Ontology {noun}

[uncountable] a branch of philosophy that deals with the nature of existence

[countable] a list of concepts and categories in a subject area that shows the relationships between them

In simple words, one can say that ontology is the study of what there is. 

Ontology as a branch of philosophy is the science of what is, of the kinds and structures of objects, properties, events, processes, and relations in every area of reality. “Ontology” is often used by philosophers as a synonym of “metaphysics”.

An ontology is a formal description of knowledge as a set of concepts within a domain and the relationships that hold between them. To enable such a description, we need to formally specify components such as individuals (instances of objects), classes, attributes and relations as well as restrictions, rules and axioms. As a result, ontologies do not only introduce a sharable and reusable knowledge representation but can also add new knowledge about the domain. It ensures a common understanding of information and makes explicit domain assumptions thus allowing organizations to make better sense of their data.

In computer science, ontology refers to a formal representation of a domain of knowledge or a conceptual model that defines a set of concepts and the relationships between them, often represented in a hierarchical structure or graph. Ontologies are used in fields such as artificial intelligence, knowledge management, and the semantic web to enable the sharing and reuse of knowledge across different applications and domains.

The ontology data model can be applied to a set of individual facts to create a knowledge graph – a collection of entities, where the types and the relationships between them are expressed by nodes and edges between these nodes, By describing the structure of the knowledge in a domain, the ontology sets the stage for the knowledge graph to capture the data in it.

Ontology seeks to provide a definitive and exhaustive classification of entities in all spheres of being. The classification should be definitive in the sense that it can serve as an answer to such questions as: What classes of entities are needed for a complete description and explanation of all the goings-on in the universe? Or: What classes of entities are needed to give an account of what makes true all truths? It should be exhaustive in the sense that all types of entities should be included in the classification, including also the types of relations by which entities are tied together to form larger wholes. 

Methods of Ontology:  The methods of ontology – henceforth in philosophical contexts always used in the adequatist sense – are the methods of philosophy in general. They include the development of theories of wider or narrower scope and the testing and refinement of such theories by measuring them up, either against difficult counter-examples or against the results of science. These methods were familiar already to Aristotle himself. In the course of the twentieth century a range of new formal tools became available to ontologists for the development and testing of their theories. Ontologists nowadays have a choice of formal frameworks (deriving from algebra, category theory, mereology, set theory, topology) in terms of which their theories can be formulated. These new formal tools, along with the language of formal logic, can in principle allow philosophers to express intuitive ideas and definitions in clear and rigorous fashion, and, through the application of the methods of formal semantics, they can allow also for the testing of theories for logical consistency and completeness.

To create effective representations it is an advantage if one knows something about the things and processes one is trying to represent. (We might call this the Ontologist’s Credo.) The attempt to satisfy this credo has led philosophers to be maximally opportunistic in the sources they have drawn upon in their ontological explorations of reality and in their ontological theorizing.

Ontology and Information Science: In a related development, also hardly noticed by philosophers, the term “ontology” has gained currency in recent years in the field of computer and information science (Welty & Smith 2001). The big task for the new “ontology” derives from what we might call the Tower of Babel problem. Different groups of data- and knowledgebase system designers have their own idiosyncratic terms and concepts by means of which they build frameworks for information representation. Different databases may use identical labels but with different meanings; alternatively the same meaning may be expressed via different names. As ever more diverse groups are involved in sharing and translating ever more diverse varieties of information, the problems standing in the way of putting this information together within a single system increase geometrically. Methods must be found to resolve the terminological and conceptual incompatibilities which then inevitably arise. Initially, such incompatibilities were resolved on a case-by-case basis. Gradually, however, it was recognized that the provision, once and for all, of a common reference ontology – a shared taxonomy of entities – might provide significant advantages over such case-by-case resolution, and the term “ontology” came to be used by information scientists to describe the construction of a canonical description of this sort. An ontology is in this context a dictionary of terms formulated in a canonical syntax and with commonly accepted definitions designed to yield a lexical or taxonomical framework for knowledge representation which can be shared by different information-systems communities. More ambitiously, an ontology is a formal theory within which not only definitions but also a supporting framework of axioms is included (perhaps the axioms themselves provide implicit definitions of the terms involved). The methods used in the construction of ontologies thus conceived are derived on the one hand from earlier initiatives in database management systems. But they also include methods similar to those employed in philosophy (as described in Hayes 1985), including the methods used by logicians when developing formal semantic theories. 

The potential advantages of ontology thus conceived for the purposes of information management are obvious. Each group of data analysts would need to perform the task of making its terms and concepts compatible with those of other such groups only once – by calibrating its results in the terms of the single canonical backbone language. If all databases were calibrated in terms of just one common ontology (a single consistent, stable, and highly expressive set of category labels), then the prospect would arise of leveraging the thousands of person-years of effort that have been invested in creating separate database resources in such a way as to create, in more or less automatic fashion, a single integrated knowledge base of a scale hitherto unimagined, thus fulfilling an ancient philosophical dream of a Great Encyclopedia comprehending all knowledge within a single system.

Reference:

• What are Ontologies? | Ontotext Fundamentals Series
• Ontology and Data Science. How the study of what there is can help… | by Favio Vázquez | Towards Data Science
• Barry Smith- Luciano Floridi (ed.), Blackwell Guide to the Philosophy of Computing and Information. Oxford: Blackwell
• MIT - Ontology and Social Construction