A process ontology based approach to easing semantic ambiguity in business process modeling

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

40 Scopus Citations
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Author(s)

  • Shaokun Fan
  • Zhimin Hua
  • Veda C. Storey
  • J. Leon Zhao

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)57-77
Journal / PublicationData and Knowledge Engineering
Volume102
Online published28 Jan 2016
Publication statusPublished - Mar 2016

Abstract

Business process modeling continues to increase in complexity, due, in part, to the dynamic business contexts and complicated domain concepts found in today's global economic environment. Although business process modeling is a critical step in workflow automation that powers business around the world, business process modelers often misunderstand domain concepts or relationships due to their lack of precise domain knowledge. Such semantic ambiguity affects the efficiency and quality of business process modeling. To address this problem, a Process Ontology Based Approach is proposed to ease semantic ambiguity by providing a means to capture rich, semantic information on complex business processes through domain specific ontologies. This approach is grounded in the Bunge-Shanks Framework to semantic disambiguation and evaluated using an expert survey as well as a controlled laboratory experiment.

Research Area(s)

  • Business process model, Domain process ontology, Semantic ambiguity, Conceptual modeling, Process Ontology Based Approach (POBA)

Citation Format(s)

A process ontology based approach to easing semantic ambiguity in business process modeling. / Fan, Shaokun; Hua, Zhimin; Storey, Veda C. et al.
In: Data and Knowledge Engineering, Vol. 102, 03.2016, p. 57-77.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review