Data of Semantic Web as Unit of Knowledge

In service to the state of the art, advances are required toward redesigning the framework over which web applications are built. The semantic web lies at the intersection of web and machine understandable meaningful data, turning it into intelligent 'web of data'. The key requirement with any intelligent system has been to find a concrete knowledge representation that can make the inferences within time and space constraints; that is, reasoning effectively and efficiently within the resource constraints posed to the problem at one hand and with insufficient data as well as incomplete knowledge on the other hand. Various Knowledge representation schemes have been proposed in the literature, each having its limitation over the others. Ontology is the key component for semantic web engineering. Ontologies are conceptual knowledge bases providing a systematic and taxonomical description of the concepts and instances under consideration. Conceptual clarity in the computational representation of a concept is vital for holistic thinking and knowledge engineering. In order to meet the needs of an application/enterprise, knowledge should be presented taking care of all possible perspectives; and represented in a hierarchical structure with differing levels of granularity. This paper discusses about bringing all the manifestations of an ontological concept/decision under one umbrella; hence describing the resultant scheme as a unit of knowledge. By representing a concept as a knowledge unit, classical ontology is claimed to be sufficient in dealing with imprecise, vague and heterogeneous knowledge for real-world web applications; and portrays the capability to acquire fresh knowledge through its thorough interaction with the external world in a given working environment.