Fuzzy-EPC Markup Language: XML Based Interchange Formats for Fuzzy Process Models

  • Oliver Thomas
  • Thorsten Dollmann
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 255)


Recent research has led to proposals for the integration of fuzzy based information and decision rules in business process models with use of concepts based on the fuzzy set theory. While the proposed fuzzy-EPCs provide an adequate method for the conceptual representation of fuzzy business process models, the issue of exchanging and transforming such models, together with its enclosed executable components with other dedicated information systems, such as workflow management systems and fuzzy modeling tools has not yet been approached. As a first step in this direction, our paper proposes a machine-readable fuzzy-EPC representation in XML based on the EPC Markup Language (EPML). We will start with the formal fuzzy-EPC syntax definition and then introduce our extensions to EPML. An application scenario will next highlight the potential and future application areas of the fuzzy-EPC schema.


Membership Function Business Process Fuzzy System Linguistic Variable Customer Order 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Adam, O., Thomas, O.: A Fuzzy Based Approach to the Improvement of Business Processes. In: Castellanos, M., Weijters, T. (eds.) BPI 2005: Workshop on Business Process Intelligence, Nancy, France, September 5, pp. 25–35 (2005)Google Scholar
  2. 2.
    Adam, O., Thomas, O., Loos, P.: Soft Business Process Intelligence – Verbesserung von Geschäftsprozessen mit Neuro-Fuzzy-Methoden. In: Lehner, F., Nösekabel, H., Kleinschmidt, P. (eds.) Multikonferenz Wirtschaftsinformatik 2006: Band 2, GITO, Berlin, pp. 57–69 (2006)Google Scholar
  3. 3.
    Adam, O., Thomas, O., Martin, G.: Fuzzy Enhanced Process Management for the Industrial Order Handling. In: Scheer, A.-W. (ed.) Proceedings: 5th International Conference; The Modern Information Technology in the Innovation Processes of the Industrial Enterprises, MITIP 2003, German Research Center for Artificial Intelligence, Saarbruecken/Germany, September 4-6, Universität des Saarlandes, Saarbrücken, pp. 15–20 (2003)Google Scholar
  4. 4.
    Adam, O., Thomas, O., Martin, G.: Fuzzy Workflows - Enhancing Workflow Management with Vagueness. In: EURO/INFORMS Istanbul 2003 Joint International Meeting, Istanbul, July 06-10 (2003)Google Scholar
  5. 5.
    Adam, O., Thomas, O., Vanderhaeghen, D.: Fuzzy-Set-Based Modeling of Business Process Cases. In: Richter, M., et al. (eds.) ICCBR 2005: 6th International Conference on Case-Based Reasoning, Workshop 4: Similarities - Processes - Workflows, Chicago, Illinois, IL, August 23-26, pp. 251–260 (2005)Google Scholar
  6. 6.
    Becker, J., Rehfeldt, M., Turowski, K., Vering, O.: A Fuzzy Approach to a Customer-Oriented Sales Workflow. In: Steele, N.C. (ed.) ISFL 1997: Second International ICSC Symposium on Fuzzy Logic and Applications, Swiss Federal Institute of Technology Zurich, Switzerland, February 12-14, pp. 370–376. ICSC Academic Press, Zürich (1997)Google Scholar
  7. 7.
    Cao, T., Sanderson, A.C.: Task sequence planning using fuzzy Petri nets. In: International conference on systems, man and cybernetics, conference proceedings: decision aiding for complex systems, Charlottesville, VA, October 13-16, pp. 349–354. IEEE Computer Society Press, Los Alamitos (1991)Google Scholar
  8. 8.
    de Soto, A.R., Capdevila, C.A., Fernández, E.C.: Fuzzy Systems and Neural Networks XML Schemas for Soft Computing. Mathware and Soft Computing 10(2-3), 43–56 (2003)zbMATHGoogle Scholar
  9. 9.
    Forte, M.: Unschärfen in Geschäftsprozessen. Weißensee, Berlin (2002)Google Scholar
  10. 10.
    Gaurav, A., Alhajj, R.: Incorporating fuzziness in XML and mapping fuzzy relational data into fuzzy XML. In: Haddad, H. (ed.) Proceedings of the 2006 ACM Symposium on Applied Computing (SAC), Dijon, France, April 23-27, pp. 456–460. ACM, New York (2006)CrossRefGoogle Scholar
  11. 11.
    Günther, R., Lipp, H.-P.: A Fuzzy Petri Net Concept for Complex Decision Making Processes in Production Control. In: Zimmermann, H.-D. (ed.) Proceedings of the 1st European Congess on Fuzzy and Intelligent Technologies, EUFIT 1993, Aachen, Germany, September 7-10, Verl. der Augustinus Buchhandlung, Aachen, pp. 290–295 (1993)Google Scholar
  12. 12.
    Hüsselmann, C.: Fuzzy-Geschäftsprozessmanagement. Eul, Lohmar (2003)Google Scholar
  13. 13.
    Hüsselmann, C., Adam, O., Thomas, O.: Gestaltung und Steuerung wissensintensiver Geschäftsprozesse durch die Nutzung unscharfen Wissens. In: Reimer, U., et al. (eds.) WM 2003: Professionelles Wissensmanagement - Erfahrungen und Visionen: Beiträge der 2. Konferenz Professionelles Wissensmanagement - Erfahrungen und Visionen, April 2-4, pp. 343–350. Köllen, Bonn (2003) (in Luzern)Google Scholar
  14. 14.
    IBM (ed.): ABLE Rule Language: User’s Guide and Reference, Version 2.3.0. IBM Corporation (2005)Google Scholar
  15. 15.
    Jiwani, A., Alimohamed, Y., Spence, K., Özyer, T., Alhajj, R.: Fuzzy XML Model for Representing Fuzzy Relational Databases in Fuzzy XML Format. In: Manolopoulos, Y., et al. (eds.) ICEIS 2006 - Proceedings of the Eighth International Conference on Enterprise Information Systems: Databases and Information Systems Integration, Paphos, Cyprus, May 23-27, pp. 163–168 (2006)Google Scholar
  16. 16.
    Kindler, E.: On the semantics of EPCs: Resolving the vicious circle. Data & Knowledge Engineering 56(1), 23–40 (2006)CrossRefGoogle Scholar
  17. 17.
    Lee, J., Fanjiang, Y.Y.: Modeling imprecise requirements with XML. Information and Software Technology 45(7), 445–460 (2003)CrossRefGoogle Scholar
  18. 18.
    Lipp, H.-P.: Anwendung eines Fuzzy Petri Netzes zur Beschreibung von Koordinationssteuerungen in komplexen Produktionssystemen. Wissenschaftliche Zeitschrift der Technischen Universität Karl-Marx-Stadt 24(5), 633–639 (1982)Google Scholar
  19. 19.
    Ma, Z.: Fuzzy Database Modeling with XML. Springer, Berlin (2005)zbMATHGoogle Scholar
  20. 20.
    Ma, Z., Yan, L.: Fuzzy XML data modeling with the UML and relational data models. Data & Knowledge Engineering 63(3), 970–994 (2007)CrossRefMathSciNetGoogle Scholar
  21. 21.
    Mendling, J., Nüttgens, M.: EPC Markup Language (EPML) - An XML-Based Interchange Format for Event-Driven Process Chains (EPC). ISeB 4(3), 245–263 (2006)CrossRefGoogle Scholar
  22. 22.
    Rehfeldt, M.: Koordination der Auftragsabwicklung: Verwendung von unscharfen Informationen. DUV, Wiesbaden (1998)Google Scholar
  23. 23.
    Rehfeldt, M., Turowski, K.: Impact on Integrated Information Systems through Fuzzy Technology. In: Zimmermann, H.-J. (ed.) Proceedings / EUFIT 1994, Second European Congress on Intelligent Techniques and Soft Computing: Aachen, Augustinus, Aachen, September 20-23. ELITE Foundation, pp. 1637–1645 (1994)Google Scholar
  24. 24.
    Rehfeldt, M., Turowski, K.: A Fuzzy Distributed Object-Oriented Database System as a Basis for a Workflow Management System. In: Proceedings of the sixth International Fuzzy Systems Association world congress, IFSA 1995, São Paulo, Brazil, July 21-28. NTIS, Springfield (1995)Google Scholar
  25. 25.
    Rehfeldt, M., Turowski, K.: Anticipating Coordination in Distributed Information Systems through Fuzzy Information. In: Zimmermann, H.-J. (ed.) Proceedings / EUFIT 1995, Third European Congress on Intelligent Techniques and Soft Computing: Aachen, Germany, pp. 1774–1779. Verl. Mainz, Wissenschaftsverlag, Aachen (1995)Google Scholar
  26. 26.
    Rehfeldt, M., Turowski, K.: A Tool-supported Distributed Application of Fuzzy Logic in Order Processing. In: Jamshidi, M., Junku, Y., Dauchez, P. (eds.) Proceedings of the World Automation Congress (WAC 1996), Intelligent automation and control: Recent trends in development and applications, Montpellier, France, May 28-30, pp. 585–589. TSI Press, Albuquerque (1996)Google Scholar
  27. 27.
    Rehfeldt, M., Turowski, K.: Fuzzy Objects in Production Planning and Control. In: Zimmermann, H.-J. (ed.) Proceedings / EUFIT 1996, Fourth European Congress on Intelligent Techniques and Soft Computing, Aachen, Germany, September 2-5. ELITE Foundation, pp. 1985–1989. Verl. Mainz, Wissenschaftsverlag, Aachen (1996)Google Scholar
  28. 28.
    Rehfeldt, M., Turowski, K.: A Flexible Java-based Fuzzy Kernel for Business Applications. In: Alpaydin, E. (ed.) International ICSC symposium on engineering of intelligent systems: EIS 1998, pp. 204–209. ICSC Academic Press, London (1998)Google Scholar
  29. 29.
    Rosemann, M., van der Aalst, W.M.P.: A configurable reference modelling language. Information Systems 32(1), 1–23 (2007)CrossRefGoogle Scholar
  30. 30.
    Rozinat, A., van der Aalst, W.M.P.: Decision Mining in Business Processes. In BPM Center Report, BPM-06-10, Eindhoven University of Technology (2006)Google Scholar
  31. 31.
    Sanchez, E. (ed.): Fuzzy Logic and the Semantic Web. Elsevier, Amsterdam (2006)zbMATHGoogle Scholar
  32. 32.
    Scheer, A.-W.: ARIS - business process frameworks, 2., completely rev. and enl. ed. Springer, Berlin (1998)Google Scholar
  33. 33.
    Scheer, A.-W.: ARIS - business process modeling. 2., completely rev. and enl. ed. Springer, Berlin (1999)Google Scholar
  34. 34.
    Scheer, A.-W., Thomas, O., Adam, O.: Process Modeling Using Event-driven Process Chains. In: Dumas, M., van der Aalst, W.M.P., ter Hofstede, A.H.M. (eds.) Process-aware Information Systems: Bridging People and Software through Process Technology, pp. 119–145. Wiley, Hoboken (2005)CrossRefGoogle Scholar
  35. 35.
    Srinivasan, P., Gracanin, D.: Approximate Reasoning with Fuzzy Petri Nets. In: Second IEEE International Conference on Fuzzy Systems, San Francisco, California, March 28-April 1, pp. 396–401. IEEE Computer Society, Piscataway (1993)CrossRefGoogle Scholar
  36. 36.
    Straccia, U.: A Fuzzy Description Logic for the Semantic Web. In: Sanchez, E. (ed.) Fuzzy Logic and the Semantic Web, pp. 73–90. Elsevier, Amsterdam (2006)Google Scholar
  37. 37.
    Thomas, O., Adam, O., Leyking, K., Loos, P.: A Fuzzy Paradigm Approach for Business Process Intelligence. In: IEEE Joint Conference on E-Commerce Technology (CEC 2006) and Enterprise Computing, E-Commerce and E-Services (EEE 2006), San Francisco, California, June 26-29, pp. 206–213. IEEE Computer Society Press, Los Alamitos (2006)Google Scholar
  38. 38.
    Thomas, O., Adam, O., Loos, P.: Using Reference Models for Business Process Improvement: A Fuzzy Paradigm Approach. In: Abramowicz, W., Mayr, H.C. (eds.) Business Information Systems: 9th International Conference on Business Information Systems (BIS 2006), Klagenfurt, Austria, May 31-June 2, pp. 47–57. Köllen, Bonn (2006)Google Scholar
  39. 39.
    Thomas, O., Adam, O., Seel, C.: A fuzzy based approach to the management of agile processes. In: Althoff, K.-D., et al. (eds.) WM2005: Professional Knowledge Management Experiences and Visions: Contributions to the 3rd Conference Professional Knowledge Management Experiences and Visions, Proceedings, Kaiserslautern, April 10-13, DFKI GmbH, Kaiserslautern (2005)Google Scholar
  40. 40.
    Thomas, O., Adam, O., Seel, C.: Business Process Management with Vague Data. In: Proceedings: DEXA 2005: Sixteenth International Workshop on Database and Expert Systems Applications, Copenhagen, Denmark, August 22-26, pp. 962–966. IEEE Computer Society Press, Los Alamitos (2005)Google Scholar
  41. 41.
    Thomas, O., Dollmann, T.: Towards the Interchange of Fuzzy-EPCs: An XML-based Approach for Fuzzy Business Process Engineering. In: Bichler, M., et al. (eds.) Multikonferenz Wirtschaftsinformatik 2008, pp. 1999–2010. GITO, Berlin (2008)Google Scholar
  42. 42.
    Thomas, O., Dollmann, T., Loos, P.: Towards Enhanced Business Process Models Based on Fuzzy Attributes and Rules. In: Proceedings of the 13th Americas Conference on Information Systems, Keystone, Colorado, USA, August 09-12. AIS, Atlanta (2007)Google Scholar
  43. 43.
    Thomas, O., Dollmann, T., Loos, P.: Rules Integration in Business Process Models – A Fuzzy Oriented Approach. Enterprise Modelling and Information Systems Architecures 3(2), 18–30 (2008)Google Scholar
  44. 44.
    Tietze, M.: Einsatzmöglichkeiten der Fuzzy-Set-Theorie zur Modellierung von Unschärfe in Unternehmensplanspielen. Unitext, Göttingen (1999)Google Scholar
  45. 45.
    Tiwari, A., Turner, C.J., Majeed, B.: A review of business process mining: state-of-the-art and future trends. Business Process Management Journal 14(1), 5–22 (2008)CrossRefGoogle Scholar
  46. 46.
    Tseng, C., Khamisy, W.: XML Schema for Fuzzy Systems, Computational Intelligence Lab, SJSU (2006), (accessed 3 March 2006)
  47. 47.
    Tseng, C., Khamisy, W., Vu, T.: Universal fuzzy system representation with XML. Computer Standards & Interfaces 28(2), 218–230 (2005)CrossRefGoogle Scholar
  48. 48.
    Turowski, K., Weng, U.: Representing and processing fuzzy information: an XML-based approach. Knowledge-Based Systems 15(1-2), 67–75 (2002)CrossRefGoogle Scholar
  49. 49.
    Valette, R., Courvoisier, M.: Petri nets and Artificial Intelligence. In: Zurawski, R., Dillon, T.S. (eds.) IEEE International Workshop on Emerging Technologies and Factory Automation: Technology for the intelligent factory, World Congress Centre, Melbourne, Australia, August 11 - 14, pp. 218–238. CRL Publishing, Aldershot (1992)Google Scholar
  50. 50.
    von Uthmann, C.: Improving the Use of Petri Nets for Business Process Modeling. Westfälische Wilhelms-Universität, Münster (1999)Google Scholar
  51. 51.
    Witte, R.: Architektur von Fuzzy-Informationssystemen. Books on Demand, Norderstedt (2002)Google Scholar
  52. 52.
    Zimmermann, H.-J., Angenstenberger, J., Lieven, K., Weber, R. (eds.): Fuzzy-Technologien: Prinzipien, Werkzeuge, Potentiale. VDI-Verl, Düsseldorf (1993)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Oliver Thomas
    • 1
  • Thorsten Dollmann
    • 2
  1. 1.Institute of Information Management and Corporate Governance, Chair in Information Management and Information SystemsUniversity of OsnabrückOsnabrückGermany
  2. 2.Institute for Information Systems (IWi) The German Research Center for Artificial Intelligence (DFKI)Saarland UniversitySaarbrückenGermany

Personalised recommendations