Being the important means by which people acquire and publish information nowadays, theWeb has been a huge information resource depository all around the world and the huge amount of information on the Web is getting larger and larger every day. It is becoming very crucial for computer programs to deal with information on the Web automatically and intelligently. But most of today’s Web content is suitable for human consumption. The Semantic Web is a vision that has sparked a wide-ranging enthusiasm for a generation of the Web. The Semantic Web has emerged as an extension of the current Web in which information is given well-defined meaning, enabling computers and people to better work in cooperation. The central idea of the Semantic Web is to make the Web more understandable to computer programs so that people can make more use of this gigantic asset.
The Semantic Web is generally built on syntaxes which use URIs to represent data, usually in triple based structures: i.e. many triples of URI data that can be held in databases, or interchanged in the World Wide Web using a set of particular syntaxes developed especially for the task. These syntaxes are called Resource Description Framework (RDF) syntaxes. The layer above the syntax is the simple datatyping model. The RDF Schema is designed to be a simple datatyping model for the RDF. The Web Ontology Language (OWL) is a language as an ontology language based upon the RDF. OWL takes the RDF Schema a step further, by giving us more in-depth properties and classes. The next step in the architecture of the Semantic Web is trust and proof.
In the real world, human knowledge and natural language have a big deal of imprecision and vagueness. While the Semantic Web concept and research attracts attention, as long as there will be used two-valued-based logical methods no progress will be expected in handling ill-structured, uncertain or imprecise information encountered in the real world knowledge. Fuzzy logic, probability, and more generally soft computing, have been applied in a large number and a wide variety of applications, with a real-world impact across a wide array of domains with human-like behavior and reasoning. Soft computing has been a crucial means of implementing machine intelligence. Therefore, soft computing cannot be ignored in order to bridge the gap between human-understandable soft logic and machine-readable hard logic. None of the usual logical requirements can be guaranteed: there is no centrally defined format for data, no guarantee of truth for assertions made, and no guarantee of consistency. It can be believed that soft computing can play an important and positive role in the development of the Semantic Web. It should be noticed, however, that soft computing may not be assumed to be the (only) basis for the Semantic Web, but its related concepts and techniques will certainly reinforce the systems classically developed within the W3C. Currently the research and development of soft computing in the area of ontologies and Semantic Web are attracting an increased attention.