Although one can think that Software, Knowledge and Ontology Engineering are components of an ISA or partOf relations, because a knowledge base (KB) is a kind of software, and an ontology could be considered a kind of KB, in fact most of methodologies, tools and languages in Software Engineering are oriented to algorithmic, to "prescriptive" problems, while those in Knowledge Engineering are more related with problem solutions of heuristic type.

Concerning comparison between Knowledge Engineering and Ontology Engineering, the first is more "representation oriented" than the second one, more "modelling oriented".

Of course, due the fact that, in practice, there are not "pure" ontology projects and applications, almost always they are involved in some practical issue (foundational ontologies and some top level domain ontologies could be exceptions), where modelling, representation and algorithmic, all together, are systemically and sistematically combined.

Consequently, it makes sense to find ontology engineering foundations, particularly those related with methodologies.

Generally the term Ontology means a philosophical study of the nature of being, existence or reality . In computer science or information science ontology is a formal representation of a set of concepts within a domain and relationships between those concepts . Gruber (1993) gave a different definition of ontology in which it is considered more than “nature of being”. According to Gruber (1993) ontology is a specification of a conceptualization. Conceptualization means structured interpretation of a part of the world in which people used to think and communicate in the world.

Ontology contains hierarchies and tree structures. Hendler (2001) defines it as a set of knowledge terms including the vocabulary, the semantic relations among the terms, and some simple rules of inference and logic for some particular topic. There has been much debate about the best definition of ontology. Gruber’s (1993) definition is widely accepted; however, one criticism about it is the general nature of the term specification, as there are no agreed-upon borders (Brewster & O’Hara, 2004; Borst, 1997). Borst (1997) modified Gruber’s definition of ontology as “ontology is a formal specification of a shared conceptualization”. Inclusion of the two words ‘shared’ and ‘formal’ in the modified definition emphasise, respectively, on the agreed upon conceptualization of the ontology that can be specified by a group, and machine readability of the ontology.

When we learn anything basically we build its ontology in our mind. The conceptual connections and the rules to use specific concepts and the connections with respect to the context. So our learning is nothing but ontology building. It is the most natural way of learning. Mostly ontologies were used for machine learning and information retrieval in the past. Now, people are exploring its usefulness for teaching and learning as well.