An experiment on an ontology-based support approach for process modeling

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• 作者：Jonas Bulegon Gassen ; ^a ; ^b ; ^{jbgassen@gmail.com} ; ^{jgassen@wu.ac.at} ; Jan Mendling^b ; Amel Bouzeghoub^c ; Luciné ; ia Heloisa Thom^a ; José ; Palazzo M. de Oliveira^a
• 关键词：Business process modeling ; Process of process modeling ; Ontologies ; Activity labels ; Cognitive load
• 刊名：Information and Software Technology
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：83
• 期：Complete
• 页码：94-115
• 全文大小：3737 K
• 卷排序：83

文摘

Context: Recent research discusses the use of ontologies, dictionaries and thesaurus as a means to improve activity labels of process models. However, the trade-off between quality improvement and extra effort is still an open question. It is suspected that ontology-based support could require additional effort for the modeler.Objective: In this paper, we investigate to which degree ontology-based support potentially increases the effort of modeling. We develop a theoretical perspective grounded in cognitive psychology, which leads us to the definition of three design principles for appropriate ontology-based support. The objective is to evaluate the design principles through empirical experimentation.Method: We tested the effect of presenting relevant content from the ontology to the modeler by means of a quantitative analysis. We performed controlled experiments using a prototype, which generates a simplified and context-aware visual representation of the ontology. It logs every action of the process modeler for analysis. The experiment refers to novice modelers and was performed as between-subject design with vs. without ontology-based support. It was carried out with two different samples.Results: Part of the effort-related variables we measured showed significant statistical difference between the group with and without ontology-based support. Overall, for the collected data, the ontology support achieved good results.Conclusion: We conclude that it is feasible to provide ontology-based support to the modeler in order to improve process modeling without strongly compromising time consumption and cognitive effort.