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Mining Expressive and Executable Resource-Aware Imperative Process Models

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Enterprise, Business-Process and Information Systems Modeling (BPMDS 2018, EMMSAD 2018)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 318))

Abstract

Process mining extracts relevant information on executed business processes from historical data stored in event logs. The data typically available include the activities executed, temporal information and the resources in charge of their execution. With such data, the functional, behavioural and organisational perspectives of a process can be discovered. Many existing process mining approaches are capable of generating representations involving the first two perspectives with all types of processes. The extraction of simple and complex resource assignment rules has also been tackled with declarative process models. However, it is noticeable that despite imperative notations like BPMN are mostly used for process modelling nowadays, the existing process mining approaches for enriching such models with resource assignments cannot discover rules like separation of duties and do not produce executable resource-aware process models. In this paper we present an approach for mining resource-aware imperative process models that uses an expressive resource assignment language (RALph) with the de-facto standard notation BPMN. The organisational perspective of the resulting models can be automatically analysed thanks to the formal semantics of RALph. The method has been implemented and tested with a real use case.

This work was funded by the Austrian Science Fund (FWF) - grant V 569-N31 (PRAIS).

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Notes

  1. 1.

    http://www.promtools.org/doku.php.

  2. 2.

    BPMN Viewer and Editor, https://bpmn.io.

  3. 3.

    https://www.signavio.com.

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Author information

Authors and Affiliations

  1. Vienna University of Economics and Business, Vienna, Austria

    Cristina Cabanillas & Jan Mendling

  2. University of Bayreuth, Bayreuth, Germany

    Stefan Schönig & Christian Sturm

Authors
  1. Cristina Cabanillas
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  2. Stefan Schönig
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  3. Christian Sturm
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  4. Jan Mendling
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Corresponding author

Correspondence to Cristina Cabanillas .

Editor information

Editors and Affiliations

  1. University of Duisburg-Essen, Essen, Germany

    Jens Gulden

  2. University of Haifa, Haifa, Israel

    Iris Reinhartz-Berger

  3. Munich University of Applied Sciences, Munich, Germany

    Rainer Schmidt

  4. INESC-ID, University of Lisbon, Lisbon, Portugal

    Sérgio Guerreiro

  5. Luxembourg Institute of Science and Technology, Esch-sur-Alzette, Luxembourg

    Wided Guédria

  6. Saint Louis University, St. Louis, Missouri, USA

    Palash Bera

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Cabanillas, C., Schönig, S., Sturm, C., Mendling, J. (2018). Mining Expressive and Executable Resource-Aware Imperative Process Models. In: Gulden, J., Reinhartz-Berger, I., Schmidt, R., Guerreiro, S., Guédria, W., Bera, P. (eds) Enterprise, Business-Process and Information Systems Modeling. BPMDS EMMSAD 2018 2018. Lecture Notes in Business Information Processing, vol 318. Springer, Cham. https://doi.org/10.1007/978-3-319-91704-7_1

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  • DOI: https://doi.org/10.1007/978-3-319-91704-7_1

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  • Print ISBN: 978-3-319-91703-0

  • Online ISBN: 978-3-319-91704-7

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