Abstract
Conceptual modeling is the foundation of system analysis and design methodologies. It is challenging because it requires a clear understanding of an application domain and the ability to translate the requirement specification into a conceptual data model. Semi-automated conceptual data modeling is a process of using an intelligent tool to aid the modeler for the purpose of building a quality conceptual data model. In this paper, we first present six categories of methodologies that can be used for developing conceptual data models. We then describe the characteristics of each category, compare these characteristics, and present related work of each category. We finally suggest a framework for semi-automatically generating conceptual data models from requirements and suggest challenging research topics.
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