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PROVED: A Tool for Graph Representation and Analysis of Uncertain Event Data

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Application and Theory of Petri Nets and Concurrency (PETRI NETS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12734))

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Abstract

The discipline of process mining aims to study processes in a data-driven manner by analyzing historical process executions, often employing Petri nets. Event data, extracted from information systems (e.g. SAP), serve as the starting point for process mining. Recently, novel types of event data have gathered interest among the process mining community, including uncertain event data. Uncertain events, process traces and logs contain attributes that are characterized by quantified imprecisions, e.g., a set of possible attribute values. The PROVED tool helps to explore, navigate and analyze such uncertain event data by abstracting the uncertain information using behavior graphs and nets, which have Petri nets semantics. Based on these constructs, the tool enables discovery and conformance checking.

We thank the Alexander von Humboldt (AvH) Stiftung for supporting our research interactions.

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Notes

  1. 1.

    Available at https://github.com/proved-py/proved-core/.

  2. 2.

    Available at https://github.com/proved-py/proved-app/.

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Authors and Affiliations

  1. Chair of Process and Data Science (PADS) Department of Computer Science, RWTH Aachen University, Aachen, Germany

    Marco Pegoraro, Merih Seran Uysal & Wil M. P. van der Aalst

Authors
  1. Marco Pegoraro
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  2. Merih Seran Uysal
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  3. Wil M. P. van der Aalst
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Corresponding author

Correspondence to Marco Pegoraro .

Editor information

Editors and Affiliations

  1. Université de Genève, Carouge, Switzerland

    Didier Buchs

  2. Universitat Politècnica de Catalunya, Barcelona, Spain

    Josep Carmona

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Pegoraro, M., Uysal, M.S., van der Aalst, W.M.P. (2021). PROVED: A Tool for Graph Representation and Analysis of Uncertain Event Data. In: Buchs, D., Carmona, J. (eds) Application and Theory of Petri Nets and Concurrency. PETRI NETS 2021. Lecture Notes in Computer Science(), vol 12734. Springer, Cham. https://doi.org/10.1007/978-3-030-76983-3_24

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  • DOI: https://doi.org/10.1007/978-3-030-76983-3_24

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  • Online ISBN: 978-3-030-76983-3

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