Advertisement

Activity-Oriented Clustering Techniques in Large Process and Compliance Rule Repositories

  • Stefanie Rinderle-Ma
  • Sonja Kabicher
  • Linh Thao Ly
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 100)

Abstract

Organizations often have to deal with large collections of business process models and compliance rules. Particular challenges in this context are compliance checks, consistency checks, and the maintenance of the process and rule repositories. In case that a-priory knowledge about dependencies within the process base and the rule base is not available, compliance checking must be performed by verifying all rules for each process, which turns out to be very costly in a context of large process and rule repositories. In this paper we present activity-oriented clustering techniques for efficient compliance checking which are particularly applicable in process and rule repositories where no a-priori clustering is considered. Further it is shown how the proposed clustering techniques influence the complexity of consistency checks. Finally, qualitative and quantitative aspects of the presented clustering techniques are discussed. The techniques provide a first step to effective and efficient management of large business process and compliance rule repositories.

Keywords

Business Process Cluster Technique Consistency Check Execution Trace Business Process Model 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Ly, L.T., Rinderle, S., Dadam, P.: Integration and verification of semantic constraints in adaptive process management systems. Data & Knowledge Engineering 64(1), 3–23 (2008)CrossRefGoogle Scholar
  2. 2.
    Valkenburg, M.: Van ameyde international case study. Technical report (2010), http://www.bptrends.com
  3. 3.
    Namiri, K.: Model-Driven Management of Internal Controls for Business Process Compliance. PhD thesis, University of Karlsruhe (2008)Google Scholar
  4. 4.
    Federal Agency for Security in IT, G.: It baseline security - catalogues (2006), http://www.bsi.bund.de (in German Language)
  5. 5.
    Ly, L.T., Rinderle-Ma, S., Dadam, P.: Design and Verification of Instantiable Compliance Rule Graphs in Process-Aware Information Systems. In: Pernici, B. (ed.) CAiSE 2010. LNCS, vol. 6051, pp. 9–23. Springer, Heidelberg (2010) 10.1007/978-3-642-13094-6_3CrossRefGoogle Scholar
  6. 6.
    Knuplesch, D., Ly, L.T., Rinderle-Ma, S., Pfeifer, H., Dadam, P.: On Enabling Data-Aware Compliance Checking of Business Process Models. In: Parsons, J., Saeki, M., Shoval, P., Woo, C., Wand, Y. (eds.) ER 2010. LNCS, vol. 6412, pp. 332–346. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  7. 7.
    Tran, H., Zdun, U., Dustdar, S.: VbTrace: using view-based and model-driven development to support traceability in process-driven SOAs. Software and Systems Modeling 10, 5–29 (2011) 10.1007/s10270-009-0137-0CrossRefGoogle Scholar
  8. 8.
    Suwa, M., Scott, A.C., Shortcliffe, E.H.: An approach to verifying completeness and consistency in a Rule-Based expert system. AI Magazine 3(4) (1982)Google Scholar
  9. 9.
    Nguyen, T.A., Perkins, W.A., Laffey, T.J., Pecora, D.: Checking an expert systems knowledge base for consistency and completeness. In: Proc. Int’l Conf. on Artificial intelligence, vol. 1, pp. 375–378 (1985) ACM ID: 1625205Google Scholar
  10. 10.
    Hornung, T., Koschmider, A., Oberweis, A.: A recommender system for business process models. SSRN eLibrary (2007)Google Scholar
  11. 11.
    Awad, A., Sakr, S.: Querying Graph-Based Repositories of Business Process Models. In: Yoshikawa, M., Meng, X., Yumoto, T., Ma, Q., Sun, L., Watanabe, C. (eds.) DASFAA 2010. LNCS, vol. 6193, pp. 33–44. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  12. 12.
    Di Francescomarino, C., Tonella, P.: Crosscutting Concern Documentation by Visual Query of Business Processes. In: Ardagna, D., Mecella, M., Yang, J. (eds.) BPM 2008 Workshops. LNBIP, vol. 17, pp. 18–31. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  13. 13.
    Awad, A., Decker, G., Weske, M.: Efficient Compliance Checking Using BPMN-Q and Temporal Logic. In: Dumas, M., Reichert, M., Shan, M.-C. (eds.) BPM 2008. LNCS, vol. 5240, pp. 326–341. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  14. 14.
    Rosa, M.L., Reijers, H.A., van der Aalst, W.M., Dijkman, R.M., Mendling, J., Dumas, M., García-Bañuelos, L.: APROMORE: an advanced process model repository. Expert Systems with Applications 38(6), 7029–7040 (2011)CrossRefGoogle Scholar
  15. 15.
    Jin, T., Wang, J., Wu, N., La Rosa, M., ter Hofstede, A.H.M.: Efficient and Accurate Retrieval of Business Process Models through Indexing. In: Meersman, R., Dillon, T.S., Herrero, P. (eds.) OTM 2010, Part I. LNCS, vol. 6426, pp. 402–409. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  16. 16.
    Namiri, K., Stojanovic, N.: Towards a formal framework for business process compliance. In: Multikonferenz Wirtschaftsinformatik, MKWI 2008 (2008)Google Scholar
  17. 17.
    Liu, Y., Müller, S., Xu, K.: A static compliance-checking framework for business process models. IBM Systems Journal 46(2), 335–361 (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Stefanie Rinderle-Ma
    • 1
  • Sonja Kabicher
    • 1
  • Linh Thao Ly
    • 2
  1. 1.Faculty of Computer Science, Workflow Systems and Technology GroupUniversity of ViennaAustria
  2. 2.Institute of Databases and Information SystemsUlm UniversityGermany

Personalised recommendations