Selecting optimal instantiations of data models - Theory and validation of an ex ante approach

Bowen, P. L., Debreceny, R., Rohde, F. H. and Basford, J. (2006) Selecting optimal instantiations of data models - Theory and validation of an ex ante approach. Decision Support Systems, 42 2: 1170-1186. doi:10.1016/j.dss.2005.10.002

Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials)
Name Description MIMEType Size Downloads

Author Bowen, P. L.
Debreceny, R.
Rohde, F. H.
Basford, J.
Title Selecting optimal instantiations of data models - Theory and validation of an ex ante approach
Journal name Decision Support Systems   Check publisher's open access policy
ISSN 0167-9236
Publication date 2006-11
Sub-type Article (original research)
DOI 10.1016/j.dss.2005.10.002
Volume 42
Issue 2
Start page 1170
End page 1186
Total pages 17
Editor A. B. Whinston
Place of publication The Netherlands
Publisher Elsevier BV
Collection year 2006
Language eng
Subject C1
350202 Business Information Systems (incl. Data Processing)
700299 Information services not elsewhere classified
Abstract The schema of an information system can significantly impact the ability of end users to efficiently and effectively retrieve the information they need. Obtaining quickly the appropriate data increases the likelihood that an organization will make good decisions and respond adeptly to challenges. This research presents and validates a methodology for evaluating, ex ante, the relative desirability of alternative instantiations of a model of data. In contrast to prior research, each instantiation is based on a different formal theory. This research theorizes that the instantiation that yields the lowest weighted average query complexity for a representative sample of information requests is the most desirable instantiation for end-user queries. The theory was validated by an experiment that compared end-user performance using an instantiation of a data structure based on the relational model of data with performance using the corresponding instantiation of the data structure based on the object-relational model of data. Complexity was measured using three different Halstead metrics: program length, difficulty, and effort. For a representative sample of queries, the average complexity using each instantiation was calculated. As theorized, end users querying the instantiation with the lower average complexity made fewer semantic errors, i.e., were more effective at composing queries. (c) 2005 Elsevier B.V. All rights reserved.
Keyword Computer Science, Artificial Intelligence
Computer Science, Information Systems
Operations Research & Management Science
Models Of Data
Data Representations
Object-relational Databases
Relational Databases
Query Languages
Query Complexity
Software Complexity
Query Performance
Q-Index Code C1

Document type: Journal Article
Sub-type: Article (original research)
Collections: Excellence in Research Australia (ERA) - Collection
2007 Higher Education Research Data Collection
UQ Business School Publications
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Scopus Citation Count Cited 2 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Wed, 15 Aug 2007, 06:43:40 EST