Wed .19 Oct 2019
TR | RU | UK | KK | BE |

Ontology (information science)

ontology (information science)
In computer science and information science, an ontology is a formal naming and definition of the types, properties, and interrelationships of the entities that really or fundamentally exist for a particular domain of discourse It is thus a practical application of philosophical ontology, with a taxonomy

An ontology compartmentalizes the variables needed for some set of computations and establishes the relationships between them

The fields of artificial intelligence, the Semantic Web, systems engineering, software engineering, biomedical informatics, library science, enterprise bookmarking, and information architecture all create ontologies to limit complexity and to organize information The ontology can then be applied to problem solving


  • 1 Etymology and definition
  • 2 Overview
  • 3 History
  • 4 Components
  • 5 Types
    • 51 Domain ontology
    • 52 Upper ontology
    • 53 Hybrid ontology
  • 6 Visualization
  • 7 Engineering
    • 71 Editor
    • 72 Learning
  • 8 Languages
  • 9 Published examples
  • 10 Libraries
  • 11 Examples of applications
  • 12 See also
  • 13 References
  • 14 Further reading
  • 15 External links

Etymology and definition

The term ontology has its origin in philosophy and has been applied in many different ways The word element onto- comes from the Greek ὤν, ὄντος, "being", "that which is", present participle of the verb εἰμί "be" The core meaning within computer science is a model for describing the world that consists of a set of types, properties, and relationship types There is also generally an expectation that the features of the model in an ontology should closely resemble the real world related to the object


What many ontologies have 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, there is considerable work on problems of ontological relativity eg, Quine and Kripke in philosophy, Sowa and Guarino in computer science, and debates concerning whether a normative ontology is viable eg, debates over foundationalism in philosophy, and over the Cyc project in AI Differences between the two are largely matters of focus Computer scientists are more concerned with establishing fixed, controlled vocabularies, while philosophers are more concerned with first principles, such as whether there are such things as fixed essences or whether enduring objects must be ontologically more primary than processes

Other fields make ontological assumptions that are sometimes explicitly elaborated and explored For instance, the definition and ontology of economics also sometimes called the political economy is hotly debated especially in Marxist economics where it is a primary concern, but also in other subfields Such concerns intersect with those of information science when a simulation or model is intended to enable decisions in the economic realm; for example, to determine what capital assets are at risk and if so by how much see risk management Some claim all social sciences have explicit ontology issues because they do not have hard falsifiability criteria like most models in physical sciences and that indeed the lack of such widely accepted hard falsification criteria is what defines a social or soft science


Historically, ontologies arise out of the branch of philosophy known as metaphysics, 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 and universals, between intrinsic and extrinsic properties, and between essence and existence 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

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 and Cyc, with comparatively little debate over how they were built

Since the mid-1970s, researchers in the field of artificial intelligence AI 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 that enable certain kinds of automated reasoning 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

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 is credited with a deliberate definition of ontology as a technical term in computer science Gruber introduced the term to mean a specification of a conceptualization:

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

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 To specify a conceptualization, one needs to state axioms that do constrain the possible interpretations for the defined terms


Main article: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:

IndividualsInstances or objects the basic or "ground level" objectsClassesSets, collections, concepts, classes in programming, types of objects, or kinds of thingsAttributesAspects, properties, features, characteristics, or parameters that objects and classes can haveRelationsWays in which classes and individuals can be related to one anotherFunction termsComplex structures formed from certain relations that can be used in place of an individual term in a statementRestrictionsFormally stated descriptions of what must be true in order for some assertion to be accepted as inputRulesStatements 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 formAxiomsAssertions including rules in a 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 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 statementsEventsThe changing of attributes or relations

Ontologies are commonly encoded using ontology languages


Domain ontology

A domain ontology or domain-specific ontology represents concepts which belong to part of the world Particular meanings of terms applied to that domain are provided by domain ontology For example, the word card has many different meanings An ontology about the domain of poker would model the "playing card" meaning of the word, while an ontology about the domain of computer hardware would model the "punched card" and "video card" meanings

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 arise due to different languages, different intended usage of the ontologies, and different perceptions of the domain based on cultural background, education, ideology, etc

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, but this area of research is still largely theoretical

Upper ontology

Main article:Upper ontology

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 usually employs a core glossary that contains the terms and associated object descriptions as they are used in various relevant domain sets

There are several standardized upper ontologies available for use, including BFO, BORO method, Dublin Core, GFO, OpenCyc/ResearchCyc, SUMO, the Unified Foundational Ontology UFO, 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

Hybrid ontology

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


A survey of ontology visualization techniques is presented by Katifori et al An evaluation of two most established ontology visualization techniques:indented tree and graph is discussed in A visual language for ontologies represented in OWL is specified by the Visual Notation for OWL Ontologies VOWL


Main article:Ontology engineering

Ontology engineering or ontology building is a subfield of knowledge engineering 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

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

Known challenges with ontology engineering include:

  1. Ensuring the ontology is current with domain knowledge and term use
  2. Providing sufficient specificity and concept coverage for the domain of interest, thus minimizing the content completeness problem
  3. Ensuring the ontology can support its use cases


Ontology editors are applications designed to assist in the creation or manipulation of ontologies They often express ontologies in one of many ontology languages Some provide export to other ontology languages however

Among the most relevant criteria for choosing an ontology editor are the degree to which the editor abstracts from the actual ontology representation language used for persistence and the visual navigation possibilities within the knowledge model Next come built-in inference engines and information extraction facilities, and the support of meta-ontologies such as OWL-S, Dublin Core, etc Another important feature is the ability to import & export foreign knowledge representation languages for ontology matching Ontologies are developed for a specific purpose and application

  • aka software Ontology, taxonomy and thesaurus management software available from The Synercon Group
  • Anzo for Excel Includes an RDFS and OWL ontology editor within Excel; generates ontologies from Excel spreadsheets
  • Chimaera Other web service by Stanford
  • CmapTools Ontology Editor COE Java based ontology editor from the Florida Institute for Human and Machine Cognition Supports numerous formats
  • dot15926 Editor Open source ontology editor for data compliant to engineering ontology standard ISO 15926 Allows Python scripting and pattern-based data analysis Supports extensions
  • EMFText OWL2 Manchester Editor, Eclipse-based, open-source, Pellet integration
  • Enterprise Architect, along with UML modeling, supports OMG's Ontology Definition MetaModel which includes OWL and RDF
  • Fluent Editor, a comprehensive ontology editor for OWL and SWRL with Controlled Natural Language Controlled English Supports OWL, RDF, DL and Functional rendering, unlimited imports and built-in reasoning services
  • HOZO Java-based graphical editor especially created to produce heavy-weight and well thought out ontologies, from Osaka University and Enegate Co, ltd
  • Java Ontology Editor JOE 1998
  • KAON single user and server based solutions possible, open source, from FZI/AIFB Karlsruhe
  • KMgen Ontology editor for the KM language km:The Knowledge Machine
  • Knoodl Free web application/service that is an ontology editor, wiki, and ontology registry Supports creation of communities where members can collaboratively import, create, discuss, document and publish ontologies Supports OWL, RDF, RDFS, and SPARQL queries Available since early Nov 2006 from Revelytix, Inc
  • Model Futures IDEAS AddIn free A plug-in for Sparx Systems Enterprise Architect that allows IDEAS Group 4D ontologies to be developed using a UML profile
  • Model Futures OWL Editor Free Able to work with very large OWL files eg Cyc and has extensive import and export capabilities inc UML, Thesaurus Descriptor, MS Word, CA ERwin Data Modeler, CSV, etc
  • myWeb Java-based, mySQL connection, bundled with applet that allows online browsing of ontologies including OBO
  • Neologism Web-based, open source, supports RDFS and a subset of OWL, built on Drupal
  • NeOn Toolkit Eclipse-based, open source, OWL support, several import mechanisms, support for reuse and management of networked ontologies, visualization, etc…from NeOn Project
  • OBO-Edit Java-based, downloadable, open source, developed by the Gene Ontology Consortium for editing biological ontologies
  • OntoStudio Eclipse-based, downloadable, support for RDFS, OWL and F-Logic, graphical rule editor, visualizations, from ontoprise
  • Ontolingua Web service offered by Stanford University
  • Open Semantic Framework OSF, an integrated software stack using semantic technologies for knowledge management, which includes an ontology editor
  • OWLGrEd A graphical ontology editor, easy-to-use
  • PoolParty Thesaurus Server Commercial ontology, taxonomy and thesaurus management software available from Semantic Web Company, fully based on standards like RDFS, SKOS and SPARQL, integrated with Virtuoso Universal Server
  • Protégé Java-based, downloadable, Supports OWL, open source, many sample ontologies, from Stanford University
  • ScholOnto net-centric representations of research
  • Semantic Turkey Firefox extension - also based on Java - for managing ontologies and acquiring new knowledge from the Web; developed at University of Rome, Tor Vergata
  • Sigma knowledge engineering environment is a system primarily for development of the Suggested Upper Merged Ontology
  • Swoop Java-based, downloadable, open source, OWL Ontology browser and editor from the University of Maryland
  • Semaphore Ontology Manager Commercial ontology, taxonomy and thesaurus management software available from Smartlogic Semaphore Limited Intuitive tool to manage the entire "build - enhance - review - maintain" ontology lifecycle
  • Synaptica Ontology, taxonomy and thesaurus management software available from Synaptica, LLC Web based, supports OWL and SKOS
  • TopBraid Composer Eclipse-based, downloadable, full support for RDFS and OWL, built-in inference engine, SWRL editor and SPARQL queries, visualization, import of XML and UML, from TopQuadrant
  • Transinsight The editor is especially designed for creating text mining ontologies and part of GoPubMedorg
  • WebODE Web service offered by the Technical University of Madrid
  • TwoUse Toolkit Eclipse-based, open source, model-driven ontology editing environment especially designed for software engineers
  • Be Informed Suite Commercial tool for building large ontology based applications Includes visual editors, inference engines, export to standard formats
  • Thesaurus Master Manages creation and use of ontologies for use in data management and semantic enrichment by enterprise, government, and scholarly publishers
  • TODE A Dot Net-based Tool for Ontology Development and Editing
  • VocBench Collaborative Web Application for SKOS/SKOS-XL Thesauri Management - developed on a joint effort between University of Rome, Tor Vergata and the Food and Agriculture Organization of the United Nations:FAO
  • OBIS Web based user interface that allows to input ontology instances in a user friendly way that can be accessed via SPARQL endpoint
  • Menthor Editor An ontology engineering tool for dealing with OntoUML It also includes OntoUML syntax validation, Alloy simulation, Anti-Pattern verification, and transformations from OntoUML to OWL, SBVR and Natural Language Brazilian Portuguese


Main article: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 methods have been explored to automatically link ontologies to documents, eg in the context of the BioCreative challenges


Main article:Ontology language

An ontology language is a formal language used to encode the 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 13 "Foundations of System Specifications" and functions as a de facto standard in the area of 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 for a family of ontology languages that can be accurately translated into each other
  • The 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 method to develop and maintain usable, accurate, domain ontologies
  • KIF is a syntax for first-order logic that is based on S-expressions SUO-KIF is a derivative version supporting the Suggested Upper Merged Ontology
  • MOF and UML are standards of the OMG
  • Olog is a category theoretic approach to ontologies, emphasizing translations between ontologies using functors
  • OBO, a language used for biological and biomedical ontologies
  • OntoUML is an ontologically well-founded profile of UML for conceptual modeling of domain ontologies
  • OWL is a language for making ontological statements, developed as a follow-on from RDF and RDFS, as well as earlier ontology language projects including OIL, 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 resources, and identified by URIs
  • Rule Interchange Format RIF and F-Logic combine ontologies and rules
  • Semantic Application Design Language SADL captures a subset of the expressiveness of OWL, using an English-like language entered via an 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

  • AURUM - Information Security Ontology, 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
  • BabelNet, a very large multilingual semantic network and ontology, lexicalized in many languages
  • Basic Formal Ontology, a formal upper ontology designed to support scientific research
  • BioPAX, an ontology for the exchange and interoperability of biological pathway cellular processes data
  • BMO, an e-Business Model Ontology based on a review of enterprise ontologies and business model literature
  • CCO and GexKB, 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, an e-business ontology to support online customer complaint management
  • CIDOC Conceptual Reference Model, an ontology for cultural heritage
  • COSMO, 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
  • Cyc, a large Foundation Ontology for formal representation of the universe of discourse
  • Disease Ontology, designed to facilitate the mapping of diseases and associated conditions to particular medical codes
  • DOLCE, a Descriptive Ontology for Linguistic and Cognitive Engineering
  • Drammar, ontology of drama
  • Dublin Core, a simple ontology for documents and publishing
  • Foundational, Core and Linguistic Ontologies
  • Foundational Model of Anatomy, an ontology for human anatomy
  • Friend of a Friend, an ontology for describing persons, their activities and their relations to other people and objects
  • Gene Ontology for 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 OrganizationFAO 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 FAO Country Profiles
  • GOLD, General Ontology for Linguistic Description
  • GUM Generalized Upper Model, a linguistically motivated ontology for mediating between clients systems and natural language technology
  • IDEAS Group, a formal ontology for enterprise architecture being developed by the Australian, Canadian, UK and US Defence Depts
  • Linkbase, a formal representation of the biomedical domain, founded upon Basic Formal Ontology
  • LPL, Lawson Pattern Language
  • NCBO Bioportal, biological and biomedical ontologies and associated tools to search, browse and visualise
  • NIFSTD Ontologies from the Neuroscience Information Framework:a modular set of ontologies for the neuroscience domain
  • OBO-Edit, an ontology browser for most of the Open Biological and Biomedical Ontologies
  • OBO Foundry, a suite of interoperable reference ontologies in biology and biomedicine
  • OMNIBUS Ontology, an ontology of learning, instruction, and instructional design
  • Ontology for Biomedical Investigations, an open access, integrated ontology for the description of biological and clinical investigations
  • ONSTR, Ontology for Newborn Screening Follow-up and Translational Research, Newborn Screening Follow-up Data Integration Collaborative, Emory University, Atlanta
  • Plant Ontology for plant structures and growth/development stages, etc
  • POPE, Purdue Ontology for Pharmaceutical Engineering
  • PRO, the Protein Ontology of the Protein Information Resource, Georgetown University
  • Program abstraction taxonomy
  • Protein Ontology for proteomics
  • RXNO Ontology, for name reactions in chemistry
  • Sequence Ontology, for representing genomic feature types found on biological sequences
  • SNOMED CT Systematized Nomenclature of Medicine—Clinical Terms
  • Suggested Upper Merged Ontology, a formal upper ontology
  • Systems Biology Ontology SBO, for computational models in biology
  • SWEET, Semantic Web for Earth and Environmental Terminology
  • ThoughtTreasure ontology
  • TIME-ITEM, Topics for Indexing Medical Education
  • Uberon, representing animal anatomical structures
  • UMBEL, a lightweight reference structure of 20,000 subject concept classes and their relationships derived from OpenCyc
  • WordNet, a lexical reference system
  • YAMATO, Yet Another More Advanced Top-level Ontology

The W3C Linking Open Data community project coordinates attempts to converge different ontologies into worldwide Semantic Web


The development of ontologies for the Web has led to the emergence of services providing lists or directories of ontologies with search facility Such directories have been called ontology libraries

The following are libraries of human-selected ontologies

  • COLORE is an open repository of first-order ontologies in Common Logic with formal links between ontologies in the repository
  • DAML Ontology Library maintains a legacy of ontologies in DAML
  • Ontology Design Patterns portal is a wiki repository of reusable components and practices for ontology design, and also maintains a list of exemplary ontologies
  • Protégé Ontology Library contains a set of OWL, Frame-based and other format ontologies
  • SchemaWeb is a directory of RDF schemata expressed in RDFS, OWL and DAML+OIL

The following are both directories and search engines They include crawlers searching the Web for well-formed ontologies

  • OBO Foundry is a suite of interoperable reference ontologies in biology and biomedicine
  • Bioportal ontology repository of NCBO
  • OntoSelect Ontology Library offers similar services for RDF/S, DAML and OWL ontologies
  • Ontaria 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
  • Swoogle is a directory and search engine for all RDF resources available on the Web, including ontologies
  • Open Ontology Repository initiative
  • ROMULUS is a foundational ontology repository aimed at improving semantic interoperability Currently there are three foundational ontologies in the repository:DOLCE, BFO and GFO

Examples of applications

In general, ontologies can be used beneficially in

  • enterprise applications A more concrete example is SAPPHIRE Health care or Situational Awareness and Preparedness for Public Health Incidences and Reasoning Engines which is a 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

See also

  • Commonsense knowledge bases
  • Controlled vocabulary
  • Folksonomy
  • Formal concept analysis
  • Formal ontology
  • Gene Ontology
  • General formal ontology
  • Lattice
  • Ontology
  • Ontology alignment
  • Ontology chart
  • Open Biomedical Ontologies
  • Open Semantic Framework
  • Soft ontology
  • Terminology extraction
  • Weak ontology
  • Web Ontology Language
Related philosophical concepts
  • Alphabet of human thought
  • Characteristica universalis
  • Interoperability
  • Metalanguage
  • Natural semantic metalanguage


  1. ^ a b Gruber, Thomas R June 1993 "A translation approach to portable ontology specifications" PDF Knowledge Acquisition 5 2:199–220 doi:101006/knac19931008 
  2. ^ Arvidsson, F; Flycht-Eriksson, A "Ontologies I" PDF Retrieved 26 November 2008 
  3. ^ Garshol, L M 2004 "Metadata Thesauri Taxonomies Topic Maps! Making sense of it all" Retrieved 13 October 2008 
  4. ^ Sowa, J F 1995 "Top-level ontological categories" International Journal of Human-Computer Studies 43 5-6 November/December:669–85 doi:101006/ijhc19951068 
  5. ^ Palermo, Giulio 10 January 2007 "The ontology of economic power in capitalism:mainstream economics and Marx" Cambridge Journal of Economics 31 4:539–561 doi:101093/cje/bel036 Retrieved 16 June 2013 – via Oxford Journals 
  6. ^ Zuniga, Gloria L 1999-02-02 "An Ontology Of Economic Objects" Ideas Research Division of the Federal Reserve Bank of St Louis Retrieved 2013-06-16 
  7. ^ Benjamin, Perakath C; Menzel, Christopher P; Mayer, Richard J; Fillion, Florence; Futrell, Michael T; deWitte, Paula S; Lingineni, Madhavi September 21, 1994 "IDEF5 Method Report" PDF Knowledge Based Systems, Inc 
  8. ^ Gruber, T 2008 Liu, Ling; Özsu, M Tamer, eds Ontology Encyclopedia of Database Systems Springer-Verlag ISBN 978-0-387-49616-0 
  9. ^ Gruber, T 1995 "Toward Principles for the Design of Ontologies Used for Knowledge Sharing" International Journal of Human-Computer Studies 43 5-6:907–928 doi:101006/ijhc19951081 
  10. ^ Gruber, T 2001 "What is an Ontology" Stanford University Retrieved 2009-11-09 
  11. ^ Enderton, H B 1972-05-12 A Mathematical Introduction to Logic 1 ed San Diego, CA:Academic Press p 295 ISBN 978-0-12-238450-9 2nd edition; January 5, 2001, ISBN 978-0-12-238452-3 
  12. ^ "Project:Dynamic Ontology Repair" University of Edinburgh Department of Informatics Retrieved 2 January 2012 
  13. ^ Giancarlo Guizzardi & Gerd Wagner "A Unified Foundational Ontology and some Applications of it in Business Modeling" PDF Retrieved 31 March 2014 
  14. ^ a b "Laboratory for Applied Ontology - DOLCE" Laboratory for Applied Ontology LOA Retrieved 10 February 2011 
  15. ^ a b "OWL version of DOLCE+DnS" Semantic Technology Lab Retrieved 21 February 2013 
  16. ^ Navigli, Roberto; Velardi, Paola 2004 "Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites" PDF Computational Linguistics MIT Press 30 2:151–179 doi:101162/089120104323093276 
  17. ^ Katifori, A; Halatsis, C; Lepouras, G; Vassilakis, C; Giannopoulou, E 2007 "Ontology Visualization Methods - A Survey" PDF ACM Computing Surveys 39 4:10 Archived from the original PDF on 4 March 2016 
  18. ^ Fu, Bo; Noy, Natalya F; Storey, Margaret-Anne 2013 "Indented Tree or Graph A Usability Study of Ontology Visualization Techniques in the Context of Class Mapping Evaluation" The Semantic Web – ISWC 2013:12th International Semantic Web Conference, Sydney, NSW, Australia, October 21–25, 2013, Proceedings, Part I Lecture Notes in Computer Science 8218 Berlin:Springer pp 117–134 doi:101007/978-3-642-41335-3_8 ISBN 978-3-642-41335-3 – via SpringerLink 
  19. ^ Negru, Stefan; Lohmann, Steffen; Haag, Florian 7 April 2014 "VOWL:Visual Notation for OWL Ontologies:Specification of Version 20" Visual Data Web 
  20. ^ Gómez-Pérez, Ascunion; Fernández-López, Mariano; Corcho, Oscar 2004 Ontological Engineering:With Examples from the Areas of Knowledge Management, E-commerce and the Semantic Web 1 ed Springer p 403 ISBN 978-1-85233-551-9 
  21. ^ De Nicola, Antonio; Missikoff, Michele; Navigli, Roberto 2009 "A Software Engineering Approach to Ontology Building" PDF Information Systems Elsevier 34 2:258–275 doi:101016/jis200807002 
  22. ^ Pouchard, Line; Ivezic, Nenad; Schlenoff, Craig March 2000 "Ontology Engineering for Distributed Collaboration in Manufacturing" PDF Proceedings of the AIS2000 conference 
  23. ^ Krallinger, M; Leitner, F; Vazquez, M; Salgado, D; Marcelle, C; Tyers, M; Valencia, A; Chatr-Aryamontri, A 2012 "How to link ontologies and protein-protein interactions to literature:Text-mining approaches and the Bio Creative experience" Database 2012:bas017 doi:101093/database/bas017 PMC 3309177 PMID 22438567 
  24. ^ "SADL" Sourceforge Retrieved 10 February 2011 
  25. ^ "AURUM - Information Security Ontology" Retrieved 29 January 2016 
  26. ^ "Basic Formal Ontology BFO" Institute for Formal Ontology and Medical Information Science IFOMIS 
  27. ^ "BioPAX" Retrieved 10 February 2011 
  28. ^ Osterwalder, Alexander; Pigneur, Yves June 17–19, 2002 "An e-Business Model Ontology for Modeling e-Business" PDF 15th Bled eConference, Slovenia 
  29. ^ "About CCO and GexKB" Semantic Systems Biology 
  30. ^ "CContology" Retrieved 10 February 2011 
  31. ^ "The CIDOC Conceptual Reference Model CRM" Retrieved 10 February 2011 
  32. ^ "COSMO" MICRA Inc Retrieved 10 February 2011 
  33. ^PMID 19594883  Missing or empty |title= help
  34. ^ "Foundational, Core and Linguistic Ontologies" Retrieved 10 February 2011 
  35. ^ "Foundational Model of Anatomy" Retrieved 10 February 2011 
  36. ^ "GOLD" Retrieved 10 February 2011 
  37. ^ "Generalized Upper Model" Retrieved 10 February 2011 
  38. ^ "The IDEAS Group Website" Retrieved 10 February 2011 
  39. ^ "Linkbase" Retrieved 10 February 2011 
  40. ^ "Bioportal" National Center for Biological Ontology NCBO 
  41. ^ "Ontology browser for most of the Open Biological and Biomedical Ontologies" Berkeley Bioinformatics Open Source Project BBOP 
  42. ^ "The Open Biological and Biomedical Ontologies" Berkeley Bioinformatics Open Source Project BBOP 
  43. ^ "OMNIBUS Ontology" Retrieved 10 February 2011 
  44. ^ "ONSTR" Retrieved 16 April 2014 
  45. ^ "Plant Ontology" Retrieved 10 February 2011 
  46. ^ "PRO" Retrieved 10 February 2011 
  47. ^ "Protein Ontology" Retrieved 10 February 2011 
  48. ^ Eilbeck K, Lewis SE, Mungall CJ, Yandell M, Stein L, Durbin R, Ashburner M 2005 "The Sequence Ontology:a tool for the unification of genome annotations" Genome Biology 6 5:R44 doi:101186/gb-2005-6-5-r44 PMC 1175956 PMID 15892872 
  49. ^ "SWEET" Retrieved 10 February 2011 
  50. ^PMID 22293552  Missing or empty |title= help
  51. ^ "YAMATO" Retrieved 10 February 2011 
  52. ^ "COLORE" Retrieved 4 May 2011 
  53. ^ "DAML Ontology Library" Retrieved 10 February 2011 
  54. ^ "ODP Library" Retrieved 21 February 2013 
  55. ^ "Protege Ontology Library" Retrieved 10 February 2011 
  56. ^ "SchemaWeb" Retrieved 10 February 2011 
  57. ^ "OBO Foundry" Retrieved 10 February 2011 
  58. ^ Smith, B; Ashburner, M; Rosse, C; Bard, J; Bug, W; Ceusters, W; Goldberg, L J; Eilbeck, K; Ireland, A; Mungall, C J; Leontis, N; Rocca-Serra, P; Ruttenberg, A; Sansone, S A; Scheuermann, R H; Shah, N; Whetzel, P L; Lewis, S 2007 "The OBO Foundry:Coordinated evolution of ontologies to support biomedical data integration" Nature Biotechnology 25 11:1251–1255 doi:101038/nbt1346 PMC 2814061 PMID 17989687 
  59. ^ "OntoSelect" Retrieved 10 February 2011 
  60. ^ "Ontaria" Retrieved 10 February 2011 
  61. ^ Oberle, Daniel 2014 "How ontologies benefit enterprise applications" PDF Semantic Web Journal IOS Press 5 6:473–491 doi:103233/SW-130114 
  62. ^ Frank, Andrew U 2001 "Tiers of ontology and consistency constraints in geographical information systems" International Journal of Geographical Information Science 15 7:667–678 doi:101080/13658810110061144 

Further reading

  • Oberle, D, Guarino, N, & Staab, S 2009 What is an ontology In:"Handbook on Ontologies" Springer, 2nd edition, 2009
  • Fensel, D, van Harmelen, F, Horrocks, I, McGuinness, D L, & Patel-Schneider, P F 2001 "OIL:an ontology infrastructure for the Semantic Web" In:Intelligent Systems IEEE, 162:38–45
  • Gangemi A, Presutti V 2009 Ontology Design Patterns In Staab S et al eds:Handbook on Ontologies 2nd edition, Springer, 2009
  • Maria Golemati, Akrivi Katifori, Costas Vassilakis, George Lepouras, Constantin Halatsis 2007 "Creating an Ontology for the User Profile:Method and Applications" In:Proceedings of the First IEEE International Conference on Research Challenges in Information Science RCIS, Morocco 2007
  • Mizoguchi, R 2004 "Tutorial on ontological engineering:part 3:Advanced course of ontological engineering" In:New Generation Computing Ohmsha & Springer-Verlag, 222:198-220
  • Gruber, T R 1993 "A translation approach to portable ontology specifications" In:Knowledge Acquisition 5:199–199
  • Maedche, A & Staab, S 2001 "Ontology learning for the Semantic Web" In:Intelligent Systems IEEE, 162:72–79
  • Natalya F Noy and Deborah L McGuinness Ontology Development 101:A Guide to Creating Your First Ontology Stanford Knowledge Systems Laboratory Technical Report KSL-01-05 and Stanford Medical Informatics Technical Report SMI-2001-0880, March 2001
  • Prabath Chaminda Abeysiriwardana, Saluka R Kodituwakku, "Ontology Based Information Extraction for Disease Intelligence" International Journal of Research in Computer Science, 2 6:pp 7–19, November 2012 doi:107815/ijorcs262012051
  • Razmerita, L, Angehrn, A, & Maedche, A 2003 "Ontology-Based User Modeling for Knowledge Management Systems" In:Lecture Notes in Computer Science:213–17
  • Soylu, A, De Causmaecker, Patrick 2009Merging model driven and ontology driven system development approaches pervasive computing perspective in Proc 24th Intl Symposium on Computer and Information Sciences pp 730–735
  • Smith, B Ontology Science, in C Eschenbach and M Gruninger eds, Formal Ontology in Information Systems Proceedings of FOIS 2008, Amsterdam/New York:ISO Press, 21–35
  • Uschold, Mike & Gruninger, M 1996 Ontologies:Principles, Methods and Applications Knowledge Engineering Review, 112
  • W Pidcock, What are the differences between a vocabulary, a taxonomy, a thesaurus, an ontology, and a meta-model
  • Yudelson, M, Gavrilova, T, & Brusilovsky, P 2005 Towards User Modeling Meta-ontology Lecture Notes in Computer Science, 3538:448
  • Movshovitz-Attias, Dana and Cohen, William W 2012 Bootstrapping Biomedical Ontologies for Scientific Text using NELL BioNLP in NAACL, Association for Computational Linguistics, 2012

External links

  • Knowledge Representation at Open Directory Project
  • Library of ontologies
  • GoPubMed using Ontologies for searching
  • ONTOLOG aka "Ontolog Forum" - an Open, International, Virtual Community of Practice on Ontology, Ontological Engineering and Semantic Technology
  • Use of Ontologies in Natural Language Processing
  • 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
  • Standardization of Ontologies

ontology (information science)

Ontology (information science) Information about

Ontology (information science)

  • user icon

    Ontology (information science) beatiful post thanks!


Ontology (information science)
Ontology (information science)
Ontology (information science) viewing the topic.
Ontology (information science) what, Ontology (information science) who, Ontology (information science) explanation

There are excerpts from wikipedia on this article and video

Random Posts

The San Francisco Examiner

The San Francisco Examiner

The San Francisco Examiner is a longtime daily newspaper distributed in and around San Francisco, Ca...
Frederator Films

Frederator Films

Frederator Films is an animation studio founded by Fred Seibert as part of Frederator Studios, with ...
John Hasbrouck Van Vleck

John Hasbrouck Van Vleck

John Hasbrouck Van Vleck March 13, 1899 – October 27, 1980 was an American physicist and mathematici...
Christian Lacroix

Christian Lacroix

Christian Marie Marc Lacroix French pronunciation: ​kʁistjɑ̃ lakʁwa; born 16 May 1951 is a Fren...