View source for Ontology (computer science)

{{Short description|Specification of a conceptualization}}
{{Information science}}
In [[Computer science|computer science]] and information science, an '''ontology''' encompasses a representation, formal naming, and definition of the categories, properties, and relations between the concepts, data, and entities that substantiate one, many, or all [[Philosophy:Domain of discourse|domains of discourse]]. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of concepts and categories that represent the subject.

Every [[Academic discipline|academic discipline]] or field creates ontologies to limit complexity and organize data into information and knowledge. 
Each uses ontological assumptions to frame explicit theories, research and applications. New ontologies may improve problem solving within that domain. Translating research papers within every field is a problem made easier when experts from different countries maintain a [[Controlled vocabulary|controlled vocabulary]] of [[Social:Jargon|jargon]] between each of their languages.<ref name="Budin2005">{{citation|author=G Budin|editor=Helle V. Dam|others=Jan Engberg, Heidrun Gerzymisch-Arbogast|title=Knowledge Systems and Translation|chapter-url=https://books.google.com/books?id=IL2E9xuJLAAC&pg=PA113|year=2005|publisher=Walter de Gruyter|isbn=978-3-11-018297-2|page=113|chapter=Ontology-driven translation management}}</ref>

For instance, the definition and ontology of economics is a primary concern in Marxist economics,<ref>{{cite journal|first=Giulio |last=Palermo|title=The ontology of economic power in capitalism: mainstream economics and Marx |journal=Cambridge Journal of Economics |volume=31 |issue=4 |pages=539–561 |date=10 January 2007 |doi=10.1093/cje/bel036 |via=Oxford Journals }}</ref> but also in other [[Biology:Outline of economics#Branches of economics|subfields of economics]].<ref>{{cite journal|author=Zuniga, Gloria L. |url=https://ideas.repec.org/p/pra/mprapa/5566.html |title=An Ontology Of Economic Objects |journal=Mpra Paper |publisher=Research Division of the Federal Reserve Bank of St. Louis |date=1999-02-02 |access-date=2013-06-16}}</ref> An example of economics relying on information science occurs in cases where a simulation or model is intended to enable economic decisions, such as determining what [[Finance:Capital asset|capital asset]]s are at risk and by how much (see [[Risk management|risk management]]).

What ontologies in both [[Computer science|computer science]] and [[Philosophy:Philosophy|philosophy]] have in common is the attempt to represent entities, ideas and events, with all their interdependent properties and relations, according to a system of categories. In both fields, there is considerable work on problems of [[Ontology engineering|ontology engineering]] (e.g., [[Biography:Willard Van Orman Quine|Quine]] and [[Biography:Saul Kripke|Kripke]] in philosophy, [[Biography:John F. Sowa|Sowa]] and Guarino in computer science),<ref>{{cite journal |first=J. F. |last=Sowa |title=Top-level ontological categories
|journal=International Journal of Human-Computer Studies |volume=43 |issue=5–6 (November/December)
|year=1995 |pages=669–85 |doi=10.1006/ijhc.1995.1068 }}</ref> and debates concerning to what extent [[Philosophy:Normative|normative]] ontology is possible (e.g., [[Philosophy:Foundationalism|foundationalism]] and [[Philosophy:Coherentism|coherentism]] in philosophy, [[Basic formal ontology|BFO]] and [[Software:Cyc|Cyc]] in artificial intelligence).

Applied ontology is considered a successor to prior work in philosophy, however many current efforts are more concerned with establishing controlled vocabularies of narrow domains than first principles, the existence of [[Philosophy:Essence|fixed essences]] or whether enduring objects (e.g., [[Philosophy:Perdurantism|perdurantism]] and [[Philosophy:Endurantism|endurantism]]) may be ontologically more primary than [[Process|process]]es. [[Artificial intelligence]] has retained the most attention regarding applied ontology in subfields like [[Natural language processing|natural language processing]] within [[Machine translation|machine translation]] and knowledge representation, but ontology editors are being used often in a range of fields like education without the intent to contribute to AI.<ref>{{cite journal|first=Mark |last=Musen|title=The Protégé Project: A Look Back and a Look Forward |journal=AI Matters|volume=1|issue=4|pages=4–12|doi=10.1145/2757001.2757003|pmid=27239556|pmc=4883684|year=2015}}</ref>

== Etymology ==
The compound word ''ontology'' combines ''onto-'', from the [[Social:Ancient Greek|Greek]] ὄν<!--[sic] (neuter), not ὤν (masculine)-->, ''on'' (gen. ὄντος, ''ontos''), i.e. "being; that which is", which is the present participle of the verb εἰμί, ''eimí'', i.e. "to be, I am", and -λογία, ''-logia'', i.e. "logical discourse", see [[Social:Classical compound|classical compound]]s for this type of word formation.<ref name=OnlineEtDict>{{cite dictionary|title=ontology|url=https://www.etymonline.com/word/ontology|dictionary=Online Etymology Dictionary}}</ref><ref name=LSJ>{{LSJ|ei)mi/1|εἰμί|ref}}</ref>

While the [[Social:Etymology|etymology]] is Greek, the oldest extant record of the word itself, the New Latin form ''ontologia'', appeared in 1606 in the work ''Ogdoas Scholastica'' by [[Biography:Jacob Lorhard|Jacob Lorhard]] (''Lorhardus'') and in 1613 in the ''Lexicon philosophicum'' by Rudolf Göckel (''Goclenius'').

The first occurrence in English of ''ontology'' as recorded by the ''OED'' (''Oxford English Dictionary'', online edition, 2008) came in ''Archeologia Philosophica Nova'' or ''New Principles of Philosophy'' by Gideon Harvey.

==History==
Ontologies arise out of the branch of [[Philosophy:Philosophy|philosophy]] known as [[Philosophy:Metaphysics|metaphysics]], which deals with questions like "what exists?" and "what is the nature of reality?". One of five traditional branches of philosophy, metaphysics is concerned with exploring existence through properties, entities and relations such as those between [[Physics:Particular|particular]]s and [[Philosophy:Universal (metaphysics)|universals]], [[Philosophy:Intrinsic and extrinsic properties|intrinsic and extrinsic properties]], or [[Philosophy:Essence|essence]] and [[Philosophy:Existence|existence]]. Metaphysics has been an ongoing topic of discussion since recorded history.

Since the mid-1970s, researchers in the field of [[Artificial intelligence|artificial intelligence]] (AI) have recognized that [[Knowledge engineering|knowledge engineering]] is the key to building large and powerful AI systems{{citation needed|date=February 2021}}. AI researchers argued that they could create new ontologies as [[Computational model|computational model]]s that enable certain kinds of [[Automated reasoning|automated reasoning]], which was only [[AI winter|marginally successful]]. 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-based systems|knowledge-based systems]]. In particular, David Powers introduced the word ''ontology'' to AI to refer to real world or robotic grounding,<ref>{{cite journal | first=David | last=Powers |year=1983 |title=Robot Intelligence| journal=Electronics Today International}}</ref><ref>{{cite journal | first=David | last=Powers |year=1984 | title=Natural Language the Natural Way|journal=Computer Compacts| volume=2 | issue=3–4 | pages=100–109 | doi=10.1016/0167-7136(84)90088-X }}</ref><ref>{{cite book | first1=David | last1=Powers |first2=Chris | last2=Turk |title=Machine Learning of Natural Language|publisher=Springer-Verlag|isbn=978-1-4471-1697-4|year=1989}}</ref> publishing in 1990 literature reviews emphasizing grounded ontology in association with the call for papers for a AAAI Summer Symposium Machine Learning of Natural Language and Ontology, with an expanded version published in SIGART Bulletin and included as a preface to the proceedings.<ref>{{cite conference| title=Preface: Goals, Issues and Directions in Machine Learning of Natural Language and Ontology|conference=AAAI Spring Symposium on Machine Learning of Natural Language and Ontology|first1=David | last1=Powers|publisher=DFKI|year=1991}}</ref>  Some researchers, drawing inspiration from philosophical ontologies, viewed computational ontology as a kind of applied philosophy.<ref name="TG08">{{cite encyclopedia |first=T. |last=Gruber |year=2008 |url=http://tomgruber.org/writing/ontology-definition-2007.htm  |title=Ontology |encyclopedia=Encyclopedia of Database Systems |editor1-first=Ling |editor1-last=Liu |editor2-first=M. Tamer |editor2-last=Özsu |publisher=Springer-Verlag|isbn=978-0-387-49616-0}}</ref>

In 1993, the widely cited web page and paper "Toward Principles for the Design of Ontologies Used for Knowledge Sharing" by [[Biography:Tom Gruber|Tom Gruber]]<ref name="TRG95">{{cite journal|last=Gruber|first=T.|year=1993|title=Toward Principles for the Design of Ontologies Used for Knowledge Sharing|journal=International Journal of Human-Computer Studies|volume=43|issue=5–6|pages=907–928|doi=10.1006/ijhc.1995.1081}}</ref> used ''ontology'' as a technical term in [[Computer science|computer science]] closely related to earlier idea of semantic networks and [[Taxonomy (general)|taxonomies]]. Gruber introduced the term as ''a specification of a conceptualization'': <blockquote>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.<ref name="TRG01">{{cite web |first=T. |last=Gruber |author-link=Tom Gruber |year=2001 |url=http://www-ksl.stanford.edu/kst/what-is-an-ontology.html |title=What is an Ontology? |publisher=[[Organization:Stanford University|Stanford University]] |access-date=2009-11-09 |archive-url=https://web.archive.org/web/20100716004426/http://www-ksl.stanford.edu/kst/what-is-an-ontology.html |archive-date=2010-07-16 |url-status=dead }}</ref></blockquote>

Attempting to distance ontologies from taxonomies and similar efforts in [[Engineering:Knowledge modeling|knowledge modeling]] that rely on [[Class (computer programming)|classes]] and [[Inheritance (object-oriented programming)|inheritance]], Gruber stated (1993): <blockquote>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 extension|conservative definitions]]&nbsp;&mdash; that is, definitions in the traditional logic sense that only introduce terminology and do not add any knowledge about the world.<ref>{{cite book |first=H. B. |last=Enderton |date=1972-05-12 |title=A Mathematical Introduction to Logic |location=San Diego, CA |publisher=Academic Press |edition=1 |page=[https://archive.org/details/mathematicalintr00ende/page/295 295] |isbn=978-0-12-238450-9 |postscript=2nd edition; January 5, 2001 |url-access=registration |url=https://archive.org/details/mathematicalintr00ende/page/295 }}</ref> To specify a conceptualization, one needs to state [[Axiom|axiom]]s that do constrain the possible interpretations for the defined terms.<ref name="TRG93">{{cite journal |first=Thomas R. |last=Gruber |author-link=Tom Gruber |date=June 1993 |url=http://tomgruber.org/writing/ontolingua-kaj-1993.pdf |title=A translation approach to portable ontology specifications |journal=Knowledge Acquisition |volume=5 |issue=2 |pages=199–220 |doi=10.1006/knac.1993.1008 |citeseerx= 10.1.1.101.7493 }}</ref></blockquote>

As refinement of Gruber's definition Feilmayr and Wöß (2016) stated: "An ontology is a formal, explicit specification of a shared conceptualization that is characterized by high semantic expressiveness required for increased complexity."<ref>{{cite journal |last1=Feilmayr|first1=Christina|last2=Wöß|first2=Wolfram|title=An analysis of ontologies and their success factors for application to business|journal=Data & Knowledge Engineering|volume=101|date=2016|pages=1–23 |doi=10.1016/j.datak.2015.11.003}}</ref>

== Components ==
Contemporary ontologies share many structural similarities, regardless of the language in which they are expressed.  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)
; [[Class (set theory)|Classes]]<!-- This deliberately links to the disambiguation page -->
: Sets, collections, concepts, classes in programming, [[Philosophy:Class|types of objects]] or kinds of things
; [[Attribute (computing)|Attributes]]
: Aspects, properties, features, characteristics or parameters that objects (and classes) can have
; [[Relation (mathematics)|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 [[Philosophy:Logical form|logical form]] that together comprise the overall theory that the ontology describes in its domain of application. This definition differs from that of "axioms" in [[Software:Generative grammar|generative grammar]] and formal logic.  In those disciplines, axioms include only statements asserted as ''a priori'' knowledge.  As used here, "axioms" also include the theory derived from axiomatic statements
; [[Philosophy:Event|Events]]<!-- this links  to the philosophy sense of 'Events' as that is currently the only article describing the issues around defining events in the ontology community-->
: The changing of attributes or relations

Ontologies are commonly encoded using [[Ontology language|ontology language]]s.

== Types ==
=== Domain ontology<!--linked from 'Domain ontology'--> ===
A domain ontology (or domain-specific ontology) represents concepts which belong to a realm of the world, such as biology or politics. Each domain ontology typically models domain-specific definitions of terms. For example, the word ''card'' has many different meanings. An ontology about the domain of [[Engineering:Poker|poker]] would model the "playing card" meaning of the word, while an ontology about the domain of [[Computer hardware|computer hardware]] would model the "[[Engineering:Punched card|punched card]]" and "[[Engineering:Video card|video card]]" meanings.

Since domain ontologies are written by different people, they represent concepts in very specific and unique ways, and are often incompatible within the same project. As systems that rely on domain ontologies expand, they often need to merge domain ontologies by hand-tuning each entity or using a combination of software merging and hand-tuning. This presents a challenge to the ontology designer. Different ontologies in the same domain arise due to different languages, different intended usage of the ontologies, and different perceptions of the domain (based on cultural background, education, ideology, etc.){{citation needed|date=February 2021}}.

At present, merging ontologies that are not developed from a common [[Upper ontology|upper ontology]] is a largely manual process and therefore time-consuming and expensive. Domain ontologies that use the same upper ontology to provide a set of basic elements with which to specify the meanings of the domain ontology entities can be merged with less effort. There are studies on generalized techniques for merging ontologies,<ref name="Dynamic Ontology Repair">{{cite web |url=http://dream.inf.ed.ac.uk/projects/dor/ |title=Project: Dynamic Ontology Repair |publisher= University of Edinburgh Department of Informatics|access-date=2 January 2012}}</ref> but this area of research is still ongoing, and it's a recent event to see the issue sidestepped by having multiple domain ontologies using the same upper ontology like the [[Organization:OBO Foundry|OBO Foundry]].

=== Upper ontology ===
{{Main|Upper ontology}}
An upper ontology (or foundation ontology) is a model of the commonly shared relations and objects that are generally applicable across a wide range of domain ontologies. It usually employs a core glossary that overarches the terms and associated object descriptions as they are used in various relevant domain ontologies.

Standardized upper ontologies available for use include [[Basic Formal Ontology|BFO]], BORO method, [[Dublin Core]], GFO, [[Software:Cyc|Cyc]], [[Suggested Upper Merged Ontology|SUMO]], [[Software:UMBEL|UMBEL]], the Unified Foundational Ontology (UFO),<ref>{{cite web|last=Giancarlo Guizzardi & Gerd Wagner|url=http://ceur-ws.org/Vol-125/paper2.pdf|access-date=31 March 2014|title=A Unified Foundational Ontology and some Applications of it in Business Modeling}}</ref> and [[Upper ontology#DOLCE|DOLCE]].<ref name="DOLCE">{{cite web |url=http://www.loa-cnr.it/DOLCE.html |title=Laboratory for Applied Ontology - DOLCE |publisher=Laboratory for Applied Ontology (LOA)|access-date=10 February 2011}}</ref><ref name="DOLCE-OWL">{{cite web |url=http://www.ontologydesignpatterns.org/ont/dul/DUL.owl |title=OWL version of DOLCE+DnS  |publisher=Semantic Technology Lab|access-date=21 February 2013}}</ref> [[Software:WordNet|WordNet]] has been considered an upper ontology by some and has been used as a linguistic tool for learning domain ontologies.<ref>{{cite journal |first1=Roberto |last1=Navigli  |first2=Paola |last2=Velardi |year=2004 |title=Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites |journal=Computational Linguistics |volume=30 |issue=2 |publisher=MIT Press |pages=151–179 |doi=10.1162/089120104323093276|citeseerx=10.1.1.329.6965 |s2cid=2453822 }}</ref>

=== Hybrid ontology ===
The [[Gellish]] ontology is an example of a combination of an upper and a domain ontology.

== Visualization ==
{{InfoMaps}}
A survey of ontology visualization methods is presented by Katifori et al.<ref>{{cite journal |last1=Katifori |first1=A. |last2=Halatsis |first2=C. |last3=Lepouras |first3=G. |last4=Vassilakis |first4=C. |last5=Giannopoulou |first5=E. |title=Ontology Visualization Methods - A Survey |journal=ACM Computing Surveys |volume=39 |issue=4 |page=10 |date=2007 |url=http://entrezneuron.googlecode.com/svn-history/r2/trunk/references/12-onto-vis-survey-final.pdf |archive-url=https://web.archive.org/web/20160304203317/http://entrezneuron.googlecode.com/svn-history/r2/trunk/references/12-onto-vis-survey-final.pdf |archive-date=4 March 2016 |doi=10.1145/1287620.1287621|citeseerx=10.1.1.330.3281 |s2cid=14205872 }}</ref> An updated survey of ontology visualization methods and tools was published by Dudás et al.<ref>{{cite journal |last1=Dudás |first1=M. |last2=Lohmann |first2=S. |last3=Svátek |first3=V. |last4=Pavlov |first4=D. |title=Ontology Visualization Methods and Tools: a Survey of the State of the Art |journal=Knowledge Engineering Review |volume=33 |issue=e10 |date=2018 |doi=10.1017/S0269888918000073|s2cid=52965103 }}</ref> The most established ontology visualization methods, namely indented tree and graph visualization are evaluated by Fu et al.<ref>{{cite conference |first1=Bo |last1=Fu |first2=Natalya F. |last2=Noy |first3=Margaret-Anne |last3=Storey |title=Indented Tree or Graph? A Usability Study of Ontology Visualization Techniques in the Context of Class Mapping Evaluation |book-title=The Semantic Web – ISWC 2013: 12th International Semantic Web Conference, Sydney, NSW, Australia, October 21–25, 2013, Proceedings, Part I |series=Lecture Notes in Computer Science |volume=8218 |pages=117–134 |doi=10.1007/978-3-642-41335-3_8 |isbn=978-3-642-41335-3 |publisher=Springer |location=Berlin |date=2013 |doi-access=free }}</ref> A visual language for ontologies represented in [[Web Ontology Language|OWL]] is specified by the ''Visual Notation for OWL Ontologies (VOWL)''.<ref>{{cite web |last1=Negru |first1=Stefan |last2=Lohmann |first2=Steffen |last3=Haag |first3=Florian |date=7 April 2014 |title=VOWL: Visual Notation for OWL Ontologies: Specification of Version 2.0 |website=Visual Data Web |url=http://vowl.visualdataweb.org/v2/ }}</ref>

== Engineering ==
{{Main|Ontology engineering}}
Ontology engineering (also called ontology building)  is a set of tasks related to the development of ontologies for a particular domain.<ref name="PIS00">{{cite journal|last1=Pouchard|first1=Line|last2=Ivezic|first2=Nenad|last3=Schlenoff|first3=Craig|date=March 2000|title=Ontology Engineering for Distributed Collaboration in Manufacturing|url=http://www.mel.nist.gov/msidlibrary/doc/AISfinal2.pdf|journal=Proceedings of the AIS2000 Conference}}</ref> It is a subfield of [[Knowledge engineering|knowledge engineering]] that studies the ontology development process, the ontology life cycle, the methods and methodologies for building ontologies, and the tools and languages that support them.<ref name="PFC04">{{cite book |first1=Ascunion |last1=Gómez-Pérez |first2=Mariano |last2=Fernández-López |first3=Oscar |last3=Corcho |year=2004 |title=Ontological Engineering: With Examples from the Areas of Knowledge Management, E-commerce and the Semantic Web |url=https://archive.org/details/springer_10.1007-b97353 |publisher=Springer |isbn=978-1-85233-551-9 |page=[https://archive.org/details/springer_10.1007-b97353/page/n411 403] |edition=1 }}</ref><ref name="DMN">{{cite journal |first1=Antonio |last1=De Nicola |first2=Michele |last2=Missikoff |first3=Roberto |last3=Navigli |year=2009 |url=http://www.dsi.uniroma1.it/~navigli/pubs/De_Nicola_Missikoff_Navigli_2009.pdf |title=A Software Engineering Approach to Ontology Building |journal=Information Systems |volume=34 |issue=2 |publisher=Elsevier |pages=258–275 | doi = 10.1016/j.is.2008.07.002 }}</ref>

Ontology engineering aims to make explicit the knowledge contained in software applications, and organizational procedures for a particular domain. Ontology engineering offers a direction for overcoming semantic obstacles, such as those related to the definitions of business terms and software classes. Known challenges with ontology engineering include:
# Ensuring the ontology is ''current'' with [[Philosophy:Domain knowledge|domain knowledge]] and term use
# Providing ''sufficient specificity and concept coverage'' for the domain of interest, thus minimizing the content completeness problem
# Ensuring the ontology can support its use cases

=== Editors ===
'''Ontology editors''' are applications designed to assist in the creation or manipulation of ontologies. It is common for ontology editors to use one or more ontology languages.

Aspects of ontology editors include: visual navigation possibilities within the knowledge model, [[Philosophy:Inference engine|inference engine]]s and [[Information extraction|information extraction]]; support for modules; the import and export of foreign knowledge representation languages for ontology matching; and the support of meta-ontologies such as [[OWL-S]], [[Dublin Core]], etc.<ref>{{cite journal |first=Emhimed |last=Alatrish |date=2013 |url=http://www.ef.uns.ac.rs/mis/archive-pdf/2013%20-%20No2/MIS2013-2-4.pdf |title=A comparison of some ontology editors |journal=Management Information Systems |volume=8 |issue=2 |pages=18–24}}</ref>

=== Learning ===
{{Main|Ontology learning}}
Ontology learning is the automatic or semi-automatic creation of ontologies, including extracting a domain's terms from natural language text. As building ontologies manually is extremely labor-intensive and time-consuming, there is great motivation to automate the process.  Information extraction and [[Text mining|text mining]] have been explored to automatically link ontologies to documents, for example in the context of the BioCreative challenges.<ref>{{Cite journal
 | pmid = 22438567
| year = 2012
| last1 = Krallinger
| first1 = M
| title = How to link ontologies and protein-protein interactions to literature: Text-mining approaches and the Bio ''Creative'' experience
| journal = Database
| volume = 2012
| pages = bas017
| last2 = Leitner
| first2 = F
| last3 = Vazquez
| first3 = M
| last4 = Salgado
| first4 = D
| last5 = Marcelle
| first5 = C
| last6 = Tyers
| first6 = M
| last7 = Valencia
| first7 = A
| last8 = Chatr-Aryamontri
| first8 = A
| doi = 10.1093/database/bas017
| pmc = 3309177
}}</ref>

=== Research ===
{{further|Philosophy:Epistemology}}

Epistemological assumptions, which in research asks "What do you know? or "How do you know it?", creates the foundation researchers use when approaching a certain topic or area for potential research. As epistemology is directly linked to knowledge and how we come about accepting certain truths, individuals conducting academic research must understand what allows them to begin theory building. Simply, epistemological assumptions force researchers to question how they arrive at the knowledge they have.{{citation needed|date=February 2022}}

== Languages ==
{{Main|Ontology language}}
An [[Ontology language|ontology language]] is a [[Formal language|formal language]] used to encode an ontology. There are a number of such languages for ontologies, both proprietary and standards-based:
* [[Common Algebraic Specification Language]] is a general logic-based specification language developed within the IFIP working group 1.3 "Foundations of System Specifications" and is a ''de facto'' standard language for software specifications. It is now being applied to ontology specifications in order to provide modularity and structuring mechanisms.
* Common logic is ISO standard 24707, a specification of a family of ontology languages that can be accurately translated into each other.
* The [[Software:Cyc|Cyc]] project has its own ontology language called [[CycL]], based on first-order predicate calculus with some higher-order extensions.
* DOGMA (Developing Ontology-Grounded Methods and Applications) adopts the fact-oriented modeling approach to provide a higher level of semantic stability.
* The [[Gellish]] language includes rules for its own extension and thus integrates an ontology with an ontology language.
* [[IDEF5]] is a [[Software engineering|software engineering]] method to develop and maintain usable, accurate, domain ontologies.
* [[Knowledge Interchange Format|KIF]] is a syntax for [[First-order logic|first-order logic]] that is based on [[S-expression]]s.  SUO-KIF is a derivative version supporting the [[Suggested Upper Merged Ontology]].
* [[Organization:Meta-Object Facility|MOF]] and [[Unified Modeling Language|UML]] are standards of the [[Organization:Object Management Group|OMG]]
* [[Olog]] is a [[Category theory|category theoretic]] approach to ontologies, emphasizing translations between ontologies using [[Functor|functor]]s. 
* [[Medicine:Open Biomedical Ontologies|OBO]], a language used for biological and biomedical ontologies.
* [[OntoUML]] is an ontologically well-founded profile of UML for conceptual modeling of domain ontologies.
* [[Web Ontology Language|OWL]] is a language for making ontological statements, developed as a follow-on from [[Resource Description Framework|RDF]] and RDFS, as well as earlier ontology language projects including [[Ontology Inference Layer|OIL]], [[DARPA Agent Markup Language|DAML]], and DAML+OIL. OWL is intended to be used over the [[World Wide Web]], and all its elements (classes, properties and individuals) are defined as RDF [[Web resource|resource]]s, and identified by [[Uniform Resource Identifier|URI]]s.
* [[Rule Interchange Format]] (RIF) and F-Logic combine ontologies and rules.
* [[Semantic Application Design Language]] (SADL)<ref>{{cite web |url=http://sadl.sourceforge.net/sadl.html |title=SADL |work=[[Software:SourceForge|SourceForge]] |access-date=10 February 2011}}</ref> captures a subset of the expressiveness of [[Web Ontology Language|OWL]], using an English-like language entered via an [[Software:Eclipse|Eclipse]] Plug-in.
* SBVR (Semantics of Business Vocabularies and Rules) is an OMG standard adopted in industry to build ontologies.
* TOVE Project, TOronto Virtual Enterprise project

== Published examples ==
* [[Arabic Ontology]], a linguistic ontology for Arabic, which can be used as an Arabic Wordnet but with ontologically-clean content.
* AURUM - Information Security Ontology,<ref>{{cite web |url=http://www.securityontology.com |title=AURUM - Information Security Ontology |access-date=29 January 2016}}</ref> An ontology for information security knowledge sharing, enabling users to collaboratively understand and extend the domain knowledge body. It may serve as a basis for automated information security risk and compliance management.
* [[Software:BabelNet|BabelNet]], a very large multilingual semantic network and ontology, lexicalized in many languages
* [[Basic Formal Ontology]],<ref>{{cite web |url=http://www.ifomis.org/bfo/ |title=Basic Formal Ontology (BFO)
|publisher=Institute for Formal Ontology and Medical Information Science (IFOMIS) }}</ref> a formal upper ontology designed to support scientific research
* BioPAX,<ref>{{cite web |url=http://biopax.org |title=BioPAX |access-date=10 February 2011}}</ref> an ontology for the exchange and interoperability of biological pathway (cellular processes) data
* BMO,<ref>{{cite journal |first1=Alexander |last1=Osterwalder |first2=Yves |last2=Pigneur |url=http://129.3.20.41/eps/io/papers/0202/0202004.pdf |title=An e-Business Model Ontology for Modeling e-Business |location=15th Bled eConference, Slovenia |date=June 17–19, 2002 |url-status=dead |archive-url=https://web.archive.org/web/20110419183256/http://129.3.20.41/eps/io/papers/0202/0202004.pdf |archive-date=2011-04-19 }}</ref> an e-Business Model Ontology based on a review of enterprise ontologies and business model literature
* SSBMO,<ref>{{cite journal |first1=Antony |last1=Upward |first2=Peter |last2=Jones |url=https://www.academia.edu/14461116 |title=An Ontology for Strongly Sustainable Business Models: Defining an Enterprise Framework Compatible with Natural and Social Science |journal=Organization & Environment |volume=29 |issue=1 |pages=97–123 |doi=10.1177/1086026615592933 |year=2016|s2cid=145089240 }}</ref> a Strongly Sustainable Business Model Ontology based on a review of the systems based natural and social science literature (including business).  Includes critique of and significant extensions to the Business Model Ontology (BMO).
* CCO and GexKB,<ref>{{cite web|title=About CCO and GexKB|url=http://www.semantic-systems-biology.org/apo/|archive-url=https://archive.today/20120730222759/http://www.semantic-systems-biology.org/apo/|url-status=dead|archive-date=2012-07-30|publisher=Semantic Systems Biology}}</ref> Application Ontologies (APO) that integrate diverse types of knowledge with the Cell Cycle Ontology (CCO) and the Gene Expression Knowledge Base (GexKB)
* CContology (Customer Complaint Ontology),<ref>{{cite web |url=http://www.jarrar.info/CContology/ |title=CContology |access-date=10 February 2011}}</ref> an e-business ontology to support online customer complaint management
* [[CIDOC Conceptual Reference Model]], an ontology for [[Social:Cultural heritage|cultural heritage]]<ref>{{cite web |url=http://www.cidoc-crm.org/ |title=The CIDOC Conceptual Reference Model (CRM) |access-date=10 February 2011}}</ref>
* COSMO,<ref>{{cite web |url=http://micra.com/COSMO/ |title=COSMO |publisher=MICRA Inc.|access-date=10 February 2011}}</ref> a Foundation Ontology (current version in OWL) that is designed to contain representations of all of the primitive concepts needed to logically specify the meanings of any domain entity.  It is intended to serve as a basic ontology that can be used to translate among the representations in other ontologies or databases.  It started as a merger of the basic elements of the OpenCyc and SUMO ontologies, and has been supplemented with other ontology elements (types, relations) so as to include representations of all of the words in the Longman dictionary defining vocabulary.
* [[Software:Computer Science Ontology|Computer Science Ontology]], an automatically generated ontology of research topics in the field of Computer Science
* [[Software:Cyc|Cyc]], a large Foundation Ontology for formal representation of the universe of discourse
* [[Biology:Disease Ontology|Disease Ontology]],<ref>{{cite journal |pmid=19594883 | doi=10.1186/1471-2164-10-S1-S6 | pmc=2709267 | volume=10 Suppl 1 | title=Annotating the human genome with Disease Ontology | journal=BMC Genomics | page=S6 | last1 = Osborne | first1 = JD | last2 = Flatow | first2 = J | last3 = Holko | first3 = M | last4 = Lin | first4 = SM | last5 = Kibbe | first5 = WA | last6 = Zhu | first6 = LJ | last7 = Danila | first7 = MI | last8 = Feng | first8 = G | last9 = Chisholm | first9 = RL | year=2009| issue=Suppl 1 }}</ref> designed to facilitate the mapping of diseases and associated conditions to particular medical codes
* [[Upper ontology#DOLCE|DOLCE]], a Descriptive Ontology for Linguistic and Cognitive Engineering<ref name="DOLCE"/><ref name="DOLCE-OWL"/>
* Drammar, ontology of drama<ref>{{Cite journal|last1=Damiano|first1=Rossana|last2=Lombardo|first2=Vincenzo|last3=Pizzo|first3=Antonio|date=2005|editor-last=Subsol|editor-first=Gérard|title=Formal Encoding of Drama Ontology|journal=Virtual Storytelling. Using Virtual Reality Technologies for Storytelling|volume=3805|series=Lecture Notes in Computer Science|language=en|publisher=Springer Berlin Heidelberg|pages=95–104|doi=10.1007/11590361_11|isbn=9783540322856|url=https://iris.unito.it/bitstream/2318/148510/1/chp%253A10.1007%252F11590361_11.pdf|hdl=2318/148510|hdl-access=free}}</ref>{{Citation needed|date=August 2018}}
* [[Dublin Core]], a simple ontology for documents and publishing
* Financial Industry Business Ontology (FIBO),  a business conceptual ontology for the financial industry<ref>{{cite web |url=http://www.omg.org/hot-topics/finance.htm |title=Financial Industry Business Ontology (FIBO) |access-date=15 March 2017}}</ref> 
* Foundational, Core and Linguistic Ontologies<ref>{{cite web |url=http://www.loa-cnr.it/Ontologies.html
|title=Foundational, Core and Linguistic Ontologies |access-date=10 February 2011}}</ref>
* [[Organization:Foundational Model of Anatomy|Foundational Model of Anatomy]],<ref>{{cite web |url=http://sig.biostr.washington.edu/projects/fm/AboutFM.html |title=Foundational Model of Anatomy |access-date=10 February 2011}}</ref> an ontology for human anatomy
* Friend of a Friend, an ontology for describing persons, their activities and their relations to other people and objects
* [[Biology:Gene Ontology|Gene Ontology]] for [[Biology:Genomics|genomics]]
* Gellish English dictionary, an ontology that includes a dictionary and taxonomy that includes an upper ontology and a lower ontology that focusses on industrial and business applications in engineering, technology and procurement.
* [[Geopolitical ontology]], an ontology describing geopolitical information created by Food and Agriculture Organization(FAO). The geopolitical ontology includes names in multiple languages (English, French, Spanish, Arabic, Chinese, Russian and Italian); maps standard coding systems (UN, ISO, FAOSTAT, AGROVOC, etc.); provides relations among territories (land borders, group membership, etc.); and tracks historical changes. In addition, FAO provides web services of geopolitical ontology and a module maker to download modules of the geopolitical ontology into different formats (RDF, XML, and EXCEL). See more information at [[Software:FAO Country Profiles|FAO Country Profiles]].
* GAO (General Automotive Ontology) - an ontology for the automotive industry that includes 'car' extensions<ref>{{cite web |url=https://makolab.com/en/innovation/schema-org-automotive-extension |title=Car Extension |access-date=15 June 2017}}</ref>
* GOLD,<ref>{{cite web |url=http://www.linguistics-ontology.org/gold.html |title=GOLD |access-date=10 February 2011}}</ref> General Ontology for Linguistic Description
* GUM (Generalized Upper Model),<ref>{{cite web |url=http://www.fb10.uni-bremen.de/anglistik/langpro/webspace/jb/gum/index.htm |title=Generalized Upper Model |access-date=10 February 2011}}</ref> a linguistically motivated ontology for mediating between clients systems and natural language technology
* [[IDEAS Group]],<ref>{{cite web |url=http://www.ideasgroup.org |title=The IDEAS Group Website |access-date=10 February 2011 |archive-url=https://web.archive.org/web/20181216021632/http://www.ideasgroup.org/ |archive-date=16 December 2018 |url-status=dead }}</ref> a formal ontology for enterprise architecture being developed by the Australian, Canadian, UK and U.S. Defence Depts.
* Linkbase,<ref>{{cite web |url=http://www.landcglobal.com/pages/linkbase.php |title=Linkbase |access-date=10 February 2011 |url-status=dead |archive-url=https://web.archive.org/web/20080918063746/http://www.landcglobal.com/pages/linkbase.php |archive-date=18 September 2008 }}</ref> a formal representation of the biomedical domain, founded upon Basic Formal Ontology.
* LPL, Landmark Pattern Language<ref>[https://docs.infor.com/help_lmrk_cloudsuite_11.0/topic/com.lawson.help.developer/InforLandmarkConfigurationConsoleLPL.pdf Configuration Console Reference Guide: Landmark Pattern Language (LPL)]. Retrieved 4 February 2020.</ref>
* NCBO Bioportal,<ref>{{cite web|title=Bioportal|url=http://www.bioontology.org/tools/portal/bioportal.html|publisher=National Center for Biological Ontology (NCBO)|access-date=2013-10-24|archive-url=https://web.archive.org/web/20090612212543/http://www.bioontology.org/tools/portal/bioportal.html|archive-date=2009-06-12|url-status=dead}}</ref> biological and biomedical ontologies and associated tools to search, browse and visualise
* NIFSTD Ontologies from the [[Biology:Neuroscience Information Framework|Neuroscience Information Framework]]: a modular set of ontologies for the neuroscience domain.
* OBO-Edit,<ref>{{cite web|title=Ontology browser for most of the Open Biological and Biomedical Ontologies|url=http://oboedit.org/?page=index|publisher=Berkeley Bioinformatics Open Source Project (BBOP)}}</ref> an ontology browser for most of the Open Biological and Biomedical Ontologies
* [[Organization:OBO Foundry|OBO Foundry]],<ref>{{cite web|title=The Open Biological and Biomedical Ontologies|url=http://www.obofoundry.org/|publisher=Berkeley Bioinformatics Open Source Project (BBOP)}}</ref> a suite of interoperable reference ontologies in biology and biomedicine
* OMNIBUS Ontology,<ref>{{cite web |url=http://edont.qee.jp/omnibus/ |archive-url=https://archive.today/20120719151539/http://edont.qee.jp/omnibus/ |url-status=dead |archive-date=19 July 2012 |title=OMNIBUS Ontology |access-date=10 February 2011 }}</ref> an ontology of learning, instruction, and instructional design
* [[Medicine:Ontology for Biomedical Investigations|Ontology for Biomedical Investigations]], an open-access, integrated ontology of biological and clinical investigations
* ONSTR,<ref>{{cite web |url= https://nbsdc.org/onstr.php |title= ONSTR |access-date= 16 April 2014 |archive-url= https://web.archive.org/web/20140416231158/https://nbsdc.org/onstr.php |archive-date= 16 April 2014 |url-status= dead |df= dmy-all }}</ref> Ontology for Newborn Screening Follow-up and Translational Research, Newborn Screening Follow-up Data Integration Collaborative, Emory University, Atlanta.
* Plant Ontology<ref name="Plant Ontology">{{cite web |url=http://www.plantontology.org/ |title=Plant Ontology |access-date=10 February 2011}}</ref> for plant structures and growth/development stages, etc.
* POPE, Purdue Ontology for Pharmaceutical Engineering
* PRO,<ref>{{cite web |url=http://pir.georgetown.edu/pro/ |title=PRO |access-date=10 February 2011 |archive-url=https://web.archive.org/web/20110310192741/http://pir.georgetown.edu/pro/ |archive-date=10 March 2011 |url-status=dead }}</ref> the Protein Ontology of the Protein Information Resource, Georgetown University
* [[ProbOnto]], knowledge base and ontology of [[Probability distribution|probability distribution]]s.<ref>{{cite web |url=http://www.probonto.org |title=ProbOnto |access-date=1 July 2017}}</ref><ref>{{cite journal|pmid=27153608 | doi=10.1093/bioinformatics/btw170 | pmc=5013898  | volume=32 | issue=17 | pages=2719–21 | title=ProbOnto: ontology and knowledge base of probability distributions | year=2016 | journal=Bioinformatics | last1 = Swat | first1 = MJ | last2 = Grenon | first2 = P | last3 = Wimalaratne | first3 = S}}</ref>
* Program abstraction taxonomy{{Citation needed|date=August 2018}}
* Protein Ontology<ref>{{cite web |url=http://pir.georgetown.edu/pro/ |title=Protein Ontology |access-date=10 February 2011 |archive-url=https://web.archive.org/web/20110310192741/http://pir.georgetown.edu/pro/ |archive-date=10 March 2011 |url-status=dead }}</ref> for [[Biology:Proteomics|proteomics]]
* RXNO Ontology, for [[Chemistry:Name reaction|name reaction]]s in chemistry
*SCDO, the Sickle Cell Disease Ontology,<ref>{{Cite journal|last1=Nembaware|first1=Victoria|last2=Mazandu|first2=Gaston K.|last3=Hotchkiss|first3=Jade|last4=Safari Serufuri|first4=Jean-Michel|last5=Kent|first5=Jill|last6=Kengne|first6=Andre Pascal|last7=Anie|first7=Kofi|last8=Munung|first8=Nchangwi Syntia|last9=Bukini|first9=Daima|last10=Bitoungui|first10=Valentina Josiane Ngo|last11=Munube|first11=Deogratias|date=2020-10-01|title=The Sickle Cell Disease Ontology: Enabling Collaborative Research and Co-Designing of New Planetary Health Applications|journal=OMICS: A Journal of Integrative Biology|volume=24|issue=10|pages=559–567|doi=10.1089/omi.2020.0153|pmc=7549008|pmid=33021900}}</ref> facilitates data sharing and collaborations within the SDC community, amongst other applications (see list on [https://scdontology.h3abionet.org/ SCDO website]).
* [[Biology:Sequence Ontology|Sequence Ontology]],<ref>{{cite journal |vauthors= Eilbeck K, Lewis SE, Mungall CJ, Yandell M, Stein L, Durbin R, Ashburner M |title= The Sequence Ontology: a tool for the unification of genome annotations |journal= Genome Biology |volume= 6 |issue= 5 |pages= R44 |year= 2005 |pmid= 15892872 |pmc= 1175956 |doi= 10.1186/gb-2005-6-5-r44 |author-link6= Richard M. Durbin |author-link7= Michael Ashburner |author-link2= Suzanna Lewis}}</ref> for representing genomic feature types found on [[Biology:Sequence|biological sequences]]
* [[Medicine:SNOMED CT|SNOMED CT]] (Systematized Nomenclature of Medicine—Clinical Terms)
* [[Suggested Upper Merged Ontology]],<ref>Niles, I., & Pease, A., (2001), Toward a Standard Upper Ontology, in Proceedings of the 2nd International Conference on Formal Ontology in Information Systems (FOIS-2001), Chris Welty and Barry Smith, eds, pp2-9.</ref> a formal upper ontology
* [[Biology:Systems Biology Ontology|Systems Biology Ontology]] (SBO), for computational models in biology
* SWEET,<ref>{{cite web |url=http://sweetontology.net |title=SWEET |access-date=11 March 2022}}</ref> Semantic Web for Earth and Environmental Terminology
* SSN/SOSA,<ref>{{cite web |url=https://www.w3.org/TR/vocab-ssn/ |title=SSN |access-date=10 November 2021}}</ref> The Semantic Sensor Network Ontology (SSN) and Sensor, Observation, Sample, and Actuator Ontology (SOSA) are W3C Recommendation  and OGC Standards for describing sensors and their observations.
* ThoughtTreasure ontology
* [[TIME-ITEM]], Topics for Indexing Medical Education
* [[Biology:Uberon|Uberon]],<ref>{{cite journal|pmid=22293552 | doi=10.1186/gb-2012-13-1-r5 | pmc=3334586 | volume=13 | issue=1 | title=Uberon, an integrative multi-species anatomy ontology | year=2012 | journal=Genome Biol. | page=R5 | last1 = Mungall | first1 = CJ | last2 = Torniai | first2 = C | last3 = Gkoutos | first3 = GV | last4 = Lewis | first4 = SE | last5 = Haendel | first5 = MA}}</ref> representing animal anatomical structures
* [[Software:UMBEL|UMBEL]], a lightweight reference structure of 20,000 subject concept classes and their relationships derived from OpenCyc
* [[Software:WordNet|WordNet]], a lexical reference system
* YAMATO,<ref>{{cite web |url=http://www.ei.sanken.osaka-u.ac.jp/hozo/onto_library/upperOnto.htm |title=YAMATO |access-date=10 February 2011 |archive-url=https://web.archive.org/web/20110303225900/http://www.ei.sanken.osaka-u.ac.jp/hozo/onto_library/upperOnto.htm |archive-date=3 March 2011 |url-status=dead }}</ref> Yet Another More Advanced Top-level Ontology

The W3C [[Linked data#Linking Open Data community project|Linking Open Data community project]] coordinates attempts to converge different ontologies into worldwide [[Semantic Web]].

== Libraries ==
The development of ontologies has led to the emergence of services providing lists or directories of ontologies called ontology libraries.

The following are libraries of human-selected ontologies.
* COLORE<ref>{{cite web |url=http://stl.mie.utoronto.ca/colore/ |title=COLORE |access-date=4 May 2011}}</ref> is an open repository of first-order ontologies in [[Common Logic]] with formal links between ontologies in the repository.
* DAML Ontology Library<ref>{{cite web |url=http://www.daml.org/ontologies/ |title=DAML Ontology Library |access-date=10 February 2011}}</ref> maintains a legacy of ontologies in DAML.
* Ontology Design Patterns portal<ref>{{cite web |url=http://www.ontologydesignpatterns.org |title=ODP Library |access-date=21 February 2013}}</ref> is a wiki repository of reusable components and practices for ontology design, and also maintains a list of ''exemplary ontologies''. 
* Protégé Ontology Library<ref>{{cite web
|url=http://protegewiki.stanford.edu/index.php/Protege_Ontology_Library |title=Protege Ontology Library |access-date=10 February 2011}}</ref> contains a set of OWL, Frame-based and other format ontologies.
* SchemaWeb<ref>{{cite web |url=http://www.schemaweb.info/ |title=SchemaWeb |access-date=10 February 2011 |url-status=dead |archive-url=https://web.archive.org/web/20110810084028/http://www.schemaweb.info/ |archive-date=10 August 2011 }}</ref> is a directory of RDF schemata expressed in RDFS, OWL and DAML+OIL.

The following are both directories and search engines.
* [[Organization:OBO Foundry|OBO Foundry]] is a suite of interoperable reference ontologies in biology and biomedicine.<ref>{{cite web |url=http://www.obofoundry.org/ |title=OBO Foundry|access-date=10 February 2011}}</ref><ref name="pmid17989687">{{Cite journal 
| last1 = Smith | first1 = B. 
| last2 = Ashburner | first2 = M. 
| last3 = Rosse | first3 = C. 
| last4 = Bard | first4 = J. 
| last5 = Bug | first5 = W. 
| last6 = Ceusters | first6 = W. 
| last7 = Goldberg | first7 = L. J. 
| last8 = Eilbeck | first8 = K. 
| last9 = Ireland | first9 = A. 
| last10 = Mungall 
| doi = 10.1038/nbt1346 | first10 = C. J. 
| last11 = Leontis | first11 = N. 
| last12 = Rocca-Serra | first12 = P. 
| last13 = Ruttenberg | first13 = A. 
| last14 = Sansone | first14 = S. A. 
| last15 = Scheuermann | first15 = R. H. 
| last16 = Shah | first16 = N. 
| last17 = Whetzel | first17 = P. L. 
| title = The OBO Foundry: Coordinated evolution of ontologies to support biomedical data integration 
| journal = [[Engineering:Nature Biotechnology|Nature Biotechnology]] 
| volume = 25 
| issue = 11 
| pages = 1251–1255 
| year = 2007 
| pmid = 17989687 
| pmc =2814061 
}} {{open access}}</ref>
* Bioportal (ontology repository of NCBO)<ref>{{Cite web|url=https://bioportal.bioontology.org/|title=Welcome to the NCBO BioPortal {{!}} NCBO BioPortal|website=bioportal.bioontology.org|access-date=2019-03-28}}</ref>
* OntoSelect<ref>{{cite web |url=http://olp.dfki.de/OntoSelect/ |title=OntoSelect |access-date=10 February 2011 |archive-url=https://web.archive.org/web/20101111053552/http://olp.dfki.de/ontoselect/ |archive-date=11 November 2010 |url-status=dead |df=dmy-all }}</ref> Ontology Library offers similar services for RDF/S, DAML and OWL ontologies.
* Ontaria<ref>{{cite web |url=http://www.w3.org/2004/ontaria/ |title=Ontaria |access-date=10 February 2011}}</ref> is a "searchable and browsable directory of semantic web data" with a focus on RDF vocabularies with OWL ontologies. (NB Project "on hold" since 2004).
* [[Software:Swoogle|Swoogle]] is a directory and search engine for all RDF resources available on the Web, including ontologies.
* Open Ontology Repository initiative<ref>{{Cite web|url=http://ontologforum.org/index.php/OpenOntologyRepository|title=OpenOntologyRepository - OntologPSMW|website=ontologforum.org|access-date=2019-03-28}}</ref>
* ROMULUS is a foundational ontology repository aimed at improving semantic interoperability. Currently there are three foundational ontologies in the repository: [[Upper ontology#DOLCE|DOLCE]], [[Basic Formal Ontology|BFO]] and [[General formal ontology|GFO]].{{Citation needed|date=August 2018}}

== Examples of applications ==
In general, ontologies can be used beneficially in several fields.
* Enterprise applications.<ref>{{cite journal |first=Daniel |last=Oberle |title=How ontologies benefit enterprise applications |journal=Semantic Web |volume=5 |issue=6 |pages=473–491 |publisher=IOS Press |date=2014 |doi=10.3233/SW-130114 |url=http://www.semantic-web-journal.net/system/files/swj212_2.pdf }}</ref> A more concrete example is [[Software:SAPPHIRE (Health care)|SAPPHIRE (Health care)]] or ''Situational Awareness and Preparedness for Public Health Incidences and Reasoning Engines'' which is a [[Philosophy:Semantics|semantics]]-based health information system capable of tracking and evaluating situations and occurrences that may affect public health.
* Geographic information systems bring together data from different sources and benefit therefore from ontological metadata which helps to connect the semantics of the data.<ref>{{cite journal|first=Andrew U. |last=Frank|title=Tiers of ontology and consistency constraints in geographical information systems|journal=International Journal of Geographical Information Science|volume=15|issue=7|year=2001|pages=667–678|doi=10.1080/13658810110061144|s2cid=6616354}}</ref>
* Domain-specific ontologies are extremely important in biomedical research, which requires named entity disambiguation of various biomedical terms and abbreviations that have the same string of characters but represent different biomedical concepts. For example, CSF can represent Colony Stimulating Factor or Cerebral Spinal Fluid, both of which are represented by the same term, CSF, in biomedical literature.<ref>{{Cite journal|title=Disambiguation of ambiguous biomedical terms using examples generated from the UMLS Metathesaurus|journal=Journal of Biomedical Informatics|volume=43|issue=5|pages=762–773|doi=10.1016/j.jbi.2010.06.001|pmid=20541624|year=2010|last1=Stevenson|first1=Mark|last2=Guo|first2=Yikun|doi-access=free}}</ref> This is why a large number of public ontologies are related to the life sciences. Life science data science tools that fail to implement these types of biomedical ontologies will not be able to accurately determine causal relationships between concepts.<ref>{{Cite journal|title=Biomedical Ontologies|journal=Pac Symp Biocomput|pages=76–78|pmc=4300097|year=2005|author1=BODENREIDER O|author2=MITCHELL JA|author3=MCCRAY AT|pmid=15759615|doi=10.1142/9789812704856_0016|isbn=978-981-238-598-7}}</ref>

== See also ==
{{div col|colwidth=25em}}
* Commonsense knowledge bases
* [[Concept map]]
* [[Controlled vocabulary]]
* [[Classification scheme (information science)]]
* [[Folksonomy]]
* [[Formal concept analysis]]
* [[Formal ontology]]
* [[Knowledge graph]]
* [[Lattice (order)|Lattice]]
* [[Philosophy:Ontology|Ontology]]
* [[Ontology alignment]]
* [[Ontology chart]]
* [[Software:Open Semantic Framework|Open Semantic Framework]]
* [[Engineering:Semantic technology|Semantic technology]]
* Soft ontology
* [[Terminology extraction]]
* Weak ontology
* [[Web Ontology Language]]
{{div col end}}

;Related philosophical concepts
* [[Philosophy:Alphabet of human thought|Alphabet of human thought]]
* [[Characteristica universalis]]
* [[Engineering:Interoperability|Interoperability]]
* [[Level of measurement]]
* [[Philosophy:Metalanguage|Metalanguage]]
* Natural semantic metalanguage

== References ==
{{Reflist}}

== Further reading ==
*{{cite book |last1=Oberle |first1=D. |last2=Guarino |first2=N. |last3=Staab |first3=S. |chapter=What is an ontology? |chapter-url=https://iaoa.org/isc2012/docs/Guarino2009_What_is_an_Ontology.pdf |title={{harvnb|Staab|Studer|2009}} |year=2009 |pages=1–17 |doi=10.1007/978-3-540-92673-3_0|isbn=978-3-540-70999-2 }}
*{{cite journal |last1=Fensel |first1=D. |last2=van Harmelen |first2=F. |last3=Horrocks |first3=I. |last4=McGuinness |first4=D.L. |last5=Patel-Schneider |first5=P.F. |title=OIL: an ontology infrastructure for the Semantic Web |journal=IEEE Intelligent Systems |volume=16 |issue=2 |pages=38–45 |year=2001 |doi=10.1109/5254.920598 |url=}}
*{{cite book |last1=Gangemi |first1=A. |last2=Presutti |first2=V. |chapter=Ontology Design Patterns |chapter-url=http://www.academia.edu/download/6070620/handbookchapter_odps.pdf |editor= |title={{harvnb|Staab|Studer|2009}} |pages= }}
*{{cite book |first1=M. |last1=Golemati |first2=A. |last2=Katifori |first3=C. |last3=Vassilakis |first4=G. |last4=Lepouras |first5=C. |last5=Halatsis |chapter=Creating an Ontology for the User Profile# Method and Applications |chapter-url=http://oceanis.mm.di.uoa.gr/pened/papers/11-onto-user-final.pdf |title=Proceedings of the First IEEE International Conference on Research Challenges in Information Science (RCIS), Morocco 2007 |publisher= |year=2007 |citeseerx=10.1.1.74.9399|archive-url=https://web.archive.org/web/20081217030517/http://oceanis.mm.di.uoa.gr/pened/papers/11-onto-user-final.pdf |archive-date=2008-12-17 }}
*{{cite journal |first=R. |last=Mizoguchi |title=Tutorial on ontological engineering: Part 3: Advanced course of ontological engineering |journal=New Gener Comput |volume=22 |issue= |pages=193–220 |year=2004 |doi=10.1007/BF03040960 |s2cid=23747079 |url=http://www.ei.sanken.osaka-u.ac.jp/pub/miz/Part3V3.pdf |access-date=2009-06-08 |archive-date=2013-03-09 |archive-url=https://web.archive.org/web/20130309053905/http://www.ei.sanken.osaka-u.ac.jp/pub/miz/Part3V3.pdf |url-status=dead }}
* {{cite journal | last1 = Gruber | first1 = T. R. |  year = 1993 | title = A translation approach to portable ontology specifications | url = http://tomgruber.org/writing/ontolingua-kaj-1993.pdf | journal = Knowledge Acquisition | volume = 5 | issue = 2| pages = 199–220 | doi=10.1006/knac.1993.1008| citeseerx = 10.1.1.101.7493 }}
*{{cite journal |last1=Maedche |first1=A. |last2=Staab |first2=S. |title=Ontology learning for the Semantic Web |journal=IEEE Intelligent Systems |volume=16 |issue=2 |pages=72–79 |year=2001 |doi=10.1109/5254.920602 |url=}}
*{{cite document |first1=Natalya F. |last1=Noy |first2=Deborah L. |last2=McGuinness |title=Ontology Development 101: A Guide to Creating Your First Ontology |date=March 2001 |id=Stanford Knowledge Systems Laboratory Technical Report KSL-01-05, Stanford Medical Informatics Technical Report SMI-2001-0880 |url=http://www-ksl.stanford.edu/people/dlm/papers/ontology-tutorial-noy-mcguinness-abstract.html|archive-url=https://web.archive.org/web/20100714172301/http://www-ksl.stanford.edu/people/dlm/papers/ontology-tutorial-noy-mcguinness-abstract.html |archive-date=2010-07-14 }}
* {{cite journal | last1 = Chaminda Abeysiriwardana | first1 = Prabath | last2 = Kodituwakku | first2 = Saluka R | year = 2012 | title = Ontology Based Information Extraction for Disease Intelligence | journal = International Journal of Research in Computer Science | volume = 2 | issue = 6| pages = 7–19 | doi = 10.7815/ijorcs.26.2012.051 | arxiv = 1211.3497 | bibcode = 2012arXiv1211.3497C | s2cid = 11297019 }}
*{{cite book |last1=Razmerita |first1=L. |last2=Angehrn |first2=A. |last3=Maedche |first3=A. |chapter=Ontology-Based User Modeling for Knowledge Management Systems |chapter-url=https://link.springer.com/chapter/10.1007/3-540-44963-9_29 |title=User Modeling 2003 |publisher=Springer |year=2003 |isbn=3-540-44963-9 |pages=213–7 |series=Lecture Notes in Computer Science |volume=2702 |doi=10.1007/3-540-44963-9_29 |citeseerx=10.1.1.102.4591}}
*{{cite book |last1=Soylu |first1=A. |last2=De Causmaecker |first2=Patrick |chapter=Merging model driven and ontology driven system development approaches pervasive computing perspective |title=Proceedings of the 24th International Symposium on Computer and Information Sciences |year=2009 |isbn= 978-1-4244-5021-3|pages=730–5 |doi=10.1109/ISCIS.2009.5291915|s2cid=2267593 |chapter-url=https://lirias.kuleuven.be/retrieve/117211 }}
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*{{cite book |editor-first=S. |editor-last=Staab |editor2-first=R. |editor2-last=Studer |editor2-link=Rudi Studer |title=Handbook on Ontologies |publisher=Springer |edition=2nd |year=2009 |isbn=978-3-540-92673-3 |pages= |doi=10.1007/978-3-540-92673-3_0}}
*{{cite journal |last1=Uschold |first1=Mike |last2=Gruninger |first2=M. |title=Ontologies: Principles, Methods and Applications |journal=Knowledge Engineering Review |volume=11 |issue=2 |pages=93–136 |year=1996 |doi=10.1017/S0269888900007797 |citeseerx=10.1.1.111.5903|s2cid=2618234 }}
*{{cite web |first=W. |last=Pidcock |title=What are the differences between a vocabulary, a taxonomy, a thesaurus, an ontology, and a meta-model? |date= |url=http://infogrid.org/wiki/Reference/PidcockArticle|archive-url=https://web.archive.org/web/20091014123802/http://infogrid.org/wiki/Reference/PidcockArticle |archive-date=2009-10-14 }}
*{{cite book |last1=Yudelson |first1=M. |last2=Gavrilova |first2=T. |last3=Brusilovsky |first3=P. |chapter=Towards User Modeling Meta-ontology |doi=10.1007/11527886_62 |chapter-url= |title=User Modeling 2005 |publisher=Springer |year=2005 |isbn=978-3-540-31878-1 |pages=448–452 |series=Lecture Notes in Computer Science |volume=3538 |citeseerx=10.1.1.86.7079}}
*{{cite book |last1=Movshovitz-Attias |first1=Dana |last2=Cohen |first2=William W. |chapter=Bootstrapping Biomedical Ontologies for Scientific Text using NELL |chapter-url=https://www.cs.cmu.edu/~dmovshov/papers/dma_bioNELL_bioNLP2012.pdf |title=Proceedings of the 2012 Workshop on Biomedical Natural Language Processing |publisher=Association for Computational Linguistics |year=2012 |pages=11–19 |citeseerx=10.1.1.376.2874}}

== External links ==
* Knowledge Representation at Open Directory Project
* [http://protegewiki.stanford.edu/wiki/Protege_Ontology_Library Library of ontologies]
* [http://www.GoPubMed.com GoPubMed] using Ontologies for searching
* [http://ontolog.cim3.net/wiki ONTOLOG] (a.k.a. "[http://ontolog.cim3.net/forum/ontolog-forum/ Ontolog Forum]") - an Open, International, Virtual Community of Practice on Ontology, Ontological Engineering and Semantic Technology
* [http://trimc-nlp.blogspot.com/2013/08/nlp-driven-ontology-modeling-for.html Use of Ontologies in Natural Language Processing]
* [http://ontolog.cim3.net/cgi-bin/wiki.pl?OntologySummit Ontology Summit] - an annual series of events (first started in 2006) that involves the ontology community and communities related to each year's theme chosen for the summit.
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* [http://kore-nordmann.de/talks/09_04_standardization_of_ontologies_paper.pdf Standardization of Ontologies]

{{Non-classical logic}}
{{Semantic Web}}
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{{DEFAULTSORT:Ontology (Information Science)}}
[[Category:Knowledge engineering]]
[[Category:Technical communication]]
[[Category:Information science]]
[[Category:Semantic Web]]
[[Category:Knowledge representation]]
[[Category:Knowledge bases]]
[[Category:Ontology editors]]

{{Sourceattribution|Ontology (computer science)|1}}