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International Conference on Business Process Management

BPM 2016: Business Process Management Workshops pp 583–594Cite as

Business Process Models for Visually Navigating Process Execution Data

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 256))

Abstract

To analyze large amounts of data, visual analysis tools offer filter mechanisms for drilling down into multi-dimensional information spaces, or slicing and dicing them according to given criteria. This paper introduces an analysis approach for navigating multi-dimensional process instance execution logs based on business process models. By visually selecting parts of a business process model, a set of available log entries is filtered to include only those entries that result from execution instances of the selected process branches. Using this approach allows to exploratively navigate through process execution logs and analyze them according to the causal-temporal relationships encoded in the underlying business process model. The business process models used by the approach can either be created using model editors, or be statistically derived using process mining techniques. We exemplify our approach with a prototypical implementation.

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Author information

Authors and Affiliations

  1. University of Duisburg-Essen, Universitätsstr. 9, 45141, Essen, Germany

    Jens Gulden

  2. Middlesex University London, The Burroughs, London, NW4 4BT, UK

    Simon Attfield

Authors
  1. Jens Gulden
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  2. Simon Attfield
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Corresponding author

Correspondence to Jens Gulden .

Editor information

Editors and Affiliations

  1. Institute of Databases and Information Systems, University of Ulm, Ulm, Germany

    Manfred Reichert

  2. Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Hajo A. Reijers

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© 2016 Springer International Publishing Switzerland

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Gulden, J., Attfield, S. (2016). Business Process Models for Visually Navigating Process Execution Data. In: Reichert, M., Reijers, H. (eds) Business Process Management Workshops. BPM 2016. Lecture Notes in Business Information Processing, vol 256. Springer, Cham. https://doi.org/10.1007/978-3-319-42887-1_47

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  • DOI: https://doi.org/10.1007/978-3-319-42887-1_47

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42886-4

  • Online ISBN: 978-3-319-42887-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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