An Architecture for Establishing Legal Semantic Workflows in the Context of Integrated Law Enforcement

  • Markus StumptnerEmail author
  • Wolfgang Mayer
  • Georg Grossmann
  • Jixue Liu
  • Wenhao Li
  • Pompeu Casanovas
  • Louis De Koker
  • Danuta Mendelson
  • David Watts
  • Bridget Bainbridge
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10791)


Traditionally the integration of data from multiple sources is done on an ad-hoc basis for each analysis scenario and application. This is a solution that is inflexible, incurs high costs, leads to “silos” that prevent sharing data across different agencies or tasks, and is unable to cope with the modern environment, where workflows, tasks, and priorities frequently change. Operating within the Data to Decision Cooperative Research Centre (D2D CRC), the authors are currently involved in the Integrated Law Enforcement Project, which has the goal of developing a federated data platform that will enable the execution of integrated analytics on data accessed from different external and internal sources, thereby providing effective support to an investigator or analyst working to evaluate evidence and manage lines of inquiries in the investigation. Technical solutions should also operate ethically, in compliance with the law and subject to good governance principles.


Natural language processing of legal texts Law enforcement investigation management 


  1. 1.
    Edwards, M., Rashid, A., Rayson, P.: A systematic survey of online data mining technology intended for law enforcement. ACM Comput. Surv. (CSUR) 48(1), 15 (2015)CrossRefGoogle Scholar
  2. 2.
    Pagallo, U.: Good onlife governance: on law, spontaneous orders, and design. In: Floridi, L. (ed.) The Onlife Manifesto. Being Human in a Hyperconnected Era, pp. 161–177. Springer, Cham (2015). Scholar
  3. 3.
    Casanovas, P.: Cyber warfare and organised crime. A regulatory model and meta-model for open source intelligence (OSINT). In: Taddeo, M., Glorioso, L. (eds.) Ethics and Policies for Cyber Operations. PSS, vol. 124, pp. 139–167. Springer, Cham (2017). Scholar
  4. 4.
    Alexe, B., ten Cate, B., Kolaitis, P.G., Tan, W.C.: Designing and refining schema mappings via data examples. In: Proceedings ACM SIGMOD International Conference on Management of Data, pp. 133–144 (2011)Google Scholar
  5. 5.
    Rodríguez-Doncel, V., Santos, C., Casanovas, P., et al.: Legal aspects of linked data – The European framework. Comput. Law Secur. Rev. (2016). Scholar
  6. 6.
    Bellahsene, Z., Bonifati, A., Rahm, E.: Schema Matching and Mapping. Data-Centric Systems and Applications. Springer, Heidelberg (2011). ISBN 978-3-642-16517-7CrossRefzbMATHGoogle Scholar
  7. 7.
    Rodriguez-Doncel, V., Gómez-Pérez, A., Mihindukulasooriya, N.: Rights declaration in linked data. In: Hartig, O., et al. (eds.) COLD. CEUR, vol. 1034 (2013).
  8. 8.
    Governatori, G., Rotolo, A., Villata, S., Gandon, F.: One license to compose them all. In: Alani, H., et al. (eds.) ISWC 2013. LNCS, vol. 8218, pp. 151–166. Springer, Heidelberg (2013). Scholar
  9. 9.
    Cardellino, C., et al.: Licentia: a tool for supporting users in data licensing on the web of data. In: Proceedings of the 2014 International Conference on Posters & Demonstrations Track, vol. 1272. (2014)Google Scholar
  10. 10.
    Rodríguez-Doncel, V., Santos, C., Casanovas, P., et al.: A linked term bank of copyright-related terms. In: Rotolo, A. (ed.) Legal Knowledge and Information Systems, pp. 91–99. IOS Press, Amsterdam (2015)Google Scholar
  11. 11.
    Knoblock, C.A., Szekely, P.A.: Exploiting semantics for big data integration. AI Mag. 36(1), 25–38 (2015)CrossRefGoogle Scholar
  12. 12.
    Xiaofei, X., Sheng, Q.Z., Zhang, L.-J., Fan, Y., Dustdar, S.: From big data to big service. IEEE Comput. 48(7), 80–83 (2015)CrossRefGoogle Scholar
  13. 13.
    Casanovas, P., Palmirani, M., Peroni, S., van Engers, T., Vitali, F.: Special issue on the semantic web for the legal domain, guest editors editorial: the next step. Semant. Web J. 7(2), 1–13 (2016)CrossRefGoogle Scholar
  14. 14.
    Boella, G., Humphreys, L., Muthuri, R., van der Torre, L., Rossi, P.: A critical analysis of legal requirements engineering from the perspective of legal practice. In: Seventh IEEE Workshop on Requirements Engineering and Law, pp. 14–21. IEEE RELAW (2014)Google Scholar
  15. 15.
    Koops, B.J., Leenes, R.: Privacy regulation cannot be hardcoded. A critical comment on the ‘privacy by design’ provision in data-protection law. Int. Rev. Law Comput. Technol. 28(2), 159–171 (2014)CrossRefGoogle Scholar
  16. 16.
    Casanovas, P., Arraiza, J., Melero, F., González-Conejero, J., Molcho, G., Cuadros, M.: Fighting organized crime through open source intelligence: regulatory strategies of the CAPER Project. In: Proceedings of the 27th Annual Conference on Legal Knowledge and Information Systems, JURIX-2014, pp. 189–199. IOS Press, Amsterdam (2014)Google Scholar
  17. 17.
    Colesky, M., Hoepman, J.H., Hillen, C.: A critical analysis of privacy design strategies. In: IEEE Symposium on Security and Privacy Workshops, pp. 33–40 (2016).
  18. 18.
    Maurushat, A., Bennet-Moses, L., Vaile, D.: Using ‘big’ metadata for criminal intelligence: understanding limitations and appropriate safeguards. In: Proceedings of the 15th International Conference on Artificial Intelligence and Law, pp. 196–200. ACM (2015)Google Scholar
  19. 19.
    Selway, M., Grossmann, G., Mayer, W., Stumptner, M.: Formalising natural language specifications using a cognitive linguistic/configuration based approach. Inf. Syst. 54, 191–208 (2015)CrossRefGoogle Scholar
  20. 20.
    Bennet Moses, L., Chan, J., De Koker, L., et al.: Big Data Technology and National Security - Comparative International Perspectives on Strategy, Policy and Law Australia. Data to Decisions CRC (2016)Google Scholar
  21. 21.
    Parliamentary Joint Committee on Law Enforcement. In: Inquiry into the Gathering and Use of Criminal Intelligence (2013).
  22. 22.
    Pagallo, U.: Online security and the protection of civil rights: a legal overview. Philos. Technol. 26, 381–395 (2013)CrossRefGoogle Scholar
  23. 23.
    Grossmann, G., et al.: Integrated Law Enforcement Platform Federated Data Model. Technical report, Data to Decisions CRC (2017)Google Scholar
  24. 24.
    Lebo, T., et al.: Prov-o: The PROV Ontology. W3C Recommendation (2013)Google Scholar
  25. 25.
    Kolovos, D.S., Paige, R.F., Polack, F.A.C.: The epsilon transformation language. In: Vallecillo, A., Gray, J., Pierantonio, A. (eds.) ICMT 2008. LNCS, vol. 5063, pp. 46–60. Springer, Heidelberg (2008). Scholar
  26. 26.
    Del Corro, L., Gemulla, R.: Clausie: clause-based open information extraction. In: Proceedings of the 22nd International Conference on World Wide Web. ACM (2013)Google Scholar
  27. 27.
    Mondorf, A., Wimmer, M.A.: Requirements for an architecture framework for pan-european e-government services. In: Scholl, H.J., et al. (eds.) EGOVIS 2016. LNCS, vol. 9820, pp. 135–150. Springer, Cham (2016). Scholar
  28. 28.
    Open Group Standard TOGAF Version 9.1 Document Number: G116. ISBN 9789087536794Google Scholar
  29. 29.
    Watts, D., Bainbridge, B., de Koker, L., Casanovas, P., Smythe, S.: Project B.3. In: A Governance Framework for the National Criminal Intelligence System (NCIS), Data to Decisions Cooperative Research Centre, La Trobe University, 30 June 2017Google Scholar
  30. 30.
    Bennet-Moses, L., de Koker, L.: Open secrets: balancing operational secrecy and transparency in the collection and use of data for national security and law enforcement agencies. Melb. Univ. Law Rev. 41(2) (2017)Google Scholar
  31. 31.
    Bainbridge, B., de Koker, L., Watts, D., Mendelson, D., Casanovas, P.: Identity Assurance, ‘Pattern of Life’ and Big Data Analytics Report. Project B.1: Identity Assurance, Law and Policy Program. Data to Decisions Cooperative Research Centre, La Trobe University, May 2017Google Scholar
  32. 32.
    Mayer, W., Stumpfner, M., Casanovas, P., de Koker, L.: Towards a linked information architecture for integrated law enforcement. In: Poblet, M., Plaza, E., Casanovas, P. (eds.), Linked Democracy: Artificial Intelligence for Democratic Innovation, IJCAI-2017 Workshop, August, Melbourne, CEUR, pp. 15–37 (2017).
  33. 33.
    Berson, A., Dubov, L.: Master Data Management and Data Governance, 2nd edn. McGraw-Hill Education, New York (2010)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.University of South AustraliaAdelaideAustralia
  2. 2.La Trobe Law SchoolLa Trobe UniversityMelbourneAustralia
  3. 3.Autonomous University of BarcelonaBarcelonaSpain
  4. 4.Deakin Law SchoolDeakin UniversityMelbourneAustralia

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