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Extracting Event Data from Document-Driven Enterprise Systems

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Advanced Information Systems Engineering (CAiSE 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13901))

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Abstract

The preparation of input event data is one of the most critical phases in process mining projects. Different frameworks have been developed to offer methodologies and/or supporting toolkits for data preparation. One of these frameworks, called OnProm, relies on sophisticated semantic technologies to extract event logs from relational databases. The toolkit consists of a series of general steps, meant to work on arbitrary, legacy databases. However, in many settings, the input database is not a legacy one but is structured with conceptually understandable object types and relationships that can be effectively employed to support business users in the extraction process. This is, for example, the case for document-driven enterprise systems. In this paper, we focus on this class of systems and propose a guided approach, erprep, to support a group of business and technical users in setting up OnProm with minimal effort. We demonstrate the approach in a real-life use case.

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Notes

  1. 1.

    The DL-Lite family provides the formal counterpart of the lightweight ontology language OWL 2 QL, standardized by the W3C [15].

  2. 2.

    See, e.g., the tools developed by Ontopic, https://ontopic.ai/.

  3. 3.

    History-tables closely relate to the notion of redo logs in databases, previously studied within process mining in [8].

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Author information

Authors and Affiliations

  1. Free University of Bozen-Bolzano, 39100, Bolzano, Italy

    Diego Calvanese & Marco Montali

  2. Umeå University, 90187, Umeå, Sweden

    Diego Calvanese

  3. Hasselt University, 3500, Hasselt, Belgium

    Mieke Jans

  4. Maastricht University, 6200, MD, Maastricht, Netherlands

    Mieke Jans

  5. Virtual Vehicle Research GmbH, 8010, Graz, Austria

    Tahir Emre Kalayci

Authors
  1. Diego Calvanese
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  2. Mieke Jans
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  3. Tahir Emre Kalayci
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  4. Marco Montali
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Corresponding author

Correspondence to Mieke Jans .

Editor information

Editors and Affiliations

  1. The University of Queensland, Brisbane, QLD, Australia

    Marta Indulska

  2. University of Haifa, Haifa, Israel

    Iris Reinhartz-Berger

  3. Universidad San Jorge, Zaragoza, Spain

    Carlos Cetina

  4. Universitat Politècnica de València, Valencia, Spain

    Oscar Pastor

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Calvanese, D., Jans, M., Kalayci, T.E., Montali, M. (2023). Extracting Event Data from Document-Driven Enterprise Systems. In: Indulska, M., Reinhartz-Berger, I., Cetina, C., Pastor, O. (eds) Advanced Information Systems Engineering. CAiSE 2023. Lecture Notes in Computer Science, vol 13901. Springer, Cham. https://doi.org/10.1007/978-3-031-34560-9_12

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  • DOI: https://doi.org/10.1007/978-3-031-34560-9_12

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