Discovering, analyzing and enhancing BPMN models using ProM

A.A. Kalenkova, M. Leoni, de, W.M.P. Aalst, van der

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    14 Citations (Scopus)
    62 Downloads (Pure)


    Process mining techniques relate observed behavior to modeled behavior, e.g., the automatic discovery of a process model based on an event log. Process mining is not limited to process discovery and also includes conformance checking and model enhancement. Conformance checking techniques are used to diagnose the deviations of the observed behavior as recorded in the event log from some process model. Model enhancement allows to extend process models using additional perspectives, conformance and performance information. In recent years, BPMN (Business Process Model and Notation) 2.0 has become a de facto standard for modeling business processes in industry. This paper presents the BPMN support current in ProM. ProM is the most known and used open-source process mining framework. ProM’s functionalities of discovering, analyzing and enhancing BPMN models are discussed. Support of the BPMN 2.0 standard will help ProM users to bridge the gap between formal models (such as Petri nets, causal nets and others) and process models used by practitioners.
    Original languageEnglish
    Title of host publicationBPM Demo Sessions 2014 (co-located with BPM 2014, Eindhoven, The Netherlands, September 20, 2014)
    EditorsL. Limonad, B. Weber
    Publication statusPublished - 2014
    EventBPM Demo Sessions 2014 (BPMD 2014), September 10, 2014, Eindhoven, The Netherlands - Eindhoven, Netherlands
    Duration: 10 Sep 201410 Sep 2014

    Publication series

    NameCEUR Workshop Proceedings
    ISSN (Print)1613-0073


    OtherBPM Demo Sessions 2014 (BPMD 2014), September 10, 2014, Eindhoven, The Netherlands
    Abbreviated titleBPMD 2014
    OtherCo-located with the 12th International Conference on Business Process Management (BPM 2014)

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