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Here’s a some snippets from an article in the Web Services Journal that nicely explains some of the business benefits of a services-based architecture that uses ontologies to integrate disparate applications and knowledge spaces.

Note that XML / RDF / OWL – all from the W3C – together only make up part of the story on new tools for how making it easy for systems (and users, and businesses…) to understand and work with complicated information spaces and relationships. There’s also Topic Maps, which do a very good job of visually mapping relationships that people and systems can understand.

Article:Semantic Mapping, Ontologies, and XML Standards

The key to managing complexity in application integration projects

Snippets:
Another important notion of ontologies is entity correspondence. Ontologies that are leveraged in more of a B2B environment must leverage data that is scattered across very different information systems, and information that resides in many separate domains. Ontologies in this scenario provide a great deal of value because we can join information together, such as product information mapped to on-time delivery history mapped to customer complaints and compliments. This establishes entity correspondence.
So, how do you implement ontologies in your application integration problem domain? In essence, some technology – either an integration broker or applications server, for instance – needs to act as an ontology server and/or mapping server.

An ontology server houses the ontologies that are created to service the application integration problem domain. There are three types of ontologies stored: shared, resource, and application. Shared ontologies are made up of definitions of general terms that are common across and between enterprises. Resource ontologies are made up of definitions of terms used by a specific resource. Application ontologies are native to particular applications, such as an inventory application. Mapping servers store the mappings between ontologies (stored in the ontology server). The mapping server also stores conversion functions, which account for the differences between schemas native to remote source and target systems. Mappings are specified using a declarative syntax that provides reuse.

RDF uses XML to define a foundation for processing metadata and to provide a standard metadata infrastructure for both the Web and the enterprise. The difference between the two is that XML is used to transport data using a common format, while RDF is layered on top of XML defining a broad category of data. When the XML data is declared to be of the RDF format, applications are then able to understand the data without understanding who sent it.