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Breaking Down Barriers with Knowledge Graphs: Data Integration for Cross-Organizational Process Mining | SpringerLink
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Breaking Down Barriers with Knowledge Graphs: Data Integration for Cross-Organizational Process Mining

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  • First Online:
Process Mining Workshops (ICPM 2023)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 503))

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Abstract

Cross-organizational process mining (coPM) with data from at least two organizations assists cooperating organizations in optimizing their operations by enabling an in-depth and continuous process analysis. As coPM faces unique challenges and is rarely applied, we followed a design science-based approach and developed a three-step extension to the PM project methodology to integrate data across organizational boundaries. Each organization first creates a local event data knowledge graph (KG). Second, a trusted third party integrates all local KGs into a global KG. Third, a federated event log and process knowledge are retrieved for coPM analysis. Overall, we present the first version of a methodology to support data integration for coPM, thereby assisting researchers and practitioners in unlocking value potentials from coPM analysis.

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Notes

  1. 1.

    https://www.ietf.org/rfc/rfc2396.txt.

  2. 2.

    https://www.w3.org/TR/2014/REC-rdf11-concepts-20140225/.

  3. 3.

    https://www.w3.org/TR/2012/REC-owl2-overview-20121211/.

  4. 4.

    https://www.w3.org/TR/shacl/.

  5. 5.

    https://www.w3.org/TR/2008/REC-rdf-sparql-query-20080115/.

  6. 6.

    The example is publicly available in a GitHub repository (https://anonymous.4open.science/r/e-pm2-data-5D3B).

  7. 7.

    https://github.com/RMLio/rmlmapper-java.

  8. 8.

    https://www.w3.org/TR/2013/REC-prov-O-20130430/.

  9. 9.

    https://www.w3.org/TR/2008/WD-skos-reference-20080829/skos.html.

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Acknowledgments

This work was supported by the Bayerisches Verbundforschungsprogramm (BayVFP) through the KIWI project (grant no. DIK0318/03).

Author information

Authors and Affiliations

  1. Munich Airport, Munich, Germany

    Julian Rott

  2. Technical University of Munich, Garching, Germany

    Julian Rott & Helmut Krcmar

  3. Fraunhofer IIS, Nürnberg, Germany

    Rene Dorsch, Michael Freund & Andreas Harth

  4. University of Applied Sciences Landshut, Landshut, Germany

    Markus Böhm

Authors
  1. Julian Rott
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  2. Rene Dorsch
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  3. Michael Freund
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  4. Markus Böhm
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  5. Andreas Harth
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  6. Helmut Krcmar
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Corresponding author

Correspondence to Julian Rott .

Editor information

Editors and Affiliations

  1. KU Leuven, Leuven, Belgium

    Johannes De Smedt

  2. University of Haifa, Haifa, Israel

    Pnina Soffer

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Rott, J., Dorsch, R., Freund, M., Böhm, M., Harth, A., Krcmar, H. (2024). Breaking Down Barriers with Knowledge Graphs: Data Integration for Cross-Organizational Process Mining. In: De Smedt, J., Soffer, P. (eds) Process Mining Workshops. ICPM 2023. Lecture Notes in Business Information Processing, vol 503. Springer, Cham. https://doi.org/10.1007/978-3-031-56107-8_38

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  • DOI: https://doi.org/10.1007/978-3-031-56107-8_38

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  • Online ISBN: 978-3-031-56107-8

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