Semantic Simulations

An ontology, along with its associated instance data, is basically a data base similar to a relational data base, but much more expressive.. Because of this additional expressiveness it is often called a knowledge base. Never-the-less, it is still just a data structure. It does not contain any computer processing code, it cannot execute any algorithms, it is just a place to store data which can be acted upon by other computer programs. An ontology consists of a formal structure based on descriptive logic that allows the user to organize data in terms of defined relationships between classes and properties. It can contain some rules, using the Semantic Web Rules Language or other rule languages, that set conditions for when certain classes or properties apply under certain conditions. Also, the fact that an ontology data structure is built upon formal description logic provides an additional capability - reasoning, although the reasoning process must be done with an external computer program and not by the ontology itself. A simple example of formal reasoning can be shown by the following example. If the following statements are formally expressed in an ontology: Barack Obama is the President of the United States and Milia Obama is the daughter of Barack Obama. Then a reasoner can produce the additional fact, not actually in the knowledge base, that Milia Obama is the daughter of the the President of the United States. This reasoning process seems simple enough, but it is well beyond the capabilities provided by traditional relational data bases. Additional, the reasoning is not limited to one-step reasoning as shown in this simple example, but could produce new facts that are based on a string of formal logic connections. This multistage reasoning capability could produce new facts that are well beyond what human thought processes might discover in a large data collection.