In computer science Computer science or computing science is the study of the theoretical foundations of information and computation, and of practical techniques for their implementation and application in computer systems. It is frequently described as the systematic study of algorithmic processes that create, describe, and transform information. Computer science and information science Information science is an interdisciplinary science primarily concerned with the analysis, collection, classification, manipulation, storage, retrieval and dissemination of information. Practitioners within the field study the application and usage of knowledge in organizations, along with the interaction between people, organizations and any, an ontology is a formal representation of the knowledge by a set of concepts within a domain The domain of discourse, sometimes called the universe of discourse, logical discourse, or simply discourse, is an analytic tool used in deductive logic, especially predicate logic. It indicates the relevant set of entities that are being dealt with by quantifiers and the relationships between those concepts. It is used to reason Reasoning is the cognitive process of looking for reasons, beliefs, conclusions, actions or feelings about the properties of that domain, and may be used to describe the domain.

In theory, an ontology is a "formal, explicit specification of a shared conceptualisation".^[1] An ontology provides a shared vocabulary, which can be used to model a domain — that is, the type of objects and/or concepts that exist, and their properties and relations.^[2]

Ontologies are used in artificial intelligence Artificial intelligence is the intelligence of machines and the branch of computer science that aims to create it. Textbooks define the field as "the study and design of intelligent agents," where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who, the Semantic Web Semantic Web is a group of methods and technologies to allow machines to understand the meaning - or "semantics" - of information on the World Wide Web, systems engineering Systems engineering is an interdisciplinary field of engineering that focuses on how complex engineering projects should be designed and managed. Issues such as logistics, the coordination of different teams, and automatic control of machinery become more difficult when dealing with large, complex projects. Systems engineering deals with work-, software engineering Software engineering is a profession and field of study dedicated to designing, implementing, and modifying software so that it is of higher quality, more affordable, maintainable, and faster to build. The term software engineering first appeared in the 1968 NATO Software Engineering Conference, and was meant to provoke thought regarding the, biomedical informatics Health informatics, Health care informatics or medical informatics is the intersection of information science, computer science, and health care. It deals with the resources, devices, and methods required to optimize the acquisition, storage, retrieval, and use of information in health and biomedicine. Health informatics tools include not only, library science Library science is an interdisciplinary field that applies the practices, perspectives, and tools of management, information technology, education, and other areas to libraries; the collection, organization, preservation, and dissemination of information resources; and the political economy of information. The first school for library science was, enterprise bookmarking Enterprise bookmarking is a method for Enterprise 2.0 users to tag, organize, store, and search bookmarks of both web pages on the Internet and data resources stored in a distributed database or fileserver. This is done collectively and collaboratively in a process by which users add tag and knowledge tags, and information architecture Information architecture is the art of expressing a model or concept of information used in activities that require explicit details of complex systems. Among these activities are library systems, Content Management Systems, web development, user interactions, database development, programming, technical writing, enterprise architecture, and as a form of knowledge representation Knowledge representation and reasoning is an area in artificial intelligence that is concerned with how to formally "think", that is, how to use a symbol system to represent "a domain of discourse" - that which can be talked about, along with functions that may or may not be within the domain of discourse that allow inference about the world or some part of it. The creation of domain ontologies is also fundamental to the definition and use of an enterprise architecture framework An Enterprise Architecture Framework is a framework for an Enterprise Architecture, which defines, how to organize the structure and views associated with an Enterprise Architecture.

Overview

The term ontology Ontology (from the Greek ὄν, genitive ὄντος: "of being" and -λογία, -logia: science, study, theory) is the philosophical study of the nature of being, existence or reality in general, as well as the basic categories of being and their relations. Traditionally listed as a part of the major branch of philosophy known as has its origin in philosophy Philosophy is the study of general and fundamental problems concerning matters such as existence, knowledge, values, reason, mind, and language. It is distinguished from other ways of addressing fundamental questions by its critical, generally systematic approach and its reliance on rational argument. The word "philosophy" comes from the, and has been applied in many different ways. The core meaning within computer science Computer science or computing science is the study of the theoretical foundations of information and computation, and of practical techniques for their implementation and application in computer systems. It is frequently described as the systematic study of algorithmic processes that create, describe, and transform information. Computer science is a model for describing the world that consists of a set of types, properties, and relationship types. Exactly what is provided around these varies, but they are the essentials of an ontology. There is also generally an expectation that there be a close resemblance between the real world and the features of the model in an ontology.^[3]

What ontology has in common in both computer science and in philosophy is the representation of entities, ideas, and events, along with their properties and relations, according to a system of categories. In both fields, one finds considerable work on problems of ontological relativity (e.g., Quine Willard Van Orman Quine (known to intimates as "Van") was an American philosopher and logician in the analytic tradition. From 1930 until his death 70 years later, Quine was continuously affiliated with Harvard University in one way or another, first as a student, then as a professor of philosophy and a teacher of mathematics, and and Kripke Saul Aaron Kripke is an American philosopher and logician. He is a professor emeritus at Princeton and teaches as a distinguished professor of philosophy at CUNY Graduate Center. Since the 1960s Kripke has been a central figure in a number of fields related to mathematical logic, philosophy of language, philosophy of mathematics, metaphysics, in philosophy, Sowa John Florian Sowa is the computer scientist who invented conceptual graphs, a graphic notation for logic and natural language, based on the structures in semantic networks and on the existential graphs of Charles S. Peirce. He is currently developing high-level "ontologies" for artificial intelligence and automated natural language and Guarino in computer science)^[4], and debates concerning whether a normative ontology is viable (e.g., debates over foundationalism Foundationalism is any theory in epistemology that holds that beliefs are justified (known, etc.) based on what are called basic beliefs (also commonly called foundational beliefs). Basic beliefs are beliefs that give justificatory support to other beliefs, and more derivative beliefs are based on those more basic beliefs. The basic beliefs are in philosophy, debates over the Cyc Cyc is an artificial intelligence project that attempts to assemble a comprehensive ontology and knowledge base of everyday common sense knowledge, with the goal of enabling AI applications to perform human-like reasoning. The project was started in 1984 by Douglas Lenat at MCC and is developed by company Cycorp. Parts of the project are released project in AI). Differences between the two are largely matters of focus. Philosophers are less concerned with establishing fixed, controlled vocabularies than are researchers in computer science, while computer scientists are less involved in discussions of first principles (such as debating whether there are such things as fixed essences, or whether entities must be ontologically more primary than processes).

History

Historically, ontologies arise out of the branch of philosophy Philosophy is the study of general and fundamental problems concerning matters such as existence, knowledge, values, reason, mind, and language. It is distinguished from other ways of addressing fundamental questions by its critical, generally systematic approach and its reliance on rational argument. The word "philosophy" comes from the known as metaphysics Metaphysics is a branch of philosophy concerned with explaining the fundamental nature of being and the world although it is not easily defined.. Someone who studies metaphysics would be called either a metaphysicist or a metaphysician, which deals with the nature of reality – of what exists. This fundamental branch is concerned with analyzing various types or modes of existence, often with special attention to the relations between particulars In philosophy, particulars are concrete entities existing in space and time as opposed to abstractions. There are, however, theories of abstract particulars or tropes. For example, Socrates is a particular . Redness, by contrast, is not a particular, because it is abstract and multiply-instantiated (my bicycle, this apple, and that woman's hair and universals In metaphysics, a universal is what particular things have in common, namely characteristics or qualities. In other words, universals are repeatable or recurrent entities that can be instantiated or exemplified by many particular things. For example, suppose there are two chairs in a room, each of which is green. These two chairs both share the, between intrinsic and extrinsic properties An intrinsic property is a property that an object or a thing has of itself, independently of other things, including its context. An extrinsic property is a property that depends on a thing's relationship with other things. For example, mass is a physical intrinsic property of any physical object, whereas weight is an extrinsic property that, and between essence In philosophy, essence is the attribute or set of attributes that make an object or substance what it fundamentally is, and which it has by necessity, and without which it loses its identity. Essence is contrasted with accident: a property that the object or substance has contingently, without which the substance can still retain its identity. The and existence In common usage, existence is the world we are aware of through our senses, and that persists independently without them. In academic philosophy the word has a more specialized meaning, being contrasted with essence, which specifies different forms of existence as well as different identity conditions for objects and properties. Philosophers. The traditional goal of ontological inquiry in particular is to divide the world "at its joints", to discover those fundamental categories, or kinds, into which the world’s objects naturally fall.^[5]

During the second half of the 20th century, philosophers extensively debated the possible methods or approaches to building ontologies, without actually building any very elaborate ontologies themselves. By contrast, computer scientists were building some large and robust ontologies (such as WordNet WordNet is a lexical database for the English language. It groups English words into sets of synonyms called synsets, provides short, general definitions, and records the various semantic relations between these synonym sets. The purpose is twofold: to produce a combination of dictionary and thesaurus that is more intuitively usable, and to and Cyc Cyc is an artificial intelligence project that attempts to assemble a comprehensive ontology and knowledge base of everyday common sense knowledge, with the goal of enabling AI applications to perform human-like reasoning. The project was started in 1984 by Douglas Lenat at MCC and is developed by company Cycorp. Parts of the project are released) with comparatively little debate over how they were built.

Since the mid-1970s, researchers in the field of artificial intelligence Artificial intelligence is the intelligence of machines and the branch of computer science that aims to create it. Textbooks define the field as "the study and design of intelligent agents," where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who have recognized that capturing knowledge is the key to building large and powerful AI systems. AI researchers argued that they could create new ontologies as computational models A computational model is a mathematical model in computational science that requires extensive computational resources to study the behavior of a complex system by computer simulation. The system under study is often a complex nonlinear system for which simple, intuitive analytical solutions are not readily available. Rather than deriving a that enable certain kinds of automated reasoning Automated reasoning is an area of computer science dedicated to understanding different aspects of reasoning in a way that allows the creation of software which allows computers to reason completely or nearly completely, automatically. As such, it is usually considered a subfield of artificial intelligence, but it also has strong connections to. In the 1980s, the AI community began to use the term ontology to refer to both a theory of a modeled world and a component of knowledge systems. Some researchers, drawing inspiration from philosophical ontologies, viewed computational ontology as a kind of applied philosophy.^[6]

In the early 1990s, the widely cited Web page and paper "Toward Principles for the Design of Ontologies Used for Knowledge Sharing" by Tom Gruber^[7] is credited with a deliberate definition of ontology as a technical term in computer science Computer science or computing science is the study of the theoretical foundations of information and computation, and of practical techniques for their implementation and application in computer systems. It is frequently described as the systematic study of algorithmic processes that create, describe, and transform information. Computer science. Gruber "introduced the term to mean a specification of a conceptualization. That is "an ontology is a description (like a formal specification of a program) of the concepts and relationships that can 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".^[8]

According to Gruber (1993) "ontologies are often equated with taxonomic hierarchies of classes, class definitions, and the subsumption relation, but ontologies need not be limited to these forms. Ontologies are also not limited to conservative definitions – that is, definitions in the traditional logic sense that only introduce terminology and do not add any knowledge about the world.^[9] To specify a conceptualization, one needs to state axioms that do constrain the possible interpretations for the defined terms.^[1]

In the early years of the 21st century, the interdisciplinary project of cognitive science Cognitive science is the interdisciplinary study of how information, e.g., concerning perception, language, reasoning, and emotion, is represented and transformed in the brain. It consists of multiple research disciplines, including psychology, artificial intelligence, philosophy, neuroscience, learning sciences, linguistics, anthropology, has been bringing the two circles of scholars closer together^{[citation needed]}. For example, there is talk of a "computational turn in philosophy" that includes philosophers analyzing the formal ontologies of computer science (sometimes even working directly with the software), while researchers in computer science have been making more references to those philosophers who work on ontology (sometimes with direct consequences for their methods). Still, many scholars in both fields are uninvolved in this trend of cognitive science, and continue to work independently of one another, pursuing separately their different concerns.

Ontology components

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.

Common components of ontologies include:

• Individuals: instances or objects (the basic or "ground level" objects)
• Classes In set theory and its applications throughout mathematics, a class is a collection of sets which can be unambiguously defined by a property that all its members share. The precise definition of "class" depends on foundational context. In work on ZF set theory, the notion of class is informal, whereas other set theories, such as NBG set: sets In set theory and its applications throughout mathematics, a class is a collection of sets which can be unambiguously defined by a property that all its members share. The precise definition of "class" depends on foundational context. In work on ZF set theory, the notion of class is informal, whereas other set theories, such as NBG set, collections, concepts, classes in programming In object-oriented programming, a class is a construct that is used as a blueprint to create objects of that class. This blueprint describes the state and behavior that the objects of the class all share. An object of a given class is called an instance of the class. The class that contains (and was used to create) that instance can be considered, types of objects Philosophers sometimes distinguish classes from types and kinds. We can talk about the class of human beings, just as we can talk about the type , human being, or humanity. How, then, might classes differ from types? One might well think they are not actually different categories of being, but typically, while both are treated as abstract objects,, or kinds of things.
• Attributes A good example is the process of XML assigning values to properties . Note that the element's value is found before the (separate) end tag, not in the element itself. The element itself may have a number of attributes set (NAME="IAMAPROPERTY"): aspects, properties, features, characteristics, or parameters that objects (and classes) can have
• Relations In mathematics, a binary relation on a set A is a collection of ordered pairs of elements of A. In other words, it is a subset of the Cartesian product A2 = A × A. More generally, a binary relation between two sets A and B is a subset of A × B. The terms dyadic relation and 2-place relation are synonyms for binary relations: ways in which classes and individuals 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
• Axioms: assertions (including rules) in a logical form The form or logical form of an argument is the representation of its sentences using the formal grammar and symbolism of a logical/formal system to display its similarity with all other arguments of the same type that together comprise the overall theory that the ontology describes in its domain of application. This definition differs from that of "axioms" in generative grammar In theoretical linguistics, generative grammar refers to a particular approach to the study of syntax. A generative grammar of a language attempts to give a set of rules that will correctly predict which combinations of words will form grammatical sentences. In most approaches to generative grammar, the rules will also predict the morphology of a and formal logic Mathematical logic is a subfield of mathematics with close connections to computer science and philosophical logic. The field includes both the mathematical study of logic and the applications of formal logic to other areas of mathematics. The unifying themes in mathematical logic include the study of the expressive power of formal systems and the. In those disciplines, axioms include only statements asserted as a priori knowledge. As used here, "axioms" also include the theory derived from axiomatic statements.
• Events In philosophy, events are objects in time or instantiations of properties in objects. However, a definite definition has not been reached, as multiple theories exist concerning events: the changing of attributes or relations

Ontologies are commonly encoded using ontology languages.

Domain ontologies and upper ontologies

A domain ontology (or domain-specific ontology) models a specific domain, or part of the world. It represents the particular meanings of terms as they apply to that domain. For example the word card Card primarily refers to an entire or piece of card stock. More generally, the term can refer to a small flat object has many different meanings. An ontology about the domain of poker Poker is a family of card games that share betting rules and usually hand rankings. Poker games differ in how the cards are dealt, how hands may be formed, whether the high or low hand wins the pot in a showdown (in some games, the pot is split between the high and low hands), limits on bets and how many rounds of betting are allowed. In most would model the "playing card A playing card is a piece of specially prepared heavy paper, thin cardboard, or thin plastic, figured with distinguishing motifs and used as one of a set for playing card games. Playing cards are typically palm-sized for convenient handling" meaning of the word, while an ontology about the domain of computer hardware A personal computer is made up of multiple physical components of computer hardware, upon which can be installed an operating system and a multitude of software to perform the operator's desired functions would model the "punched card" and "video card" meanings.

An upper ontology (or foundation ontology) is a model of the common objects that are generally applicable across a wide range of domain ontologies. It contains a core glossary in whose terms objects in a set of domains can be described. There are several standardized upper ontologies available for use, including Dublin Core, GFO, OpenCyc/ResearchCyc, SUMO, and DOLCE. WordNet, while considered an upper ontology by some, is not strictly an ontology. However, it has been employed as a linguistic tool for learning domain ontologies^[10].

The Gellish ontology is an example of a combination of an upper and a domain ontology.

Since domain ontologies represent concepts in very specific and often eclectic ways, they are often incompatible. As systems that rely on domain ontologies expand, they often need to merge domain ontologies into a more general representation. This presents a challenge to the ontology designer. Different ontologies in the same domain can also arise due to different perceptions of the domain based on cultural background, education, ideology, or because a different representation language was chosen.

At present, merging ontologies that are not developed from a common foundation ontology is a largely manual process and therefore time-consuming and expensive. Domain ontologies that use the same foundation ontology to provide a set of basic elements with which to specify the meanings of the domain ontology elements can be merged automatically. There are studies on generalized techniques for merging ontologies^{[citation needed]}, but this area of research is still largely theoretical.

Ontology engineering

Ontology engineering (or ontology building) is a subfield of knowledge engineering that studies the methods and methodologies for building ontologies. It studies the ontology development process, the ontology life cycle, the methods and methodologies for building ontologies, and the tool suites and languages that support them.^[11][12]

Ontology engineering aims to make explicit the knowledge contained within software applications, and within enterprises and business procedures for a particular domain. Ontology engineering offers a direction towards solving the interoperability problems brought about by semantic obstacles, such as the obstacles related to the definitions of business terms and software classes. Ontology engineering is a set of tasks related to the development of ontologies for a particular domain.^[13]

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