Modelling Judicial Professional Knowledge: A Case Study

Chapter
First Online:
Part of the Law, Governance and Technology Series book series (LGTS, volume 3)

Abstract

This chapter is devoted to the description of the development process of an ontology that represents professional judicial knowledge, including a detailed description of the knowledge acquisition step, conceptualization and formalization steps, and the different ontology evaluation techniques explored. A socio-legal approach to the development of legal ontologies is proposed.

Keywords

Knowledge Acquisition Judicial Decision Civil Procedure Legal Expert Judicial Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References

  1. Arnaiz, A., R. López, and M. Loredo. 2005. Organización judicial. Vol. 1, Colección de esquemas de derecho procesal. Valencia: Tirant Lo Blanc.Google Scholar
  2. Baader, F. 2003. Description logic terminology, Chapter Appendix 1, 485–495. Cambridge: Cambridge University Press.Google Scholar
  3. Benjamins, V. R., P. Casanovas, J. Breuker, and A. Gangemi, eds. 2005b. Law and the Semantic Web. Legal ontologies, methodologies, legal information retrieval, and applications [outcome of the Workshop on Legal Ontologies and Web-Based Legal Information Management, June 28, 2003, Edinburgh, UK & International Seminar on Law and the Semantic Web, November 20–21, 2003, Barcelona, Spain]. Lecture notes in computer science, Vol. 3369, Berlin/Heidelberg: Springer.Google Scholar
  4. Brank, J., M. Grobelnik, and D. Mladenic. 2005. D.1.6.1 ontology evaluation. SEKT IST-2003-506826 Deliverable 1.6.1, SEKT, EU-IST Project Jozef Stefan Institute.Google Scholar
  5. Breuker, J., R. Hoekstra, A. Boer, K. van den Berg, R. Rubino, G. Sartor, M. Palmirani, A. Wyner, and T. Bench-Capon. 2007. OWL ontology of basic legal concepts (LKIF-core). Deliverable 1.4 D.1.4, ESTRELLA project (IST-2004-027655).Google Scholar
  6. Bromme, R., and H. Tillema. 1995. Fusing experience and theory: The structure of professional knowledge. Learning and Instruction 5:261–267.CrossRefGoogle Scholar
  7. Brooke, J. 1996. Sus: A ‘quick and dirty’ usability scale. In Usability evaluation in industry, ed. P. W. Jordan, B. Thomas, I. L. McClelland, and B. Weerdmeester. Chapter 21, 189–194. London: Taylor & Francis.Google Scholar
  8. Bylander, T., and B. Chandrasekaran. 1987. Generic tasks for knowledge-based reasoning: The “right” level of abstraction for knowledge acquisition. International Journal of Man-Machine Studies 26(2):231–243.CrossRefGoogle Scholar
  9. Casanovas, P., N. Casellas, C. Tempich, D. Vrandečić, and R. Benjamins. 2007a, June. OPJK and DILIGENT: Ontology modeling in a distributed environment. Artificial Intelligence and Law 15(2):171–186. Presented at the ICAIL 2005 LOAIT Workshop.Google Scholar
  10. Casanovas, P., M. Poblet, N. Casellas, J. Contreras, R. Benjamins, and M. Blázquez. 2005b. Supporting newly-appointed judges: A legal knowledge management case study. Journal of Knowledge Management 9(5):7–27.CrossRefGoogle Scholar
  11. Dean, M., G. Schreiber, S. Bechhofer, F. van Harmelen, J. Hendler, I. Horrocks, D. L. McGuinness, P. F. Patel-Schneider, and L. A. Stein. 2004, February. OWL web ontology language reference. W3c recommendation 10 February 2004, World Wide Web Consortium (W3C). http://www.w3.org/TR/owl-ref/
  12. Ding, L., and T. Finin. 2006. Characterizing the Semantic Web on the web. In The Semantic Web – ISWC 2006, 5th International Semantic Web Conference, ISWC 2006, Athens, GA, USA, November 5–9, 2006, Proceedings, ed. I.F. Cruz, S. Decker, D. Allemang, C. Preist, D. Schwabe, P. Mika, M. Uschold and L. Aroyo. Lecture notes in computer science, Vol. 4273, 242–257. Berlin/Heidelberg: Springer.Google Scholar
  13. Euzenat, J., T. L. Bach, J. Barrasa, and et al. 2004. State of the art on ontology alignment. Deliverable KWEB/2004/D2.2.3/v1.2, Knowledge Web.Google Scholar
  14. Guarino, N., and C. Welty. 2002. Evaluating ontological decisions with OntoClean. Communications of the ACM 45(2):61–65.CrossRefGoogle Scholar
  15. Hartmann, J., P. Spyns, A. Gibboin, D. Maynard, R. Cuel, M. C. Suárez-Figueroa, and Y. Sure. 2005, January. D.1.2.3. methods for ontology evaluation. Deliverable IST-2004-507482 KWEB D.1.2.3., EU-IST Network of Excellence (NoE) Knowledge Web Consortium.Google Scholar
  16. Hoekstra, R., J. Breuker, M. D. Bello, and A. Boer. 2007. The LKIF core ontology of basic legal concepts. In Proceedings of the Workshop on Legal Ontologies and Artificial Intelligence Techniques (LOAIT 2007) at the International Conference on AI and Law (ICAIL’07), Stanford, June 4, ed. P. Casanovas, M. A. Biasiotti, E. Francesconi, and M. T. Sagri, 43–63.Google Scholar
  17. Milton, N. 2007. Knowledge acquisition in practice. A step-by-step guide. Decision engineering. London: Springer.Google Scholar
  18. Moliner, M. 2000. Diccionario de Uso del Español. Gredos.Google Scholar
  19. Montero-Aroca, J., J. Gómez-Colomer, A. Montón-Redondo, and S. Barona-Vilar. 2005a. Derecho jurisdiccional I. Parte general. 14th ed. Valencia: Tirant Lo Blanch.Google Scholar
  20. Montero-Aroca, J., J. Gómez-Colomer, A. Montón-Redondo, and S. Barona-Vilar. 2007. Derecho jurisdiccional III. Proceso penal. 15th ed. Valencia: Tirant Lo Blanch.Google Scholar
  21. Montero-Aroca, J., J. Gómez-Colomer, A. Montón-Redondo, and S. Barona-Vilar. 2008. Derecho jurisdiccional I. Parte general. 16th ed. Valencia: Tirant Lo Blanch.Google Scholar
  22. Moreno-Catena, V., and V. Cortés-Domínguez. 2008. Derecho procesal penal. 3 a ed. Valencia: Tirant lo Blanch.Google Scholar
  23. Nielsen, J. 1994a. Usability engineering. San Francisco: Morgan Kaufmann.Google Scholar
  24. Nielsen, J. 2005. How to conduct a heuristic evaluation. Web. (Available at 01-10-2008).Google Scholar
  25. Noy, N. F., and D. L. McGuinness. 2001. Ontology development 101: A guide to creating your first ontology. Technical Report SMI-2001-0880, Stanford University School of Medicine.Google Scholar
  26. Pinto, H. S., C. Tempich, and S. Staab. 2004. DILIGENT: Towards a fine-grained methodology for distributed, loosely-controlled and evolving engineering of ontologies. In Proceedings of the 16th European Conference on Artificial Intelligence (ECAI 2004), August 22–27 Valencia, ed. R. L. de Mantaras and L. Saitta, 393–397. Amsterdam: IOS Press.Google Scholar
  27. Rector, A., N. Drummond, M. Horridge, J. Rogers, H. Knublauch, R. Stevens, H. Wang, and C. Wroe. 2004. OWL pizzas: Practical experience of teaching OWL-DL: Common errors & common patterns. In Proceedings of the 14th International Conference on Knowledge Engineering and Knowledge Management EKAW’04, 5–8 October, Whittlebury Hall, Northamptonshire.Google Scholar
  28. Schreiber, G., H. Akkermans, A. Anjewierden, R. de Hoog, N. Shadbolt, W. V. de Velde, and B. Wielinga. 1999. Knowledge engineering and management. The commonKADS methodology. Cambridge: A Bradford Book. MIT Press.Google Scholar
  29. Sclano, F., and P. Velardi. 2007. Termextractor: A web application to learn the common terminology of interest groups and research communities. In Proceedings of the 9th Conference on Terminology and Artificial Intelligence (TIA’07), Sophia Antinopolis, October.Google Scholar
  30. Sevcenko, M. 2003. Online presentation of an upper ontology. In Proceedings of Znalosti 2003, Ostrava, February 19–21.Google Scholar
  31. Smith, M. K., C. Welty, and D. L. McGuinness. 2004, February. OWL ontology web language guide. Recomendation, World Wide Web Consortium (W3C).Google Scholar
  32. Sowa, J. F. 1995. Top-level ontological categories. International Journal of Human-Computer Studies43(5–6):669–685.CrossRefGoogle Scholar
  33. Sure, Y. 2003. Methodology, tools and case studies for ontology based knowledge management. Ph.D. thesis, Fakultät für Wirschaftwissenschaften der Universität Fridericiana zu Karlsruhe.Google Scholar
  34. Tartir, S., I. B. Arpinar, M. Moore, A. P. Sheth, and B. Aleman-Meza. 2005. OntoQA: Metric-based ontology quality analysis. In Proceedings of IEEE Workshop on Knowledge Acquisition from Distributed, Autonomous, Semantically Heterogeneous Data and Knowledge Sources, Houston, November 27.Google Scholar
  35. Tempich, C., H. S. Pinto, Y. Sure, D. Vrandečić, N. Casellas, and P. Casanovas. 2007. Ontology engineering with DILIGENT. A legal case study. In Trends in legal knowledge: The Semantic Web and the rebulaiton of electronic social systems. Papers form the B-4 Workshop on Artificial Intelligence and Law, May 25th–27th of the XXII World Congress of Philosophy of Law and Social Philosophy IVR’05, Granadam, ed. P. Casanovas, P. Noriega, D. Bourcière, and F. Galindo, 269–277. Florence: European Press Academic Publishing.Google Scholar
  36. Terziev, I., A. Kiryakov, and D. Manov. 2005. D1.8.1 base upper-level ontology (bulo) guidance. SEKT IST-2003-506826 Deliverable 1.8.1, SEKT, EU-IST Project IST-2003-506826, Ontotext Lab, Sirma Group (Bulgaria).Google Scholar
  37. Velardi, P., R. Navigli, A. Cucchiarelli, and F. Neri. 2005, July. Evaluation of OntoLearn, a methodology for automatic population of domain ontologies. In Ontology learning from text: Methods, evaluation and applications, ed. P. Buitelaar, P. Cimiano, and B. Magnini. Frontiers in artificial intelligence and applications series, Vol. 123. Amsterdam: IOS Press.Google Scholar
  38. Wang, T., B. Parsia, and J. Hendler. 2006. A survey of the web ontology landscape. In Proceedings of the International Semantic Web Conference (ISWC’06), Athens, November 5, 158–171.Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Institute of Law and TechnologyUniversitat Autònoma de BarcelonaBellaterraSpain

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