Extracting Business Vocabularies from Business Process Models: SBVR and BPMN Standards-based Approach

Tomas Skersys1, Kestutis Kapocius1, Rimantas Butleris1 and Tomas Danikauskas1

  1. Kaunas University of Technology, Center of Information Systems Design Technologies, Studentu str. 50-313a, Kaunas, Lithuania
    Kaunas University of Technology, Department of Information Systems, Studentu str. 50-313a, Kaunas, Lithuania
    {tomas.skersys, kestutis.kapocius, rimantas.butleris, tomas.danikauskas}@ktu.lt

Abstract

Approaches for the analysis and specification of business vocabularies and rules are relevant topics in both Business Process Management and Information Systems Development disciplines. However, in common practice of Information Systems Development, the Business modeling activities still are of mostly empiric nature. In this paper, aspects of the approach for semi-automatic extraction of business vocabularies (BV) from business process models (BPM) are presented. The approach is based on novel business modeling-level OMG standards “Business Process Model and Notation” (BPMN) and “Semantics for Business Vocabularies and Business Rules” (SBVR), thus contributing to OMG’s vision of Model-Driven Architecture (MDA) and to model-driven development in general. The discussed extraction approach is evaluated against fully-automatic BPMN BPM → SBVR BV transformation that has been developed in parallel to the presented work.

Key words

SBVR, BPMN, business vocabulary, business process model, model-to-model transformation

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS140106079S

Publication information

Volume 11, Issue 4 (October 2014)
Special Issue on Advances in Systems, Modeling, Languages and Agents
Year of Publication: 2014
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Skersys, T., Kapocius, K., Butleris, R., Danikauskas, T.: Extracting Business Vocabularies from Business Process Models: SBVR and BPMN Standards-based Approach. Computer Science and Information Systems, Vol. 11, No. 4, 1515–1535. (2014)