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Modeling Objectives of Knowledge Workers

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Business Process Management Workshops (BPM 2021)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 436))

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Abstract

Traditionally, business process models are imperative, limiting process behavior to a small set of variants. Purely imperative modeling languages are therefore unsuited for knowledge-intensive processes, which differ from case to case and are driven by knowledge workers. For this reason, declarative, data-centric, and hybrid approaches have been developed. However, in existing approaches, knowledge workers receive little support for late-goal modeling and subsequent planning of their actions. To address this issue, we present a model-driven approach that allows knowledge workers to specify objectives. Objectives are first order logic statements about a desired future execution state of a model’s case, regarding data and activities. Those logic expressions are a prerequisite for automated planning.

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Notes

  1. 1.

    https://github.com/bptlab/fCM-query-generator (2021/05/17).

  2. 2.

    https://www.merriam-webster.com/dictionary/objective (2021/04/27).

  3. 3.

    Source and documentation: https://github.com/bptlab/fCM-query-generator.

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Authors and Affiliations

  1. Hasso Plattner Institute, University of Potsdam, Prof.-Dr.-Helmert-Str. 2-3, 14482, Potsdam, Germany

    Stephan Haarmann, Anjo Seidel & Mathias Weske

Authors
  1. Stephan Haarmann
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  2. Anjo Seidel
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  3. Mathias Weske
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Corresponding author

Correspondence to Stephan Haarmann .

Editor information

Editors and Affiliations

  1. Sapienza University of Rome, Rome, Italy

    Andrea Marrella

  2. University of St. Gallen, St. Gallen, Switzerland

    Barbara Weber

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Haarmann, S., Seidel, A., Weske, M. (2022). Modeling Objectives of Knowledge Workers. In: Marrella, A., Weber, B. (eds) Business Process Management Workshops. BPM 2021. Lecture Notes in Business Information Processing, vol 436. Springer, Cham. https://doi.org/10.1007/978-3-030-94343-1_26

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  • DOI: https://doi.org/10.1007/978-3-030-94343-1_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-94342-4

  • Online ISBN: 978-3-030-94343-1

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