Using the W3C OWL ontology standard lets you get more out of all kinds of data. Find out how this standard and some free software lets you query two databases as if they were one.
by Bob DuCharme
July 29, 2008
WL ontologies allow you to describe data and relationships between data items. Common examples of this include complex knowledge domains such as pharmacology, but you can use OWL ontologies with simple, straightforward data that most companies already have stored in a relational database package. When you add metadata to existing data, and then use that metadata to query the data collection, you get more value out of that data. Data is the most important asset of many organizations, so the use of standards-based technology to query data collections is becoming more and more attractive.
The primary goal of this article is to put together a demonstration of how you can use OWL to integrate two relational databases, and then perform queries against the aggregate collection to answer realistic questions that you could not answer without the addition of an OWL ontology.
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WL ontologies allow you to describe data and relationships between data items. Common examples of this include complex knowledge domains such as pharmacology, but you can use OWL ontologies with simple, straightforward data that most companies already have stored in a relational database package. When you add metadata to existing data, and then use that metadata to query the data collection, you get more value out of that data. Data is the most important asset of many organizations, so the use of standards-based technology to query data collections is becoming more and more attractive.
