Information Gathering for Semantic Service Discovery and Composition in Business Process Modeling

  • Norman May
  • Ingo Weber
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 10)


When creating an execution-level process model today, two crucial problems are how to find the right services (service discovery and composition), and how to make sure they are in the right order (semantic process validation). While isolated solutions for both problems exist, a unified approach has not yet been available. Our approach resolves this shortcoming by gathering all existing information in the process, thus making the basis of semantic service discovery and task composition both broader and more targeted. Thereby we achieve the following benefits: (i) less modeling overhead for semantic annotations to the process, (ii) more information regarding the applicability of services, and (iii) early avoidance of inconsistencies in the interrelation between all process parts. Consequently, new or changed business processes can be realized in IT more efficiently and with fewer errors, thus making enterprises more agile in response to new requirements and opportunities.


Semantic Business Process Management Web Service Discovery & Composition 


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  1. 1.
    Akkiraju, R., Srivastava, B., Anca-Andreea, I., Goodwin, R., Syeda-Mahmood, T.: Semaplan: Combining planning with semantic matching to achieve web service composition. In: 4th International Conference on Web Services (ICWS 2006) (2006)Google Scholar
  2. 2.
    Constantinescu, I., Faltings, B., Binder, W.: Typed Based Service Composition. In: Proc. WWW 2004 (2004)Google Scholar
  3. 3.
    Hepp, M., Leymann, F., Domingue, J., Wahler, A., Fensel, D.: Semantic business process management: A vision towards using semantic web services for business process management. In: ICEBE, pp. 535–540 (2005)Google Scholar
  4. 4.
    Hoffmann, J., Scicluna, J., Kaczmarek, T., Weber, I.: Polynomial-Time Reasoning for Semantic Web Service Composition. In: Intl. Workshop Web Service Composition and Adaptation (WSCA) at ICWS (2007)Google Scholar
  5. 5.
    Koliadis, G., Ghose, A.: Verifying semantic business process models in inter-operation. In: Intl. Conf. Services Computing (SCC 2007) (2007)Google Scholar
  6. 6.
    Lemcke, J., Friesen, A.: Composing web-service-like abstract state machines (ASMs). In: Intl. Conf. Services Computing - Workshops (SCW 2007) (2007)Google Scholar
  7. 7.
    Li, L., Horrocks, I.: A software framework for matchmaking based on semantic web technology. In: 12th World Wide Web Conference (WWW 2003) (2003)Google Scholar
  8. 8.
    Lutz, C., Sattler, U.: A proposal for describing services with DLs. In: International Workshop on Description Logics 2002 (DL 2002) (2002)Google Scholar
  9. 9.
    Ly, L.T., Rinderle, S., Dadam, P.: Semantic correctness in adaptive process management systems. In: Dustdar, S., Fiadeiro, J.L., Sheth, A.P. (eds.) BPM 2006. LNCS, vol. 4102, Springer, Heidelberg (2006)CrossRefGoogle Scholar
  10. 10.
    Meyer, H., Weske, M.: Automated service composition using heuristic search. In: Dustdar, S., Fiadeiro, J.L., Sheth, A.P. (eds.) BPM 2006. LNCS, vol. 4102, pp. 81–96. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  11. 11.
    OMG. Business Process Modeling Notation – BPMN 1.0. Final Adopted Specification, February 6, 2006 (2006),
  12. 12.
    Paolucci, M., Kawamura, T., Payne, T., Sycara, K.: Semantic matching of web services capabilities. In: Horrocks, I., Hendler, J. (eds.) ISWC 2002. LNCS, vol. 2342, Springer, Heidelberg (2002)Google Scholar
  13. 13.
    Pistore, M., Marconi, A., Bertoli, P., Traverso, P.: Automated composition of web services by planning at the knowledge level. In: IJCAI (2005)Google Scholar
  14. 14.
    Rao, J., Su, X.: A Survey of Automated Web Service Composition Methods. In: Cardoso, J., Sheth, A.P. (eds.) SWSWPC 2004. LNCS, vol. 3387, pp. 43–54. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  15. 15.
    Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice-Hall, Englewood Cliffs (1995)Google Scholar
  16. 16.
    Sirin, E., Parsia, B.: Planning for semantic web services. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, Springer, Heidelberg (2004)Google Scholar
  17. 17.
    Stuckenschmidt, H.: Partial matchmaking using approximate subsumption. In: AAAI, pp. 1459–1464 (2007)Google Scholar
  18. 18.
    van der Aalst, W.M.P., ter Hofstede, A.H.M., Weske, M. (eds.): Business process management: A survey. Business Process Management (BPM). LNCS, vol. 2678. Springer, Heidelberg (2003)Google Scholar
  19. 19.
    Vanhatalo, J., Völzer, H., Leymann, F.: Faster and More Focused Control-Flow Analysis for Business Process Models though SESE Decomposition. In: Krämer, B.J., Lin, K.-J., Narasimhan, P. (eds.) ICSOC 2007. LNCS, vol. 4749, Springer, Heidelberg (2007)CrossRefGoogle Scholar
  20. 20.
    Weber, I., Hoffmann, J.: Semantic business process validation. Technical report, University of Innsbruck (2008),
  21. 21.
    Weber, I., Markovic, I., Drumm, C.: A Conceptual Framework for Composition in Business Process Management. In: Abramowicz, W. (ed.) BIS 2007. LNCS, vol. 4439, Springer, Heidelberg (2007)CrossRefGoogle Scholar
  22. 22.
    Winslett, M.: Reasoning about actions using a possible models approach. In: Proc. AAAI 1988 (1988)Google Scholar
  23. 23.
    Wynn, M., Verbeek, H., van der Aalst, W., ter Hofstede, A., Edmond, D.: Business process verification - finally a reality! Business Process Management Journal (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Norman May
    • 1
  • Ingo Weber
    • 1
  1. 1.SAP ResearchKarlsruheGermany

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