Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Click here to sign up for SAGE Journal Email Alerts today!

Sign In to gain access to subscriptions and/or personal tools.
Health Informatics Journal
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Schuurman, N.
Right arrow Articles by Leszczynski, A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Schuurman, N.
Right arrow Articles by Leszczynski, A.
Social Bookmarking
Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

A method to map heterogeneity between near but non-equivalent semantic attributes in multiple health data registries

Nadine Schuurman

Department of Geography, Simon Fraser University, RCB 7123, 8888 University Drive, Burnaby BC, Canada, V5A 1S6, nadine{at}sfu.ca

Agnieszka Leszczynski

Department of Geography, Simon Fraser University, RCB 7123, 8888 University Drive, Burnaby BC, Canada, V5A 1S6

Health registries from multiple jurisdictions often include terms that are assumed to be semantically equivalent (e.g. fetal death and stillbirth). Closer examination reveals that such attributes have near — but non-equivalent — semantics. Thus their degree of semantic heterogeneity is an important indicator of uncertainty associated with data integration between registries. We build an OWL-encoded ontology which formalizes the relationships between similar perinatal concepts found in different databases. We also introduce the concept of ontology-based metadata as a means of contextualizing such terms and linking context to the attribute data. This extended metadata are exported as XML from the health registries, and it — along with the OWL ontology — is interfaced via a web-based GUI accessible to health researchers. The GUI mapping serves as the basis for making ad hoc comparison and integration decisions. Uncertainty is addressed by precisely mapping semantic heterogeneity between fields.

Key Words: ontology • OWL • semantic data integration • semantic heterogeneity • Semantic Web

Health Informatics Journal, Vol. 14, No. 1, 39-57 (2008)
DOI: 10.1177/1460458207086333
Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?