A Comprehensive Overview of Ontology: Fundamental and Research Directions

Knowledge representation and reasoning is a field of ‘Artificial Intelligence’ that encodes knowledge, beliefs, actions, feelings, goals, desires, preferences, and all other mental states in the machine. An ontology is prominently used to represent knowledge and offers the richest machine-interpretable (rather than just machine-processable) and explicit semantics. Ontology does not only provide sharable and reusable knowledge, but it also provides a common understanding of the knowledge; as a result, the interoperability and interconnectedness of the model make it priceless for addressing the issues of querying data. Ontology work with concepts and relations that are very close to the working of the human brain. Ontological engineering provides the methods and methodologies for the development of ontology. Nowadays, ontologies are used in almost every field, and a lot of much research is being done on this topic. The paper aims to elaborate on the need of ontology (from data to knowledge), how does for ontology (from data to knowledge), how semantics come from logic, the ontological engineering field, history from hypertext to linked data, and further possible research directions of the ontology. This paper benefit reader who wishes to embark on ontology-based research and application development.