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
Research Areas
Information Systems and Management
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
Citation
SIAU, Keng; NAH, Fiona Fui-Hoon; and CAO, Qing.
A meta-analysis comparing relational and semantic models. (2011). Journal of Database Management. 22, (4), 57-72.
Available at: https://ink.library.smu.edu.sg/sis_research/9559
Additional URL
https://doi.org/10.4018/jdm.2011100103