A Meta-Analysis Comparing Relational and Semantic Models

Abstract

Data modeling is the sine quo non of systems development and one of the most widely researched topics in the database literature. In the past three decades, semantic data modeling has emerged as an alternative to traditional relational modeling. The majority of the research in data modeling suggests that the use of semantic data models leads to better performance; however, the findings are not conclusive and are sometimes inconsistent. The discrepancies that exist in the data modeling literature and the relatively low statistical power in the studies make meta-analysis a viable choice in analyzing and integrating the findings of these studies.

Improving Sequence Diagram Modeling Performance

“…The attributes of the class approximately correspond to attributes of the data model, much like in an entity-relationship (ER) model. A large number of classes are entity classes because the backend of most transaction-based information systems has been traditionally built on relational databases (Siau, Nah, & Cao, 2011). For modeling entity classes, one can extrapolate knowledge gained from research in data modeling (Topi & Ramesh, 2002) to help novice analysts.…”