Visual modeling of business process compliance rules with the support of multiple perspectives

David Knuplesch, Manfred Reichert, Linh Thao Ly, Akhil Kumar, Stefanie Rinderle-Ma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

33 Scopus citations


A fundamental challenge for any process-aware information system is to ensure compliance of modeled and executed business processes with imposed compliance rules stemming from guidelines, standards and laws. Such compliance rules usually refer to multiple process perspectives including control flow, time, resources, data, and interactions with business partners. On one hand, compliance rules should be comprehensible for domain experts who must define and apply them. On the other, they should have a precise semantics such that they can be automatically processed. In this context, providing a visual compliance rule language seems promising as it allows hiding formal details and offers an intuitive way of modeling. So far, visual compliance rule languages have focused on the control flow perspective, but lack adequate support for the other perspectives. To remedy this drawback, this paper provides an approach that extends visual compliance rule languages with the ability to consider data, time, resources, and partner interactions when modeling business process compliance rules. Overall, this extension will foster business process compliance support in practice.

Original languageEnglish (US)
Title of host publicationConceptual Modeling - 32th International Conference, ER 2013, Proceedings
Number of pages15
StatePublished - 2013
Event32nd International Conference on Conceptual Modeling, ER 2013 - Hong Kong, China
Duration: Nov 11 2013Nov 13 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8217 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other32nd International Conference on Conceptual Modeling, ER 2013
CityHong Kong

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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