2015 Ontologies

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Subject Headings: Ontology DB, Ontology Building, Learning, Matching, Mapping, Merging.

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Abstract

This chapter is about ontologies, that is, knowledge models of a domain of interest. We introduce ontologies, view them from the perspective of several fields of knowledge, and present existing ontologies and the different tasks of ontology building, learning, matching, mapping and merging. We also review interfaces for building ontologies and the knowledge representation languages used to implement them. Finally, we discuss the different ways of evaluating an ontology and the applications in which it can be used.

20.1 Introduction

In computational linguistics and computer science, an ontology is a formal representation of knowledge. Since ancient times human beings have constantly searched for new ways to express and encode their knowledge. Nevertheless, until recently this knowledge has overwhelmingly been represented by means of informal tools, such as natural language and pictures. Today, however, with the advent of computers – and the Web era – it is becoming increasingly clear that formally encoding knowledge would make possible a new generation of the Web to enable information processing at the meaning level.

In fact, ontologies are about meaning. A popular definition for an ontology is “a formal specification of a shared conceptualisation” (Gruber 1993). This definition makes it clear that we need to represent formally and explicitly our model of the knowledge we are interested in (typically, a domain) and that this model should be agreed among users, experts, communities, etc. In other words, we can say that an ontology is a set of definitions in a formal language for concepts that describe the world of interest, including the relationships that connect these concepts.

So, ontologies are about formalising knowledge. But how formal and explicit are ontologies? This question can be answered by comparing the degree of formalisation of ontologies with that of other resources such as terminologies, glossaries, thesauri and taxonomies. As can be seen in Figure 1, the degree of formalisation constantly increases from the least to the most formalised knowledge resource: unstructured text – just a string of text with no additional structure; terminology – a set of terms expressing concepts for the domain of interest (e.g. hotel, room, tourist, etc.); glossary – a terminology with textual definitions for each term (e.g. “an establishment that provides short-term lodging” as definition of hotel); thesaurus – which provides information about relationships between words, like synonyms (e.g. motel is a synonym of motor hotel) and antonyms (e.g. ugly is an antonym of beautiful); taxonomy – a hierarchical classification of concepts (e.g. a motel is-a hotel); ontology – a fully-structured knowledge model, including concepts, relations of various kinds and, possibly, rules and axioms.

20.2 Anatomy of an Ontology

20.2.1 Building blocks of an Ontology

An ontology is composed of the following building blocks:

References

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2015 OntologiesRoberto NavigliOntologies2015