Ontology

Ontology is a formal naming and definition of the types, properties, and interrelationships of the entities that exist in a particular domain of information. Ontologies are created to limit complexity and to organize information. Ontologies are considered one of the pillars of the Semantic Web.

The term ontology has its origin in philosophy and has been applied in many different ways. The word element onto- comes from the Greek "being", "that which is". The meaning within information management is a model for describing information that consists of a set of types, properties, and relationship types. Ontologies share many structural similarities, regardless of the language in which they are expressed. Most ontologies describe individuals (instances), classes (concepts), attributes, and relations.

In my last post, I described one of the most used applications of Dublin Core Metadata - RDF. In today's post, I will describe second most used applications of Dublin Core Metadata - Web Ontology Language (OWL).

The Web Ontology Language (OWL) is a family of knowledge representation languages for authoring ontology. Ontology is a formal way to describe taxonomy and classification networks, essentially defining the structure of knowledge for various domains: the nouns represent classes of objects and the verbs represent relations between the objects.

The Dublin Core Schema is a small set of vocabulary terms that can be used to describe different resources.

Dublin Core Metadata may be used for multiple purposes, from simple resource description, to combining metadata vocabularies of different metadata standards, to providing inter-operability for metadata vocabularies in the Linked data cloud and Semantic web implementations.

Most used applications of Dublin Core Metadata are RDF and OWL. I will describe OWL in my next post.

RDF stands for Resource Description Framework. It is a standard model for data interchange on the Web. RDF has features that facilitate data merging even if the underlying schemas differ, and it specifically supports the evolution of schemas over time without requiring all the data consumers to be changed.