAP 2003), June 1–2 2003, Tilburg, The␣Netherlands.Google Scholar
  12. Gangemi A., Pisanelli D., Steve G. (1998). Ontology integration: Experiences with medical terminologies. In: Guarino N., (eds) Formal Ontology in Information Systems. IOS Press, Amsterdam, pp 163–178Google Scholar
  13. Gómez-Pérez, A., Fernández-López, M., and Corcho, O. (2003). Ontological Engineering. Advanced Information and Knowledge Processing. Springer.Google Scholar
  14. Gruber T. R. (1995). Toward principles for the design of ontologies used for knowledge sharing. International Journal of Human Computer Studies 43(5–6):907–928CrossRefGoogle Scholar
  15. Jarrar, M. and Meersmann, R. (2001). Practical ontologies and their interpretations in applications – the dogma experiment. Technical report, Starlab research laboratories, Brussels, Belgium. Available at http://starlab.vwb.ac.be/publications/STAR-2001-04.pdf.Google Scholar
  16. Mann W. C., Thompson S. A. (1987). Rhetorical structure theory: A theory of text organization. In: Polanyi L. (eds) The Structure of Discourse. Ablex Publishing Corporation, Norwood, N.J.Google Scholar
  17. Pinto, H. S. and Martins, J. (2001). A Methodology for Ontology Integration. In Proceedings of the First International Conference on Knowledge Capture (K-CAP2001), 131–138, ACM Press, New YorkGoogle Scholar
  18. Pinto, H. S., Tempich, C., and Staab, S. (2004). DILIGENT: towards a fine-grained methodology for distributed, loosely-controlled and evolving engineering of ontologies. In de Mantaras, R. L. and Saitta, L., (eds.), Proceedings of the 16th European Conference on Artificial Intelligence (ECAI 2004), August 22–27, 393–397, IOS Press, Valencia, SpainGoogle Scholar
  19. Poblet, M. and Casanovas, P. (2005). Recruitment, Professional Evaluation and Career of Judges and Prosecutors in Spain, 185–213. IRSIG-CNR, University of Bologna, Ed. Lo ScarabeoGoogle Scholar
  20. Potts, C. and Bruns, G. (1998). Recording the reasons for design decisions. In Proceedings of the 10th international conference on Software engineering, 418–427. IEEE Computer Society PressGoogle Scholar
  21. Sure, Y., Tempich, C., Pinto, H. S., and Staab, S. (2005). A case study in supporting distributed, loosely-controlled and evolving engineering of ontologies (DILIGENT). In Lytras, M. and Naeve, A. (eds.), Intelligent Learning Infrastructures for Knowledge Intensive Organisations: A Semantic Web Perspective, chapter 14, 357–368. Idea Group Publishing, Inc.Google Scholar
  22. Tempich, C., Pinto, S., Staab, S., and Sure, Y. (2004). A case study in supporting distributed, loosely-controlled and evolving engineering of ontologies (diligent). In Tochtermann, K. and Maurer, H. (eds.), Proceedings of the 4th International Conference on Knowledge Management (I-KNOW’04), 225–232, Graz, Austria. Journal of Universal Computer Science (J.UCS). Available at: http://www.aifb.uni-karlsruhe.de/WBS/cte/html/publications/pdf/IKNOW04_ diligent_caseStudy_final.pdf.Google Scholar
  23. Uschold, M. and King, M. (1995). Towards a methodology for building ontologies. In Proceedings of IJCAI95’s Workshop on Basic Ontological Issues in Knowledge Sharing, Montreal, CanadaGoogle Scholar
  24. Vallbé, J.-J., Martí, M. A., Fortuna, B., Jakulin, A., Mladenič, D., and Casanovas, P. (2005). Stemming and lemmatisation. Improving knowledge management through language processing techniques. In Proceedings of the B4 Workshop on Artificial intelligence and Law. IVR’05, Granada, Spain. Available at: http://www.lefis.orgGoogle Scholar
  25. Visser, P. (1998). Implicit assumptions in legal knowledge systems. In Proceedings of the 13th BILETA Conference, March, 27th-28th, Dublin, IrelandGoogle Scholar
  26. Visser, P., van Kralingen, R., and Bench-Capon, T. (1997). A method for development of legal knowledge systems. In Proceedings of International Conference in Artificial Intelligence and Law, ICAIL, Melbourne, AustraliaGoogle Scholar
  27. Winkels, R., Boer, A., and Hoekstra, R. (2002). CLIME: lessons learned in legal information serving. In Proceedings of the 15th European Conference on Artificial Intelligence (ECAI 2002), Lyon, France, 230–234, IOS Press, Amsterdam, The NetherlandsGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2007

Authors and Affiliations

  • Pompeu Casanovas
    • 1
  • Núria Casellas
    • 1
  • Christoph Tempich
    • 2
  • Denny Vrandečić
    • 2
  • Richard Benjamins
    • 3
  1. 1.Institute of Law and TechnologyUABBarcelonaSpain
  2. 2.AIFBUniversität KarlsruheKarlsruheGermany
  3. 3.iSOCO, Intelligent Software ComponentsMadridSpain

Personalised recommendations