Publication Type
Journal Article
Version
publishedVersion
Publication Date
11-2004
Abstract
A complete data integration solution can be viewed as an iterative process that consists of three phases, namely analysis, derivation and evolution. The entire process is similar to a software development process with the target application being the derivation rules for the integrated databases. In many cases, data integration requires several iterations of refining the local-to-global database mapping rules before a stable set of rules can be obtained. In particular, the mapping rules, as well as the data model and query model for the integrated databases have to cope with poor data quality in local databases, ongoing local database updates and instance heterogeneities. In this paper, we therefore propose a new object-oriented global data model, known as OORA, that can accommodate attribute and relationship instance heterogeneities in the integrated databases. The OORA model has been designed to allow database integrators and end users to query both the local and resolved instance values using the same query language throughout the derivation and evolution phases of database integration. Coupled with the OORA model, we also define a set of local-to-global database mapping rules that can detect new heterogeneities among databases and resolve instance heterogeneities if situations permit.
Discipline
Databases and Information Systems
Publication
Decision Support Systems
Volume
38
Issue
2
First Page
213
Last Page
231
ISSN
0167-9236
Identifier
10.1016/S0167-9236(03)00103-9
Publisher
Elsevier
Citation
LIM, Ee Peng and CHIANG, Roger Hsiang-Li.
Accommodating Instance Heterogeneities in Database Integration. (2004). Decision Support Systems. 38, (2), 213-231.
Available at: https://ink.library.smu.edu.sg/sis_research/58
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://dx.doi.org/10.1016/S0167-9236(03)00103-9