Ontology Treatment

Ontologies have a wide range of applications. These include horizontal ontologies and vertical ontologies. Horizontal ontologies are general in nature, such as space-time relationships. These are common ontologies that span multiple domains, are not applicable to any single vertical space, and provide a mechanism to organize and standardize information content. We've employed this type of ontology for years in the form of object models, hierarchies, taxonomies, and, in many cases, XML vocabularies.

Vertical ontologies, which also incorporate features from horizontal ontologies, are domain specific, such as natural languages for health care or financial services. Vertical ontologies not only define data in terms of semantics native to a particular vertical industry, they also contain rules and formal computer languages that can perform certain types of run-time automated reasoning. This means we understand the metadata, and have logic bound to the metadata, as well.

The use of vertical ontologies, which extend the capabilities of horizontal applications, is where the most value exists. As we learn to define these ontologies as common frameworks for specific business requirements, and define the reuse of such frameworks applicable across multiple like-domains, we also learn to apply languages and reasoning techniques. Ultimately this provides repeatable information formats, rules, and logic that, in turn, enable application integration architects to leverage existing solutions rather than form them from general-purpose middleware and application development technology.

RDF and Ontologies

Resource Description Framework (RDF), a part of the XML story, provides interoperability between applications that exchange information. RDF is another Web standard that's finding use everywhere, including application integration. RDF was developed by the W3C to provide a foundation of metadata interoperability across different resource description communities and is the basis for the W3C movement to ontologies such as the use of Web Ontology Language (OWL).

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.

RDF extends the XML model and syntax to be specified for describing either resources or a collection of information. (XML points to a resource in order to scope and uniquely identify a set of properties known as the schema.)

RDF metadata can be applied to many areas, including application integration. One example would be searching for data, and cataloging data and relationships. RDF is also able to support new technology (such as intelligent software agents and exchange of content rating).

RDF itself does not offer predefined vocabularies for authoring metadata. However, the W3C does expect standard vocabularies to emerge once the infrastructure for metadata interoperability is in place. Anyone, or any industry, can design and implement a new vocabulary. The only requirement is that all resources be included in the metadata instances using the new vocabulary.

RDF benefits application integration in that it supports the concept of a common metadata layer that is sharable throughout an enterprise or between enterprises. Thus, RDF can be used as a common mechanism for describing data within the application integration problem domain.