A process ontology based approach to easing semantic ambiguity in business process modeling
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 57-77 |
Journal / Publication | Data and Knowledge Engineering |
Volume | 102 |
Online published | 28 Jan 2016 |
Publication status | Published - Mar 2016 |
Link(s)
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)
In: Data and Knowledge Engineering, Vol. 102, 03.2016, p. 57-77.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review