Understanding Business Domain Models: The Effect of Recognizing Resource-Event-Agent Conceptual Modeling Structures

Understanding Business Domain Models: The Effect of Recognizing Resource-Event-Agent Conceptual Modeling Structures

Geert Poels
Copyright: © 2011 |Pages: 33
DOI: 10.4018/jdm.2011010104
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Abstract

In this paper, the author investigates the effect on understanding of using business domain models that are constructed with Resource-Event-Agent (REA) modeling patterns. First, the author analyzes REA modeling structures to identify the enabling factors and the mechanisms by means of which users recognize these structures in a conceptual model and description of an information retrieval and interpretation task. Based on this understanding, the author hypothesizes positive effects on model understanding for situations where REA patterns can be recognized in both task and model. An experiment is then conducted to demonstrate a better understanding of models with REA patterns compared to information equivalent models without REA patterns. The results of this experiment indicate that REA patterns can be recognized with minimal prior patterns training and that the use of REA patterns leads to models that are easier to understand for novice model users.
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The Resource-Event-Agent Ontology

The REA ontology has been accepted in August 2007 as the international ISO/IEC standard 15944-4, referred to as the Open-edi Business Transaction Ontology (OeBTO). Different reference models and methodologies for designing business services in e-collaboration contexts (e.g., the UN/CEFACT’s Modeling Methodology (UMM), the E-Commerce Integration Meta-Framework (ECIMF), the ISO/IEC 14662:1997 reference model for electronic data interchange) use REA as underlying business ontology for grounding the constructs of their modeling formalisms.

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