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Consistent Abstraction of Business Processes Based on Constraints

  • Original Article
  • Published:
Journal on Data Semantics

Abstract

Exploring and understanding large business process models are important tasks in the context of business process management. In recent years, several techniques have been proposed for the abstraction of business processes. Automated abstraction techniques have been devised for verifying correctness and consistency of process models and for providing customised process views for business process analysts. Yet a goal-focused and semantic-based approach to generate purposeful abstraction of business processes is an open issue. We propose an approach for configuration of process abstractions with respect to a specific abstraction goal expressed as constraints on the correspondence relation between concrete and abstract process and process transformation operators. Our framework goes beyond simple structural aggregation and leverages domain-specific properties, taxonomies, meronymy, and flow criteria to generate a hierarchy of abstract process models. We outline the constraint-based framework, describe how rewriting-based abstraction mechanisms are embedded with consistency criteria guiding the search for abstractions, and show how notions of behaviour consistency can be utilised to obtain abstractions that conform to behavioural process inheritance criteria.

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Notes

  1. We assume that parameters are typed. A type can be inferred from the abstraction constraint C specified by the user.

  2. http://www.wordnet-online.com

  3. Satisfaction of the match-specific instance \(P(\theta )\) of the precondition formula \(P\) can be checked with respect to the concrete correspondence relation \(R\) and significance assumptions \(S\), as \(P(\theta )\), after evaluation of ground boolean expressions resulting from variable substitutions and simplification, contains only terms involving relation \(R\) and literals using predicate \(sign\). For abstraction objects where significance is not uniquely determined by \(\Gamma \) suitable assumptions may be made that match the operator’s prerequisites.

  4. http://dome.ggrossmann.com/

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Authors and Affiliations

  1. University of South Australia, Adelaide, SA, 5095, Australia

    Shamila Mafazi, Georg Grossmann, Wolfgang Mayer, Michael Schrefl & Markus Stumptner

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  1. Shamila Mafazi
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  2. Georg Grossmann
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  3. Wolfgang Mayer
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  4. Michael Schrefl
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  5. Markus Stumptner
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Correspondence to Shamila Mafazi.

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Mafazi, S., Grossmann, G., Mayer, W. et al. Consistent Abstraction of Business Processes Based on Constraints. J Data Semant 4, 59–78 (2015). https://doi.org/10.1007/s13740-014-0039-3

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  • DOI: https://doi.org/10.1007/s13740-014-0039-3

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