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Software and Systems Modeling

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21-04-2016 | Theme Section Paper

A visual language for modeling multiple perspectives of business process compliance rules

Authors: David Knuplesch, Manfred Reichert

Published in: Software and Systems Modeling | Issue 3/2017

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Abstract

A fundamental challenge for enterprises is to ensure compliance of their business processes with imposed compliance rules stemming from various sources, e.g., corporate guidelines, best practices, standards, and laws. In general, a compliance rule may refer to multiple process perspectives including control flow, time, data, resources, and interactions with business partners. On one hand, compliance rules should be comprehensible for domain experts who must define, verify, and apply them. On the other, these rules should have a precise semantics to avoid ambiguities and enable their automated processing. Providing a visual language is advantageous in this context as it allows hiding formal details and offering an intuitive way of modeling the compliance rules. However, existing visual languages for compliance rule modeling have focused on the control flow perspective so far, but lack proper support for the other process perspectives. To remedy this drawback, this paper introduces the extended Compliance Rule Graph language, which enables the visual modeling of compliance rules with the support of multiple perspectives. Overall, this language will foster the modeling and verification of compliance rules in practice.

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In this paper, the notion of process perspective corresponds to a specific business process modeling dimension according to Businska [13].

Note that imperative process modeling approaches tend to (over-)specify business processes. Hence, they are not well suited for specifying declarative constraints and process compliance rules [31, 75, 83].

Note that we reconducted the experiment with the same environment in order to involve a larger number of subjects (42 subjects in the first run, 38 subjects in the second run).

A Kolmogorov–Smirnov test (p value 0.006) suggested not accepting the assumption of a normal distribution.

Interpretation of Cohen’s d: \(d \ge 0.8\) large effect, \(0.8 > d \ge 0.5\) medium effect, \(0.5 > d \ge 0.2\) small effect, \(d < 0.2\) trivial/no effect.

Note that the compliance checker visualizes eCRGs based on a layouting algorithm; i.e., positioning information from the modeling environment is not used.

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Title: A visual language for modeling multiple perspectives of business process compliance rules
Authors: David Knuplesch
Manfred Reichert
Publication date: 21-04-2016
Publisher: Springer Berlin Heidelberg
Published in: Software and Systems Modeling / Issue 3/2017
Print ISSN: 1619-1366
Electronic ISSN: 1619-1374
DOI: https://doi.org/10.1007/s10270-016-0526-0

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