Automated database mediation using ontological metadata mappings.
OBJECTIVE
To devise an automated approach for integrating federated database information using database ontologies constructed from their extended metadata.


BACKGROUND
One challenge of database federation is that the granularity of representation of equivalent data varies across systems. Dealing effectively with this problem is analogous to dealing with precoordinated vs. postcoordinated concepts in biomedical ontologies.


METHODS
The authors describe an approach based on ontological metadata mapping rules defined with elements of a global vocabulary, which allows a query specified at one granularity level to fetch data, where possible, from databases within the federation that use different granularities. This is implemented in OntoMediator, a newly developed production component of our previously described Query Integrator System. OntoMediator's operation is illustrated with a query that accesses three geographically separate, interoperating databases. An example based on SNOMED also illustrates the applicability of high-level rules to support the enforcement of constraints that can prevent inappropriate curator or power-user actions.


CONCLUSIONS
A rule-based framework simplifies the design and maintenance of systems where categories of data must be mapped to each other, for the purpose of either cross-database query or for curation of the contents of compositional controlled vocabularies.
Marenco
Luis
L
Center for Medical Informatics, Yale University School of Medicine, PO Box 208009, New Haven, CT 06520-8009, USA. luis.marenco@yale.edu
Wang
Rixin
R
Nadkarni
Prakash
P
D003628:Database Management Systems; D019992:Databases as Topic; D006801:Humans; D033181:Information Dissemination; D016247:Information Storage and Retrieval; D020407:Internet; D009488:Neurosciences; D039061:Systematized Nomenclature of Medicine; D018511:Systems Integration; D014584:User-Computer Interface; D018875:Vocabulary, Controlled