Through ontologies and UMLS, mapping
of business rules can be applied to medical transactions to infer information
and achieve semantic interoperability. For example, if a patient can undergo only
a certain procedure once within a 30-day time period, a transaction for a patient
setting up an appointment for that procedure can be mapped to business rules to
infer that the same person cannot schedule the same procedure within that time
period. UMLS would determine the ontology for the appointment and procedures
and ensure that the patient is indeed the same, and RDF defines the business rules
for sharing the information (Nardon & Moura, 2004).
When querying multiple medical data sources for research purposes, there are many
medical science repositories in which data may not be in machine-processable format
and stored in nonstandard ways. Most of the interfaces to search and retrieve
medical sciences research require human interaction. Data extraction of such large
data sources can be very complex and often the data is reused by researchers such as
those in Genomics (Buttler et al.
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