Mining Expressive and Executable Resource-Aware Imperative Process Models

Cristina Cabanillas Macias, Christian Sturm, Jan Mendling, Stefan Schönig

Publication: Chapter in book/Conference proceedingContribution to conference proceedings


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.
Original languageEnglish
Title of host publicationBPMDS/EMMSAD@CAiSE 2018
Editors Jens Gulden and Iris Reinhartz{-}Berger and Rainer Schmidt and S{\'{e}}rgio Guerreiro and Wided Gu{\'{e}}dria and Palash Bera
Place of PublicationTallinn
Pages3 - 18
Publication statusPublished - 2018

Austrian Classification of Fields of Science and Technology (ÖFOS)

  • 102015 Information systems
  • 102022 Software development

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