In recent years, data or information has increased exponentially. This data or information is readily available online for consumers to read, understand and reproduce according to their needs. But the question(s) is/are can technologies sustain this information overload? How much time does it take to process a search query? How accurate are the results? How complex is the query? Can system understand what it is looking for? and so on.;The solution to address this complexity is to make data smart enough for system to understand process and get accurate results. Semantic Web is about adding semantics to the data so that the information online is machine readable. One way of realizing Semantic web is to connect data with proper relations or properties forming an ontology.;Ontologies are the back bone of semantic web. This paper gives a brief introduction to semantic web, techniques and technology involved in it and finally focuses on ontology and ways to model ontologies. We propose a new way of ontology modeling called Ontology Development Life Cycle (ODLC) which inherits its principles from Software Development Life Cycle (SDLC). The paper also explains Computing Ontology that is created using ODLC. Computing Ontology is an ontology that describes various disciplines, topics, and subtopics that belong to the domain of Computing Sciences. It also describes the ways in which these topics and subtopics are related to each other and to various sub disciplines. Creating and maintaining a computing ontology can come in handy for various real time applications such as Curriculum Developments, Indexing of Digital Libraries, and supporting searching.
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