Effects of Semantic Quality in Business Process Modeling

In contrast to the increasing meaning of business process management (BPM), there is a lack of knowledge about processes that impedes their analysis, implementation, and execution in business process management systems (BPMS). In this context, process modeling is an opportunity to capture process knowledge. Nevertheless, models are incomplete concerning semantic completeness. Therefore, ontologies as explicit and formal specification are used to enrich models semantically to achieve a high degree of semantic quality, model efficiency and effectiveness. But also ontology engineering needs models to describe the underlying discourse of universe. For this reason, it is the paper's goal to examine and compare the Resource Event Agent Model (REA) with respect to semantic quality, model effectiveness, and -efficiency in data modeling for ontologies. Moreover, the paper addresses the research question, if REA enables an effective modeling to reduce the precision deficit and complexity in BPM.