Towards Automating the Detection of Event Sources

  • Nico Herzberg
  • Oleh Khovalko
  • Anne Baumgrass
  • Mathias Weske
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8377)

Abstract

During business process execution, various systems and services produce a variety of data, messages, and events that are valuable for gaining insights about business processes, e.g., to ensure a business process is executed as expected. However, these data, messages, and events usually originate from different kinds of sources, each specified by different kinds of descriptions. This variety makes it difficult to automate the detection of relevant event sources for business process monitoring. In this paper, we present a course of actions to automatically associate different event sources to event object types required for business process monitoring. In particular, in a three-step approach we determine the similarity of event sources to event object types, rank those results, and derive a mapping between their attributes. Thus, relevant event sources and their bindings to specified event object types of business processes can be automatically identified. The approach is implemented and evaluated using schema matching techniques for a specific use case that is aligned with real-world energy processes, data, messages, and events.

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References

  1. 1.
    Papazoglou, M.P., Heuvel, W.J.: Service oriented architectures: approaches, technologies and research issues. The VLDB Journal 16(3) (July 2007)Google Scholar
  2. 2.
    Levina, O., Stantchev, V.: Realizing Event-Driven SOA. In: 4th International Conference on Internet and Web Applications and Services, ICIW (2009)Google Scholar
  3. 3.
    Weske, M.: Business Process Management - Concepts, Languages, Architectures, 2nd edn. Springer (2012)Google Scholar
  4. 4.
    van der Aalst, W.: Process Mining: Overview and Opportunities. ACM Transactions on Management Information Systems (TMIS) 3(2) (July 2012)Google Scholar
  5. 5.
    Weidlich, M., Ziekow, H., Mendling, J., Günther, O., Weske, M., Desai, N.: Event-Based Monitoring of Process Execution Violations. In: Rinderle-Ma, S., Toumani, F., Wolf, K. (eds.) BPM 2011. LNCS, vol. 6896, pp. 182–198. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  6. 6.
    Bülow, S., Backmann, M., Herzberg, N., Hille, T., Meyer, A., Ulm, B., Wong, T.Y., Weske, M.: Monitoring of Business Processes with Complex Event Processing. In: BPM Workshops. Springer (2013) (accepted for publication)Google Scholar
  7. 7.
    Herzberg, N., Meyer, A., Weske, M.: An Event Processing Platform for Business Process Management. In: IEEE International EDOC Conference, Vancouver (2013)Google Scholar
  8. 8.
    Etzion, O., Niblett, P.: Event Processing in Action. Manning Publications Co (2011)Google Scholar
  9. 9.
    Luckham, D.: The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems. Addison-Wesley (2002)Google Scholar
  10. 10.
    Luckham, D., Schulte, R.: Event Processing Glossary - Version 2.0 (July 2011), http://www.complexevents.com/wp-content/uploads/2011/08/EPTS_Event_Processing_Glossary_v2.pdf
  11. 11.
    OMG: Business Process Model and Notation (BPMN), Version 2.0 (2011), http://www.omg.org/spec/BPMN/2.0/
  12. 12.
    Rahm, E., Bernstein, P.A.: A survey of approaches to automatic schema matching. The VLDB Journal 10(4) (2001)Google Scholar
  13. 13.
    Euzenat, J., Shvaiko, P.: Ontology matching, vol. 18. Springer, Heidelberg (2007)MATHGoogle Scholar
  14. 14.
    Marie, A., Gal, A.: On the Stable Marriage of Maximum Weight Royal Couples. In: AAAI Workshop on Information Integration on the Web (2007)Google Scholar
  15. 15.
    Baier, T., Mendling, J.: Bridging Abstraction Layers in Process Mining by Automated Matching of Events and Activities. In: Daniel, F., Wang, J., Weber, B. (eds.) BPM 2013. LNCS, vol. 8094, pp. 17–32. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  16. 16.
    Baier, T., Mendling, J.: Bridging Abstraction Layers in Process Mining: Event to Activity Mapping. In: Nurcan, S., Proper, H.A., Soffer, P., Krogstie, J., Schmidt, R., Halpin, T., Bider, I. (eds.) BPMDS 2013 and EMMSAD 2013. LNBIP, vol. 147, pp. 109–123. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  17. 17.
    Hasan, S., O’Riain, S., Curry, E.: Approximate semantic matching of heterogeneous events. In: 6th ACM International Conference on Distributed Event-Based Systems, DEBS (2012)Google Scholar
  18. 18.
    Bellahsene, Z., Bonifati, A., Rahm, E.: Schema Matching and Mapping. Springer (2011)Google Scholar
  19. 19.
    Gal, A., Sagi, T.: Tuning the ensemble selection process of schema matchers. Information Systems 35(8) (2010)Google Scholar
  20. 20.
    Gal, A.: Managing Uncertainty in Schema Matching with Top-K Schema Mappings. In: Spaccapietra, S., Aberer, K., Cudré-Mauroux, P. (eds.) Journal on Data Semantics VI. LNCS, vol. 4090, pp. 90–114. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  21. 21.
    Kuropka, D., Troeger, P., Staab, S., Weske, M.: Semantic Service Provisioning. Springer (2008)Google Scholar
  22. 22.
    Wang, Y., Stroulia, E.: Flexible Interface Matching for Web-Service Discovery. In: 4th Int. Conference on Web Information Systems Engineering (WISE). IEEE Computer Society (2003)Google Scholar
  23. 23.
    Klein, M., Bernstein, A.: Toward high-precision service retrieval. IEEE Internet Computing 8(1), 30–36 (2004)CrossRefGoogle Scholar
  24. 24.
    Hao, Y., Zhang, Y.: Web services discovery based on schema matching. In: 13th Australasian Conference on Computer Science (ACSC), vol. 62, pp. 107–113. Australian Computer Society, Inc. (2007)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Nico Herzberg
    • 1
  • Oleh Khovalko
    • 1
  • Anne Baumgrass
    • 1
  • Mathias Weske
    • 1
  1. 1.Hasso Plattner Institute at the University of PotsdamPotsdamGermany

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