Abstract

http://ssrn.com/abstract=2030881
 


 



Modeling Languages for Business Processes and Business Rules: A Representational Analysis


Michael Zur Muehlen


Stevens Institute of Technology - Wesley J. Howe School of Technology Management

Marta Indulska


University of Queensland - Business School

March 29, 2009

Information Systems 35 (2010) pp. 379–390

Abstract:     
Process modeling and rule modeling languages are both used to document organizational policies and procedures. To date, their synergies and overlap are under-researched. Understanding the relationship between the two modeling types would allow organizations to maximize synergies, avoid content duplication, and thus reduce their overall modeling effort. In this paper we use the Bunge-Wand-Weber (BWW) representation theory to compare the representation capabilities of process and rule modeling languages. We perform a representational analysis of four rule modeling specifications: The Simple Rule Markup Language (SRML), the Semantic Web Rules Language (SWRL), the Production Rule Representation (PRR) and the Semantics of Business Vocabulary and Business Rules (SBVR) specification. We compare their BWW representation capabilities with those of four popular conceptual process modeling languages. In our analysis we focus on the aspects of maximum ontological completeness and minimum ontological overlap. The outcome of this study shows that no single language is internally complete with respect to the BWW representation model. We also show that a combination of two languages, in particular SRML and BPMN, appears to be better suited for combined process and rule modeling than any of these modeling languages used independently.

Number of Pages in PDF File: 12

Keywords: business process modeling, business rule modeling, business process management, Representation theory, BWW, BPMN, SBVR, PRR, SRML, SWRL

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Date posted: April 11, 2012  

Suggested Citation

zur Muehlen, Michael and Indulska, Marta, Modeling Languages for Business Processes and Business Rules: A Representational Analysis (March 29, 2009). Information Systems 35 (2010) pp. 379–390. Available at SSRN: http://ssrn.com/abstract=2030881

Contact Information

Michael Zur Muehlen (Contact Author)
Stevens Institute of Technology - Wesley J. Howe School of Technology Management ( email )
Hoboken, NJ 07030
United States
2012168293 (Phone)
Marta Indulska
University of Queensland - Business School ( email )
Brisbane, Queensland 4072
Australia
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