Ontologies

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Introduction

See also Data science portal | Dublin Core | FOAF - Friend of a Friend | Semantic web | Unified Medical Language System® (UMLS) | Web 3.0

Ontologies are representations of a set of concepts within a subject area or domain, and aim to clarify relationships between concepts within a subject area or domain. An ontology is a description (like a formal specification of a program) of the concepts and relationships that can formally exist for an agent or a community of agents. This definition is consistent with the usage of ontology as set of concept definitions, but more general. And it is a different sense of the word than its use in philosophy. Ontologies are similar to controlled vocabularies and are generally used to surmise the properties of a given subject or domain, and may also be used to define them accurately. Ontologies are used as a form of knowledge representation in areas as diverse as artificial intelligence, semantic web, software engineering, biomedical informatics, library science and information architecture.

An ontology can be understood as a specific kind of set of controlled terms or vocabulary. Ontologies are considered to be critical to the development of the semantic web, as it is envisioned by Sir Tim Berners-Lee and others, although there is little agreement about whether the semantic web will be any different from the current web as it is configured. What seems likely is a web space that combines human understanding of semantics (interpreted by humans) as the basis for machine understanding. It's important to note that a semantic vocabulary is a type of ontology, sometimes also merely as a collection of URIs with an (usually informally) described meaning. Ontologies are usually assumed to be accompanied by some document in a formal ontology language, though some ontologies do not use standard formats for that purpose.

Common ontological components

  • Individuals: instances or objects (the basic or "ground level" objects)
  • Classes: collections, concepts or types of objects, each of which is relevant but not identical to the notion of a "class" here.
  • Attributes: properties, features, characteristics, or parameters that objects (and classes) can have
  • Relations: ways that classes and objects can be related to one another
  • Function terms: complex structures formed from certain relations that can be used in place of an individual term in a statement
  • Restrictions: formally stated descriptions of what must be true in order for some assertion to be accepted as input
  • Rules: statements in the form of an if-then (antecedent-consequent) sentence that describe the logical inferences that can be drawn from an assertion in a particular form
  • Axia: assertions (including rules) in a logical form that together comprise the overall theory that the ontology describes, for its domain of application
  • Ontologies are commonly encoded using ontology languages

Contemporary ontologies share many structural similarities, regardless of the language in which they are expressed. As mentioned above, most ontologies describe individuals (instances), classes (concepts), attributes, and relations. In this section each of these components is discussed in turn.

Individuals (instances) are the basic, "ground level" components of an ontology. The individuals in an ontology may include concrete objects such as people, animals, tables, automobiles, molecules, and planets, as well as abstract individuals such as numbers and words. Strictly speaking, an ontology need not include any individuals, but one of the general purposes of an ontology is to provide a means of classifying individuals, even if those individuals are not explicitly part of the ontology.

Classes

Concepts that are also called type, sort, category, and kind – are abstract groups, sets, or collections of objects. They may contain individuals, other classes, or a combination of both. Some examples of classes: Note that the names given to the classes mentioned here are entirely a matter of convention.

  • Person, the class of all people
  • Vehicle, the class of all vehicles
  • Car, the class of all cars
  • Class, representing the class of all classes
  • Thing, representing the class of all things

Ontologies vary whether classes can contain other classes, whether a class can belong to itself, whether there is a universal class (that is, a class containing everything), etc. Sometimes restrictions along these lines are made in order to avoid certain well-known paradoxes.

The classes of an ontology may be extensional or intensional in nature. A class is extensional if and only if it is characterized solely by its membership. More precisely, a class C is extensional if and only if for any class C', if C' has exactly the same members as C, then C and C' are identical. If a class does not satisfy this condition, then it is intentional. While extensional classes are more well-behaved and well-understood mathematically, as well as less problematic philosophically, they do not permit the fine grained distinctions that ontologies often need to make. For example, an ontology may want to distinguish between the class of all creatures with a kidney and the class of all creatures with a heart, even if these classes happen to have exactly the same members. In the upper ontologies mentioned above, the classes are defined intensionally. Intensionally defined classes usually have necessary conditions associated with membership in each class. Some classes may also have sufficient conditions, and in those cases the combination of necessary and sufficient conditions make that class a fully defined class.

Ontology is overrated

Clay Shirky was one of the first people to argue that the exponential growth of information required the abandonment of expert classification of information. He argues that there are many ways to organize data: by using labels, lists, categories, taxonomies, ontologies. Of these, an ontology -- with its assertions about essence and relations among groups of items -- seems to be the highest-order method of organization. The predicted value of the semantic web assumes that ontological success such as the Library of Congress's classification scheme can be reproduced on a massive scale.

Shirky says that, far from being an ideal high-order tool, ontologies are nearing the end of their use in information organization. The problems ontology solve are not about organizing ideas but how to organize things -- the Library of Congress's classification scheme exists not because concepts require consistent hierarchical placement, but because books do. Shirky provides examples of how this notion shifts in the online era.

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