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Staged Configuration of Multi-perspectives Variants Based on a Generic Data Model

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Book cover Business Process Management Workshops (BPM 2011)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 100))

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Abstract

Usually, for a particular business process different variants exist in order to fulfill the individual requirements of the different users. The management of the process variability is an important aspect mainly during modeling which serves for the purpose of documentation. One common way to deal with variability is configuration. This paper presents a generic concept of a configurator which captures the characteristics of the process domain, inter alia the multi-perspectives of processes. One of the main contributions of this paper is intended to be a staged configuration process. The sequence of the partial decisions concerning the selection of a variant can be determined individually. In order to capture the process variability we developed a generic data model which empowers the derivation of variants based on a process model which integrates all possible variants.

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Author information

Authors and Affiliations

  1. Chair for Applied Computer Science, University of Bayreuth, Universitätsstr. 30, 95447, Bayreuth, Germany

    Stephanie Meerkamm

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  1. Stephanie Meerkamm
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Editor information

Editors and Affiliations

  1. University of Trento, Povo, Italy

    Florian Daniel

  2. CNAM-CEDRIC, Paris, France

    Kamel Barkaoui

  3. Vienna University of Technology, Vienna, Austria

    Schahram Dustdar

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Meerkamm, S. (2012). Staged Configuration of Multi-perspectives Variants Based on a Generic Data Model. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds) Business Process Management Workshops. BPM 2011. Lecture Notes in Business Information Processing, vol 100. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28115-0_31

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  • DOI: https://doi.org/10.1007/978-3-642-28115-0_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28114-3

  • Online ISBN: 978-3-642-28115-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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