Ontological Representation of Legal Information and an Idea of Crowdsourcing for Its Filling

  • Anatolii Getman
  • Volodymyr Karasiuk
  • Yevhen Hetman
  • Oleg Shynkarov
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 836)


This article represents consideration of the creation process of legal knowledge ontology for study purposes. The peculiarities of legal information and experience of legal knowledge formalization have been scrutinized. The peculiarities of complex systems self-organization have been considered and application of these principles to legal information on the basis of four features of self-organization has been proved. It has been determined that the most reasonable way of legal knowledge description is ontology, as a basis for forming of knowledge structure. The review of existing ontologies that are used in the field of law has been carried out. Mathematical description of the knowledge base structure has been introduced. The software package has been developed for working with legal knowledge ontology. This package of programs is used by students at the Yaroslav Mudryi National Law University. The method of collective filling and editing of the knowledge base is proposed to be used as the basis of methodology for working with the knowledge base. The ontology of legal knowledge at the University has been created not only by experts but by all the users. Principles of crowdsourcing are considered as a basic technique of technological process of the ontology filling. Results of filling of this ontology by a number of users have been briefly reviewed. The legal knowledge ontology that is being created is proposed to be used for forming an individual learning style of students.


Legal information Ontology Self-organization of legal information Crowdsourcing Individual learning style 


  1. 1.
    Law of Ukraine: “On information” No. 2657-XII. In: Summaries of the Verkhovna Rada of Ukraine (VRU), 48 (1992)Google Scholar
  2. 2.
    Valkman, Yu., Stepashko, P.: Principles of constructing the ontology of intelligent modeling. In: Valkman, Yu., et al. (eds.) Proceedings of the XVI International Conference «Intellectual Information Analysis» IIA-2016, pp. 25–34, Prosvita, Kiev (2016)Google Scholar
  3. 3.
    Laszlo, E.: A Strategy for the Future: The Systems Approach to World Order. Braziller, New York (1974)Google Scholar
  4. 4.
    Smuts, J.: Holism and Evolution. The Macmillan Company, New York (1926)Google Scholar
  5. 5.
    Sun, Z., Xie, K., Anderman, L.: The role of self-regulated learning in students’ success in flipped undergraduate math courses. Internet High. Educ. 36, 41–53 (2018). Scholar
  6. 6.
    Trujillo, B.: Self-organizing legal systems: precedent and variation in bankruptcy. In: Farell, N. (ed.) Utah Law Review, vol. 2, pp. 483–562 (2004). Accessed 18 Feb 2018
  7. 7.
    Kawaguchi, K.H.: A Social Theory of International Law: International Relations As a Complex System. Brill Academic Publishers, The Netherlands (2003). Scholar
  8. 8.
    Garbarino, C.: A model of legal systems as evolutionary networks: normative complexity and self-organization of clusters of rules. Bocconi Legal Studies Research Paper No. 1601338, Milan (2010). Accessed 15 Sept 2017
  9. 9.
    Nicolis, G., Prigogine, I.: Self-organization in Nonequilibrium Systems. Wiley, New York (1977)zbMATHGoogle Scholar
  10. 10.
    Hacken, G.: Information and Self-organization: A Macroscopic Approach to Complex Systems. World, Moskow (1991)Google Scholar
  11. 11.
    Getman, A., Karasiuk, V.: A crowdsourcing approach to building a legal ontology from text. Artif. Intell. Law 22(3), 313–335 (2014)CrossRefGoogle Scholar
  12. 12.
    Naidysh, V.: Concepts of Modern Natural Science. Alpha-M, Infra-M, Moskow (2004)Google Scholar
  13. 13.
    Tuzovsky, A., Chirikov, S., Yampolsky, V.: Knowledge Management Systems (Methods and Technologies). Publishing House of Scientific and Technical Literature, Tomsk (2005)Google Scholar
  14. 14.
    Soloviev, V., Dobrov, B., Ivanov, V., Lukashevich, N.: Ontologies and thesauri. Kazan State University, Kazan (2006). Accessed 25 May 2016
  15. 15.
    Bench-Capon, T., Visser, P.: Ontologies in legal information systems; the need for explicit specifications of domain conceptualisations. In: Proceedings of the 6th International Conference on Artificial Intelligence and Law, pp. 132–141, Melbourne, Australia (1997)Google Scholar
  16. 16.
    Saravanan, M., Ravindran, B., Raman, S.: Improving legal information retrieval using an ontological framework. Artif. Intell. Law 17(2), 101–124 (2009). Scholar
  17. 17.
    Nardi, J., Falbo, R., Almeida, J.: Foundational ontologies for semantic integration in EAI: a systematic literature review. In: Douligeris, C., Polemi N., Karantjias, A., Lamersdorf, W. (eds.) Proceedings I3E 2013, pp. 238–249. (2013). Accessed 22 Mar 2018
  18. 18.
    Nguyen, V.: Ontologies and information systems: a literature survey. DSTO-TN-1002. Defence Science and Technology Organization, Edinburg, South Australia, (2011). Accessed 24 Apr 2017
  19. 19.
    Ding, Y., Foo, S.: Ontology research and development, Part 1 - A review of ontology generation. J. Inf. Sci. 28(2), (2002). Accessed 07 Mar 2014
  20. 20.
    Breuker, J., Hoekstra R.: Epistemology and ontology in core ontologies: FOLaw and LRI-Core, two core ontologies for law. In: Proceedings of the EKAW04 Workshop on Core Ontologies in Ontology Engineering, Northamptonshire, UK, pp. 15–27. Accessed 01 Mar 2014
  21. 21.
    Gangemi, A., Prisco, A., Sagri, M.T., Steve, G., Tiscornia, D.: Some ontological tools to support legal regulatory compliance, with a case study. In: Meersman, R., Tari, Z. (eds.) On the Move to Meaningful Internet Systems 2003, OTM 2003 Workshops. LNCS, 2889, pp. 607–620. Springer, Heidelberg (2003). Accessed 10 Sept 2015
  22. 22.
    Sagri, M., Tiscornia, D., Bertagna, F.: Jur-WordNet. In: Second International Wordnet Conference, pp. 305–310. Masaryk University, Brno (2004). Accessed 10 Mar 2018
  23. 23.
    Henderson, J., Bench-Capon, T.: Dynamic arguments in a case law domain. In.: Loui, R.P. (ed.) ICAIL 2001, Proceedings of the 8th International Conference on Artificial Intelligence and Law, pp. 60–69. ACM Press, New York (2001).
  24. 24.
    Zeng, Y., Wang, R., Zeleznikow, J., Kemp, E.: Knowledge representation for the intelligent legal case retrieval. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds.) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. LNCS (Part 1), vol. 3681, pp. 339–345. Springer, Berlin, Heidelberg (2005).
  25. 25.
    Poblet, M., Casanovas, P., López-Cobo, J.-M., Castellas, N.: ODR, ontologies, and Web 2.0. J. Univ. Comput. Sci. 17(4), 618–634 (2011). Accessed 21 Jan 2018
  26. 26.
    Karasiuk, V.: Ontological paradigm of process of content for education purposes. Bull. V. Karazin Kharkiv Natl. Univ. 19(1015), 148–154 (2012)Google Scholar
  27. 27.
    Tatsyi, V., Getman, A., Ivanov, S., Karasiuk, V., Lugoviy, O., Sokolov, O.: Semantic network of knowledge in science of law. In: Shokin, Yu., Bychkov, I., Potaturkin, O. (eds.) Proceedings of the IASTED International Conference on Automation, Control, and Information Technology (ACIT 2010), pp. 218–222. ACTA Press, Anaheim, USA (2010)Google Scholar
  28. 28.
    Gee, J.: Semiotic social spaces and affinity spaces: from the age of mythology to today’s schools. In: Barton, D., Tusting, K., (eds.) Beyond Communities of Practice. Language Power and Social Context. Cambridge University Press, Cambridge, MA, pp. 214–232 (2005). Accessed 2018/02/23
  29. 29.
    Wang, S.: Ontology of learning objects repository for pedagogical knowledge sharing. Interdiscip. J. E-Learn. Learn. Obj. 4, 1–12 (2008). Accessed 18 Mar 2018
  30. 30.
    Lendyuk, T., Vasylkiv, N.: Fuzzy model of individual learning path forming and ontology design on its basis. In: Oborsky G.A. (ed.) Informatics and Mathematical Methods in Simulation, vol. 7, no. (1–2), pp. 103–112 (2017)Google Scholar
  31. 31.
    Sokolov, A., Radivonenko, O., Morozova, O., Molchanov, O.: Use of the ontological test in the system of assessing the quality of training. In: Sokol, E. (ed.) Bulletin of the National Technical University “KhPI”, vol. 2, pp. 79–85 (2011)Google Scholar
  32. 32.
    Morozova, O.: Information technology of the training process organization based on the identification of individual parameters. Sci. Techn. J. Sci. Technol. the Air Force. Ukraine 3(36), 265–268 (2013)Google Scholar
  33. 33.
    Telnov, Yu., Kazakov, V., Kozlova, O.: Dynamic intellectual system of process management in information and education environment of higher educational institutions. J. Open Educ. 1(96), 40–49 (2013). Scholar
  34. 34.
    Valaski, J., Malucelli, A., Reinehr, S.: Recommending learning materials according to ontology-based learning styles. In: CAPES (2011). Accessed 25 Feb 2018

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Yaroslav Mudryi National Law UniversityKharkivUkraine
  2. 2.National Academy of Law Science of UkraineKharkivUkraine

Personalised recommendations