Semantic Evaluation of Business Processes Using SeMFIS

Abstract

This chapter discusses the evaluation of business processes in terms of semantics. For this purpose, a method providing a set of semantic process evaluation patterns is described. In order to make these patterns operational, the SeMFIS platform for engineering semantic annotations of conceptual models is used as a foundation. SeMFIS not only features a software platform based on the ADOxx metamodeling platform but also an open framework for the development of semantic information systems. SeMFIS is thus able to support the semantic process evaluation patterns on a technical level. In particular, the querying and scripting functionality contained in SeMFIS as well as its semantic annotation facilities are used together with business process models in BPMN notation, which are part of the SeMFIS standard distribution. As a proof of concept, a case study from the area of risk management is described in order to illustrate the practical application of SeMFIS when working with the semantic process evaluation patterns.

Keywords

Semantic process evaluation Business process management SeMFIS 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Baacke, L., Fitterer, R., Rohner, P., Stroh, F.: Using semantically annotated models for pattern-based process analysis. Arbeitsberichte des Instituts für Wirtschaftsinformatik der Universitaet St. Gallen, BE IWI/HNE/03 (2010)Google Scholar
  2. 2.
    Becker, J., Bergener, P., Raeckers, M., Weiss, B., Winkelmann, A.: Pattern-Based semi-automatic analysis of weaknesses in semantic business process models in the banking sector. In: ECIS’2010. AIS (2010)Google Scholar
  3. 3.
    Bergner, M.: Integrating natural language processing with semantic-based modeling. Master’s thesis, University of Vienna (2015)Google Scholar
  4. 4.
    Bork, D., Fill, H.G.: Formal aspects of enterprise modeling methods: a comparison framework. In: Proceedings of the 2014 47th International Conference on System Sciences. IEEE (2014)Google Scholar
  5. 5.
    Fill, H.G.: Design of semantic information systems using a model-based approach. In: AAAI Spring Symposium. AAAI (2009)Google Scholar
  6. 6.
    Fill, H.G.: On the conceptualization of a modeling language for semantic model annotations. In: LNBIP, vol. 83, pp. 134–148. Springer, London, UK (2011)Google Scholar
  7. 7.
    Fill, H.G.: Using semantically annotated models for supporting business process benchmarking. In: Grabis, J., Kirikova, M. (eds.) 10th International Conference on Perspectives in Business Informatics Research. LNBIP, vol. 90, pp. 29–43. Springer (2011)Google Scholar
  8. 8.
    Fill, H.G.: An approach for analyzing the effects of risks on business processes using semantic annotations. In: European Conference on Information Systems 2012. AIS (2012)Google Scholar
  9. 9.
    Fill, H.G.: SeMFIS: a tool for managing semantic conceptual models. In: Kern, H., Tolvanen, J.P., Bottoni, P. (eds.) Workshop on Graphical Modeling Language Development (2012)Google Scholar
  10. 10.
    Fill, H.G.: On the social network based semantic annotation of conceptual models. In: Buchmann, R., Kifor, C., Yu, J. (eds.) 7th International Conference on Knowledge Science, Engineering and Management, pp. 138–149. Springer (2014)Google Scholar
  11. 11.
    Fill, H.G.: Enabling risk analysis in conceptual models by using semantic annotations - case study for semantic-based modeling (2015). http://homepage.dke.univie.ac.at/fill/semfis/SeMFIS_Case_Study.pdf. Accessed 21 Aug 2015
  12. 12.
    Fill, H.G., Burzynski, P.: Integrating ontology models and conceptual models using a meta modeling approach. In: 11th International Protégé Conference (2009)Google Scholar
  13. 13.
    Fill, H.G., Hickl, S., Karagiannis, D., Oberweis, A., Schoknecht, A.: A formal specification of the horus modeling language using FDMM. In: International Conference on Business Informatics 2013. AIS (2013)Google Scholar
  14. 14.
    Fill, H.G., Karagiannis, D.: On the conceptualisation of modelling methods using the ADOxx meta modelling platform. Enterp. Model. Inf. Syst. Architect. 8(1), 4–25 (2013)CrossRefGoogle Scholar
  15. 15.
    Fill, H.G., Schremser, D., Karagiannis, D.: A generic approach for the semantic annotation of conceptual models using a service-oriented architecture. Int. J. Knowl. Manage. 9(1), 76–88 (2013)CrossRefGoogle Scholar
  16. 16.
    Fraser, M., Kumar, K., Vaishnavi, V.: Strategies for incorporating formal specifications in software development. Commun. ACM 37(10), 74–86 (1994)CrossRefGoogle Scholar
  17. 17.
    Gennari, J., Musen, M.A., Fergerson, R., Grosso, W., Crubezy, M., Eriksson, H., Noy, N., Tu, S.: The evolution of protege: an environment for knowledge-based systems development. Int. J. Hum Comput Stud. 58, 89–123 (2003)CrossRefGoogle Scholar
  18. 18.
    Giaglis, G.: A taxonomy of business process modeling and information systems modeling techniques. Int. J. Flex. Manuf. Syst. (2001)Google Scholar
  19. 19.
    Harel, D., Rumpe, B.: Modeling languages: syntax, semantics and all that stuff—part i: the basic stuff. Technical report MCS00-16, The Weizmann Institute of Science (2000)Google Scholar
  20. 20.
    Harmon, P., Wolf, C.: The state of business process management 2014. BP Trends Report, p. 54 (2014)Google Scholar
  21. 21.
    Herbst, J., Junginger, S., Kühn, H.: Simulation in financial services with the business process management system ADONIS. Society for Computer Simulation (1997)Google Scholar
  22. 22.
    Herbst, J., Karagiannis, D.: Integrating machine learning and workflow management to support acquisition and adaptation of workflow models. In: Proceedings of the 9th International Workshop on Database and Expert Systems Applications, pp. 745–752. IEEE (1998)Google Scholar
  23. 23.
    Höferer, P.: Achieving business process model interoperability using metamodels and ontologies. In: Oesterle, H., Schelp, J., Winter, R. (eds.) 15th European Conference on Information Systems (ECIS2007), pp. 1620–1631. University of St. Gallen (2007)Google Scholar
  24. 24.
    Johannsen, F., Fill, H.G.: Codification of knowledge in business process improvement projects. In: European Conference on Information Systems (ECIS’2014). AIS (2014)Google Scholar
  25. 25.
    Johannsen, F., Fill, H.G.: Supporting Knowledge elicitation and analysis for business process improvement through a modeling tool. In: International Conference on Business Informatics 2015. AIS (2015)Google Scholar
  26. 26.
    Krahn, H., Rumpe, B.: Towards enabling architectural refactorings through source code annotations. In: Mayr, H., Breu, R. (eds.) Modellierung 2006, vol. 82, pp. 203–212. GI-LNI (2006)Google Scholar
  27. 27.
    List, B., Korherr, B.: An Evaluation of Conceptual Business Process Modelling Languages. ACM, Dijon, France (2006)CrossRefGoogle Scholar
  28. 28.
    Mylopoulos, J.: Conceptual Modeling and Telos, pp. 49–68. Wiley (1992)Google Scholar
  29. 29.
    Oberweis, A., Sander, P.: Information system behavior specification by high level Petri nets. ACM Trans. Inf. Syst. 14(4), 380–420 (1996)CrossRefGoogle Scholar
  30. 30.
    Obrst, L.: Ontologies for semantically interoperable systems. In: Proceedings of the 12th International Conference on Information and Knowledge Management. ACM Press (2003)Google Scholar
  31. 31.
    Pedrinaci, C., Domingue, J.: Ontology-Based metrics computation for business process analysis. In: Hepp, M., Hinkelmann, K., Stojanovic, N. (eds.) 4th International Workshop on Semantic Business Process Management (SBPM2009). ACM (2009)Google Scholar
  32. 32.
    Schütte, R., Becker, J.: Subjektivitätsmanagement bei Informationsmodellen (German: Management of subjectivity for information models). In: Pohl, K., Schürr, A., Vossen, G. (eds.) Modellierung 98, vol. 9. GI-Workshop (1998)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.University of ViennaViennaAustria

Personalised recommendations