Ontology-Based Approach for Semantic Service Selection in Business Process Re-Engineering

  • Sophea Chhun
  • Néjib Moalla
  • Yacine Ouzrout
Conference paper
Part of the Proceedings of the I-ESA Conferences book series (IESACONF, volume 7)


This research aims to provide the possibility to the business analysts to be able to know whether their design business processes are feasible or not. In order to solve this problem, we proposed a model called BPMNSemAuto that makes use of the existing services stored in the service registry UDDI (Universal Description Discovery and Integration). From the data extracted from the UDDI, the WSDL files and the tracking data of service execution on the server, a Web Service Ontology (WSOnto) is generated to store all the existing services. The BPMNSemAuto model takes an input of business process design specifications, and it generates an executable business process as an output. It provides an interface for business analysts to specify the description of each service task of the design business process. For each service task, the business analysts specify the task objective (keywords), inputs, outputs and weights of the Quality of Service (QoS) properties. From the design business process with the service task specifications, a Business Process Ontology (BPOnto) is generated. A service selection algorithm performs the mapping between the instances of the WSOnto and the BPOnto to obtain possible mappings between these two ontologies. The obtained mappings help the model to acquire web services to execute the desired service tasks. Moreover, the consistency checking of the inputs of the proposed model is performed before executing the service selection algorithm. WordNet is used to solve the synonym problems and at the same time a keyword extraction method is presented in this paper.


Business process Keyword extraction Ontology Ontology matching QoS Semantic web service Service selection 



This project has been funded with support from the European Commission (EMA2-2010- 2359 Project). This publication reflects the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein.


  1. 1.
    Workflow Management Coalition. (1999). Workflow management coalition terminology & glossary.Google Scholar
  2. 2.
    Rummler, G. A., & Brache, A. P. (1995). Improving performance: How to manage the white space on the organization chart (2nd ed.). San Francisco: Jossey-Bass.Google Scholar
  3. 3.
    OMG. (2011). Business process model and notation (BPMN) version 2.0. Object Management Group.Google Scholar
  4. 4.
    Lohmann, N., Verbeek, E., & Dijkman, R. (2009). Petri net transformations for business processes–a survey. In Transactions on petri nets and other models of concurrency II (pp. 46–63). Berlin Heidelberg: Springer.Google Scholar
  5. 5.
    Genrich, H. J., & Lautenbach, K. (1981). System modelling with high-level Petri nets. Theoretical Computer Science, 13(1), 109–135.MATHMathSciNetCrossRefGoogle Scholar
  6. 6.
  7. 7.
    Correia, A., & Abreu, F. B. e. (2012, January). Adding preciseness to BPMN models. Procedia Technology 5, 407–17.Google Scholar
  8. 8.
    Chandrasekaran, B., Josephson, J. R., & Benjamins, V. R. (1999). What are ontologies, and why do we need them? Intelligent Systems and Their Applications, IEEE., 14(1), 20–26.CrossRefGoogle Scholar
  9. 9.
    Lu, R., & Sadiq, S. (2007). A survey of comparative business process modeling approaches. Business information systems (pp. 82–94).Google Scholar
  10. 10.
    Abramowicz, W., Filipowska, A., Kaczmarek, M., & Kaczmarek, T. (2007). Semantically enhanced business process modelling notation. In Proceedings of the Workshop on Semantic Business Process and Product Lifecycle Management (SBPM-2007).Google Scholar
  11. 11.
    Sabou, M. (2006). Building Web service ontologies.Google Scholar
  12. 12.
    Jaeger, M., Rojec-Goldmann, G., Liebetruth, C., Mühl, G., & Geihs, K. (2005). Ranked matching for service descriptions using owl-s. Kommunikation in Verteilten Systemen (KiVS) (pp. 91–102).Google Scholar
  13. 13.
    Kalibatiene, D., & Vasilecas, O. (2011). Survey on ontology languages. Perspectives in Business Informatics Research (pp. 124–141).Google Scholar
  14. 14.
    Azleny Kamaruddin, L., Shen, J., & Beydoun, G. (2012). Evaluating usage of WSMO and OWL-S in semantic web services. In Eighth Asia-Pacific Conference on Conceptual Modelling (APCCM 2012) (pp. 53–58). Melbourne: Australian Computer Society.Google Scholar
  15. 15.
    Neelavathi, S., & Vivekanandan, K. (2011). An innovative quality of service (QOS) based service selection for service orchrestration in SOA. International Journal of Scientific and Engineering Research, 2(4), 1–8.Google Scholar
  16. 16.
    Pradnya Khutade, A., & Rashmi Phalnikar, B. (2012). QOS based web service discovery using oo concepts. International Journal of Advanced Technology & Engineering Research (IJATER), 2(6), 81–86Google Scholar
  17. 17.
    Chaari, S., Badr, Y., Biennier, F., BenAmar, C., & Favrel, J. (2008). Framework for web service selection based on non-functional properties. International Journal of Web Services Practices, 3(2), 94–109.Google Scholar
  18. 18.
    Natschläger, C. (2011). Towards a BPMN 2.0 ontology (pp. 1–15).Google Scholar
  19. 19.
    Bruno, M., Canfora, G., Di Penta, M., & Scognamiglio, R. (2004). Using SVM and concept analysis to support web service classification and annotation.Google Scholar
  20. 20.
    Batra, S., & Bawa, S. (2010). Web service categorization using normalized similarity score. International Journal of Computer Theory and Engineering, 2(1), 1793–8201.Google Scholar
  21. 21.
    Castano, S., Ferrara, A., Montanelli, S., & Varese, G. (2011). Ontology and instance matching. In Knowledge-driven multimedia information extraction and ontology evolution (pp. 167–195). Berlin Heidelberg: SpringerGoogle Scholar
  22. 22.
    Yu, T., & Lin, K. J. (2005). Service selection algorithms for composing complex services with multiple QoS constraints. Service-Oriented Computing-ICSOC, 2005, 130–143.Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Université Lumière Lyon 2Lyon Cedex 07France

Personalised recommendations