A meta-analysis comparing relational and semantic models

Publication Type

Journal Article

Publication Date

10-2011

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.

Keywords

Data modeling, Meta-analysis, Relational data models, Relational modeling, Semantic data, Semantic data model, Semantic Data Models, Semantic Model, Statistical power, Systems development, User performance

Discipline

Databases and Information Systems | Data Storage Systems

Research Areas

Information Systems and Management; Data Science and Engineering

Publication

Journal of Database Management

Volume

22

Issue

4

First Page

57

Last Page

72

ISSN

1063-8016

Identifier

10.4018/jdm.2011100103

Publisher

IGI Global

Additional URL

https://doi.org/10.4018/jdm.2011100103

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