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A technique for discovering BPMN collaboration diagrams

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Abstract

The process mining domain is actively supported by techniques and tools addressing the discovery of single-participant business processes. In contrast, approaches for discovering collaboration models out of distributed data stored by multiple interacting participants are lacking. In this context, we propose a novel technique for discovering collaboration models from sets of event logs that include data about participants’ interactions. The technique discovers each participant’s process through already available algorithms introduced by the process mining community. Then, it analyzes the logs to extract information on the exchange of messages to automatically combine the discovered processes into a collaboration model representing the distributed system’s behavior and providing analytics on the interactions. The technique has been implemented in a tool evaluated via several experiments on different application domains.

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Notes

  1. This threshold is decided empirically for this specific case study.

  2. https://pm4py.fit.fraunhofer.de/.

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  4. https://www.xes-standard.org/openxes/start.

  5. https://docs.camunda.org.

  6. https://docs.ros.org/en/foxy.

  7. https://data.4tu.nl.

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Acknowledgements

The research underlying this paper was supported by the PNRR MUR Project ECS_00000041-VITALITY.

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Authors and Affiliations

  1. School of Science and Technology, University of Camerino, Camerino, Italy

    Flavio Corradini, Sara Pettinari, Barbara Re & Lorenzo Rossi

  2. Dipartimento di Statistica, Informatica, Applicazioni, University of Florence, Florence, Italy

    Francesco Tiezzi

Authors
  1. Flavio Corradini
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  2. Sara Pettinari
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  3. Barbara Re
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  4. Lorenzo Rossi
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  5. Francesco Tiezzi
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Correspondence to Lorenzo Rossi.

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Communicated by Selmin Nurcan and Rainer Schmidt.

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Corradini, F., Pettinari, S., Re, B. et al. A technique for discovering BPMN collaboration diagrams. Softw Syst Model (2024). https://doi.org/10.1007/s10270-024-01153-5

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