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Understanding business domain models: the effect of recognizing resource-event-agent conceptual modeling structures

Geert Poels (UGent)
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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.
Keywords
Pattern Learning, Pattern Recognition, Model Understanding, Modeling Patterns, Enterprise Ontology, Conceptual Modeling, Business Domain Model, FRAMEWORK, SIMILARITY, COMPLEXITY, VALIDATION, PERFORMANCE, QUALITY, REPRESENTATION, ACCOUNTING MODEL, OPTIONAL PROPERTIES, INFORMATION-SYSTEMS

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Please use this url to cite or link to this publication:

Chicago
Poels, Geert. 2011. “Understanding Business Domain Models: The Effect of Recognizing Resource-event-agent Conceptual Modeling Structures.” Journal of Database Management 22 (1): 69–101.
APA
Poels, G. (2011). Understanding business domain models: the effect of recognizing resource-event-agent conceptual modeling structures. JOURNAL OF DATABASE MANAGEMENT, 22(1), 69–101.
Vancouver
1.
Poels G. Understanding business domain models: the effect of recognizing resource-event-agent conceptual modeling structures. JOURNAL OF DATABASE MANAGEMENT. 2011;22(1):69–101.
MLA
Poels, Geert. “Understanding Business Domain Models: The Effect of Recognizing Resource-event-agent Conceptual Modeling Structures.” JOURNAL OF DATABASE MANAGEMENT 22.1 (2011): 69–101. Print.
@article{1095745,
  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.},
  author       = {Poels, Geert},
  issn         = {1063-8016},
  journal      = {JOURNAL OF DATABASE MANAGEMENT},
  keyword      = {Pattern Learning,Pattern Recognition,Model Understanding,Modeling Patterns,Enterprise Ontology,Conceptual Modeling,Business Domain Model,FRAMEWORK,SIMILARITY,COMPLEXITY,VALIDATION,PERFORMANCE,QUALITY,REPRESENTATION,ACCOUNTING MODEL,OPTIONAL PROPERTIES,INFORMATION-SYSTEMS},
  language     = {eng},
  number       = {1},
  pages        = {69--101},
  title        = {Understanding business domain models: the effect of recognizing resource-event-agent conceptual modeling structures},
  url          = {http://dx.doi.org/10.4018/jdm.2011010104},
  volume       = {22},
  year         = {2011},
}

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