Goal-Oriented Regulatory Intelligence: How Can Watson Analytics Help?

  • Okhaide AkhigbeEmail author
  • Susie Heap
  • Sakib Islam
  • Daniel Amyot
  • John Mylopoulos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10650)


Regulations are introduced by governments to ensure the well-being, safety, and other societal needs of citizens and enterprises. Governments also create programs aiming to improve awareness about and compliance with regulations. Goal models have been used in the past to conceptualize regulations and to measure compliance assessments. However, regulators often have difficulties assessing the performance of their regulations and programs. In this paper, we model both regulations and regulatory programs with the Goal-oriented Requirement Language. Using the same conceptualization framework enables asking questions about performance and about the evidence-based impact of programs on regulations. We also investigate how Watson Analytics, a cloud-based data exploration service from IBM, can be used pragmatically to explore and visualize goal satisfaction data to understand compliance issues and program effectiveness. A simplified example inspired from a Canadian mining regulation is used to illustrate the many opportunities of Watson Analytics in that context, and some of its current limitations.


Data analytics Data visualization Goal models Goal-oriented Requirement Language GoRIM Regulatory compliance Regulatory intelligence Watson Analytics 



This work was supported financially by the National Science and Engineering Research Council of Canada (NSERC) Discovery program. We are much thankful to Colette Lacroix and IBM Canada for access to Watson Analytics. We also thank Prof. Greg Richards, Dr. Randy Giffen, and Nick Cartwright for useful discussions, as well as the reviewers for their insightful suggestions.


  1. 1.
    OECD: Recommendation of the Council on Regulatory Policy and Governance. OECD Publishing, Paris (2012)Google Scholar
  2. 2.
    OECD: The Governance of Regulators, OECD Best Practice Principles for Regulatory Policy. OECD Publishing, Paris (2014)Google Scholar
  3. 3.
    Coglianse, C.: Measuring regulatory performance: evaluating the impact of regulation and regulatory policy. OECD Expert Paper No. 1, OECD Publishing, Paris (2012)Google Scholar
  4. 4.
    Nielsen, V.L., Parker, C.: Is it possible to measure compliance? Legal Studies Research Paper No. 192, Faculty of Law, The University of Melbourne (2006). SSRN
  5. 5.
    Parker, D., Kirkpatrick, C.: Measuring regulatory performance. The economic impact of regulatory policy: a literature review of quantitative evidence. OECD Expert Paper No. 3, OECD Publishing, Paris (2012)Google Scholar
  6. 6.
    Horkoff, J., Aydemir, F.B., Cardoso, E., Li, T., Maté, A., Paja, E., Giorgini, P.: Goal-oriented requirements engineering: a systematic literature map. In: 24th International Requirements Engineering Conference (RE), pp. 106–115. IEEE CS (2016). doi: 10.1109/RE.2016.41
  7. 7.
    Akhigbe, O., Amyot, D., Richards, G.: Information technology artifacts in the regulatory compliance of business processes: a meta-analysis. In: Benyoucef, M., Weiss, M., Mili, H. (eds.) MCETECH 2015. LNBIP, vol. 209, pp. 89–104. Springer, Cham (2015). doi: 10.1007/978-3-319-17957-5_6CrossRefGoogle Scholar
  8. 8.
    Gandomi, A., Haider, M.: Beyond the hype: big data concepts, methods, and analytics. Int. J. Inf. Manag. 35(2), 137–144 (2015). doi: 10.1016/j.ijinfomgt.2014.10.007CrossRefGoogle Scholar
  9. 9.
    IBM: IBM Watson Analytics: Analytics Made Easy. Accessed 23 Apr 2017
  10. 10.
    Akhigbe, O., Amyot, D., Mylopoulos, J., Richards, G.: What can information systems do for regulators? A review of the state-of-practice in Canada. In: IEEE 11th International Conference on Research Challenges in Information Science (RCIS). IEEE CS (2017)Google Scholar
  11. 11.
    Siena, A., Perini, A., Susi, A., Mylopoulos, J.: A meta-model for modelling law-compliant requirements. In: Requirements Engineering and Law (RELAW), pp. 45–51. IEEE CS (2009). doi: 10.1109/RELAW.2009.1
  12. 12.
    Ingolfo, S., Siena, A., Perini A., Susi, A., Mylopoulos, J.: Modeling laws with Nòmos 2. In: 6th International Workshop on RE and LAW (RELAW), pp. 69–71. IEEE CS (2013). doi: 10.1109/RELAW.2013.6671350
  13. 13.
    Ingolfo, S., Jureta, I., Siena, A., Perini, A., Susi, A.: Nòmos 3: legal compliance of roles and requirements. In: Yu, E., Dobbie, G., Jarke, M., Purao, S. (eds.) ER 2014. LNCS, vol. 8824, pp. 275–288. Springer, Cham (2014). doi: 10.1007/978-3-319-12206-9_22CrossRefGoogle Scholar
  14. 14.
    Islam, S., Mouratidis, H., Jürjens, J.: A framework to support alignment of secure software engineering with legal regulations. Softw. Syst. Model. 10(3), 369–394 (2011). doi: 10.1007/s10270-010-0154-zCrossRefGoogle Scholar
  15. 15.
    Amyot, D., Mussbacher, G.: User requirements notation: the first ten years, the next ten years. J. Softw. (JSW) 6(5), 47–768 (2011)Google Scholar
  16. 16.
    Ghanavati, S., Amyot, D., Peyton, L.: Compliance analysis based on a goal-oriented requirement language evaluation methodology. In: 17th IEEE International Requirements Engineering Conference (RE 2009), pp. 133–142. IEEE CS (2009). doi: 10.1109/RE.2009.42
  17. 17.
    Ghanavati, S., Amyot, D., Rifaut, A.: Legal goal-oriented requirement language (Legal GRL) for modeling regulations. In: 6th International Workshop on Modeling in Software Engineering (MiSE), pp. 1–6. ACM (2014). doi: 10.1145/2593770.2593780
  18. 18.
    Shamsaei, A., Pourshahid, A., Amyot, D.: Business process compliance tracking using key performance indicators. In: zur Muehlen, M., Su, J. (eds.) BPM 2010. LNBIP, vol. 66, pp. 73–84. Springer, Heidelberg (2011). doi: 10.1007/978-3-642-20511-8_7CrossRefGoogle Scholar
  19. 19.
    Amyot, D., et al.: Towards advanced goal model analysis with jUCMNav. In: Castano, S., Vassiliadis, P., Lakshmanan, L.V., Lee, M.L. (eds.) ER 2012. LNCS, vol. 7518, pp. 201–210. Springer, Heidelberg (2012). doi: 10.1007/978-3-642-33999-8_25CrossRefGoogle Scholar
  20. 20.
    Tawhid, R., Braun, E., et al.: Towards outcome-based regulatory compliance in aviation security. In: 20th IEEE International Requirements Engineering Conference (RE), pp. 267–272. IEEE CS (2012). doi: 10.1109/RE.2012.6345813
  21. 21.
    Badreddin, O., Mussbacher, G., et al.: Regulation-based dimensional modeling for regulatory intelligence. In: 6th International Workshop on Requirements Engineering and Law (RELAW), pp. 1–10. IEEE CS (2013). doi: 10.1109/RELAW.2013.6671340
  22. 22.
    Aggarwal, M., Madhukar, M.: IBM’s Watson Analytics for health care: a miracle made true. In: Cloud Computing Systems and Applications in Healthcare, pp. 117–134. IGI Global (2017). doi: 10.4018/978-1-5225-1002-4.ch007
  23. 23.
    Anderson, F.: Watson Analytics sessions at World of Watson 2016. Accessed 23 Apr 2017
  24. 24.
    Hynes, C.: Regulatory intelligence: implications for product development. In: 2014 TOPRA Module: Strategic Planning in Regulatory Affairs. Accessed 23 Apr 2017
  25. 25.
    Felgate, T.: What is regulatory intelligence? Accessed 23 Apr 2017
  26. 26.
    Maguire, P.: What is ‘regulatory intelligence?’. Regulatory Affairs Professional Society. Accessed 23 Apr 2017
  27. 27.
    Rashidi-Tabrizi, R., Mussbacher, G., Amyot, D.: Transforming regulations into performance models in the context of reasoning for outcome-based compliance. In: 6th International Workshop on Requirements Engineering and Law (RELAW), pp. 34–43. IEEE CS (2013)Google Scholar
  28. 28.
    Pourshahid, A., Amyot, D., Peyton, L., Ghanavati, S., Chen, P., Weiss, M., Forster, A.J.: Business process management with the user requirements notation. Electron. Commer. Res. 9(4), 269–316 (2009). doi: 10.1007/s10660-009-9039-zCrossRefGoogle Scholar
  29. 29.
    Justice Laws Website: Consolidated federal laws of Canada, Metal Mining Effluent Regulations. Accessed 23 Apr 2017

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Okhaide Akhigbe
    • 1
    Email author
  • Susie Heap
    • 1
  • Sakib Islam
    • 1
  • Daniel Amyot
    • 1
  • John Mylopoulos
    • 1
  1. 1.School of Electrical Engineering and Computer ScienceUniversity of OttawaOttawaCanada

Personalised recommendations