The World Wide Web Consortium (W3C) has kicked off 2008 with publishing two significant Semantic Web specifications in the month of January. The first is the query language specification, SPARQL (pronounced, "sparkle") and the Ontology Language for Web (OWL) 1.1. One could argue the computer science industry is in the midst of the biggest shift in software development in the past fifty years.

To understand the depth of Semantic Web is to first understand Semantic Web is not limited to the "Web" and it includes all aspects of the computer software industry to include the corporate enterprise. Semantic Web is something an organization does, not buy or out sources.

The area of corporate enterprise will be the front line where the battle for customers will be fought. Semantic Web will allow the automation of such activities as verification, simulation, configuration, supply chain management, contracting, and service negotiation to name just a few of the benefits. To understand the risks your company is exposed today; one needs to understand the term Semantic and what it represents.

Semantic refers to aspects of meaning. As a simple example, if someone should comment that you have an "Adult" object stored in your data repository, what could you conclude about that object? First, the meaning of "Adult" is a person who is 18 years or older. You obtained this information through the use of inference, which is, deriving a conclusion based solely on what you already know.

In today’s world, with no semantics, your data repository lacks any explicitly stated meaning of an adult. You would need a programmer to write a query to retrieve all "Adults" in your data repository. The problem with this approach is that you need to know what you are looking for, and if you don’t know what you’re looking for, you will not find it!

In a Semantic world, you would explicitly define an Ontology based upon what you know through terms, relations, and axioms of your business. Developing an Ontology is the foundation for which a Semantic solution is built upon. The problem today is that Information Knowledge Architects do not completely agree on the definition of a "Ontology." Consequently, CIO’s and other senior management are miss-informed to the state of their Business Domain Ontology. There are many white papers written about the definition of an Ontology. One point that everyone seems to agree upon is that a "Semantic" Ontology is one that requires a "Reasoner" (a type of Inference Engine) to "discover" the meaning of an Ontology relationships automatically.

Benefits of developing a "Semantic" Ontology includes making domain assumptions explicit, separation of domain knowledge from the operational knowledge, making domain knowledge reusable across the enterprise, razing the "silos" of information that exists in corporate departments.

Once you have developed a information repository that has a "Semantic" Ontology that provides "context" to your business, you now have a more agile system to meet the needs of your customer. This is accomplished through the automation of human tasks, developing new business models and improving the way people and businesses communicate and interact.

Currently, there are numerous specifications in works. Ontology will require the implementation of one of the W3C semantic specifications - RDF (Resource Description Framework) or OWL (Web Ontology Language) as a start.

RDF provides a lightweight ontology system to support the exchange of knowledge on the Web. While OWL facilitates greater machine interpretability of data content than that supported by XML, RDF, and RDF Schema (RDF-S) by providing additional vocabulary along with a formal semantics. Both of these specifications are now supported with the recently adopted standard query language

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