What is the Semantic Web and how can it help you? The concept may help solve tough corporate information-management problems.
The technology behind semantics includes linguistic programming, artificial intelligence, content management and a few new areas as well. The motivation behind it can be attributed to Tim Berners-Lee and a group of Web devotees who coined the phrase "Semantic Web" more than 10 years ago. The idea was to turn the Web into a single repository of information —rather than a collection of Web sites and pages —that could be queried for its content. They created a new type of metamodel called an ontology to capture the rich meanings and relationships of all the Web's resources.
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There are some problems with the Semantic Web. To build it, every resource must be "tagged" with XML-like tags. Clearly, that is a problem of scale. Who will tag the Web and how long will that take? Among the more creative answers are, 1) let everyone tag it and 2) devise tools that can create tags without human intervention. It remains a work in progress.
The concept of a semantic Web within corporate firewalls is intriguing. If all the digital property of an organization were properly cataloged and query tools able to resolve semantic-based queries were available, it could resolve some of the most vexing problems in information management today. For example, it could provide a rich enough layer of abstraction that single-product, proprietary metadata would no longer be necessary. Instead of source-to-BI-model mappings for three different BI tools, each tool could query the metamodel. It would eliminate the need to research dependencies when source systems are modified.
When implementing service-oriented architectures, one open question is, how can you create services from existing applications if you don't know what you have? Ontologies are being used to catalog and maintain application portfolios. Why can't you do this with a relational database? You can, as some database vendors have embedded semantic capabilities, although they use ontology rather than relational engines. The relational model strips data of its intelligence and reapplies it through a query or stored procedure. Consider data warehousing: Current data warehouse best practices insist on a "single version of the truth." If Division A defines an FTE as 36 hours per week and Division B uses 40, which is the right answer?
With an ontology, there's no need to artificially force a single answer. All contexts can exist simultaneously.
As with many emerging technologies, most of the interesting developments in semantics are coming from small companies such as Metatomix, Cerebra, Metallect and SilverCreek Systems, but Oracle, IBM, Sybase, Microsoft and SAP are all aggressively pursuing it through R&D or partnerships. That's a sure sign semantics have arrived.
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