Ontology (information science)

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This article is about ontology in information science. Ontology (information science)_sentence_0

For the study of the nature of being, see Ontology. Ontology (information science)_sentence_1

In 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 domains of discourse. Ontology (information science)_sentence_2

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. Ontology (information science)_sentence_3

Every academic discipline or field creates ontologies to limit complexity and organize data into information and knowledge. Ontology (information science)_sentence_4

New ontologies improve problem solving within that domain. Ontology (information science)_sentence_5

Translating research papers within every field is a problem made easier when experts from different countries maintain a controlled vocabulary of jargon between each of their languages. Ontology (information science)_sentence_6

Etymology Ontology (information science)_section_0

Main article: Ontology § Etymology Ontology (information science)_sentence_7

The compound word ontology combines -, from the Greek , on (gen. Ontology (information science)_sentence_8

ὄντος, ontos), i.e. "being; that which is", which is the present participle of the verb , eimí, i.e. "to be, I am", and , , i.e. "logical discourse", see classical compounds for this type of word formation. Ontology (information science)_sentence_9

While the 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 Jacob Lorhard (Lorhardus) and in 1613 in the Lexicon philosophicum by Rudolf Göckel (Goclenius). Ontology (information science)_sentence_10

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. Ontology (information science)_sentence_11

Overview Ontology (information science)_section_1

What ontologies in both information science and 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. Ontology (information science)_sentence_12

In both fields, there is considerable work on problems of ontology engineering (e.g., Quine and Kripke in philosophy, Sowa and Guarino in computer science), and debates concerning to what extent normative ontology is possible (e.g., foundationalism and coherentism in philosophy, BFO and Cyc in artificial intelligence). Ontology (information science)_sentence_13

Applied ontology is considered a spiritual 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 fixed essences or whether enduring objects (e.g., perdurantism and endurantism) may be ontologically more primary than processes. Ontology (information science)_sentence_14

Every field uses ontological assumptions to frame explicit theories, research and applications. Ontology (information science)_sentence_15

For instance, the definition and ontology of economics is a primacy concern in Marxist economics, but also in other subfields of economics. Ontology (information science)_sentence_16

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 capital assets are at risk and by how much (see risk management). Ontology (information science)_sentence_17

Artificial intelligence has retained the most attention regarding applied ontology in subfields like natural language processing within 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. Ontology (information science)_sentence_18

History Ontology (information science)_section_2

Main article: Metaphysics § History Ontology (information science)_sentence_19

Main article: Artificial intelligence § History Ontology (information science)_sentence_20

Ontologies arise out of the branch of philosophy known as metaphysics, which deals with questions like "what exists?" Ontology (information science)_sentence_21

and "what is the nature of reality?". Ontology (information science)_sentence_22

One of five traditional branches of philosophy, metaphysics, is concerned with exploring existence through properties, entities and relations such as those between particulars and universals, intrinsic and extrinsic properties, or essence and existence. Ontology (information science)_sentence_23

Metaphysics has been an ongoing topic of discussion since recorded history. Ontology (information science)_sentence_24

Since the mid-1970s, researchers in the field of artificial intelligence (AI) have recognized that knowledge engineering is the key to building large and powerful AI systems. Ontology (information science)_sentence_25

AI researchers argued that they could create new ontologies as computational models that enable certain kinds of automated reasoning, which was only marginally successful. Ontology (information science)_sentence_26

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. Ontology (information science)_sentence_27

In particular, David Powers introduced the word ontology to AI to refer to real world or robotic grounding, 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. Ontology (information science)_sentence_28

Some researchers, drawing inspiration from philosophical ontologies, viewed computational ontology as a kind of applied philosophy. Ontology (information science)_sentence_29

In 1993, the widely cited web page and paper "Toward Principles for the Design of Ontologies Used for Knowledge Sharing" by Tom Gruber used ontology as a technical term in computer science closely related to earlier idea of semantic networks and taxonomies. Ontology (information science)_sentence_30

Gruber introduced the term as a specification of a conceptualization: Ontology (information science)_sentence_31

Attempting to distance ontologies from taxonomies and similar efforts in knowledge modeling that rely on classes and inheritance, Gruber stated (1993): Ontology (information science)_sentence_32

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." Ontology (information science)_sentence_33

Components Ontology (information science)_section_3

Main article: Ontology components Ontology (information science)_sentence_34

Contemporary ontologies share many structural similarities, regardless of the language in which they are expressed. Ontology (information science)_sentence_35

Most ontologies describe individuals (instances), classes (concepts), attributes and relations. Ontology (information science)_sentence_36

In this section each of these components is discussed in turn. Ontology (information science)_sentence_37

Common components of ontologies include: Ontology (information science)_sentence_38

Ontology (information science)_description_list_0

  • Individuals: Instances or objects (the basic or "ground level" objects)Ontology (information science)_item_0_0
  • Classes: Sets, collections, concepts, classes in programming, types of objects or kinds of thingsOntology (information science)_item_0_1
  • Attributes: Aspects, properties, features, characteristics or parameters that objects (and classes) can haveOntology (information science)_item_0_2
  • Relations: Ways in which classes and individuals can be related to one anotherOntology (information science)_item_0_3
  • Function terms: Complex structures formed from certain relations that can be used in place of an individual term in a statementOntology (information science)_item_0_4
  • Restrictions: Formally stated descriptions of what must be true in order for some assertion to be accepted as inputOntology (information science)_item_0_5
  • 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 formOntology (information science)_item_0_6
  • Axioms: Assertions (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 statementsOntology (information science)_item_0_7
  • Events: The changing of attributes or relationsOntology (information science)_item_0_8

Ontologies are commonly encoded using ontology languages. Ontology (information science)_sentence_39

Types Ontology (information science)_section_4

Domain ontology Ontology (information science)_section_5

A domain ontology (or domain-specific ontology) represents concepts which belong to a realm of the world, such as biology or politics. Ontology (information science)_sentence_40

Each domain ontology typically models domain-specific definitions of terms. Ontology (information science)_sentence_41

For example, the word has many different meanings. Ontology (information science)_sentence_42

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. Ontology (information science)_sentence_43

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. Ontology (information science)_sentence_44

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. Ontology (information science)_sentence_45

This presents a challenge to the ontology designer. Ontology (information science)_sentence_46

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.). Ontology (information science)_sentence_47

At present, merging ontologies that are not developed from a common upper ontology is a largely manual process and therefore time-consuming and expensive. Ontology (information science)_sentence_48

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. Ontology (information science)_sentence_49

There are studies on generalized techniques for merging ontologies, 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 OBO Foundry. Ontology (information science)_sentence_50

Upper ontology Ontology (information science)_section_6

Main article: Upper ontology Ontology (information science)_sentence_51

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. Ontology (information science)_sentence_52

It usually employs a core glossary that overarches the terms and associated object descriptions as they are used in various relevant domain ontologies. Ontology (information science)_sentence_53

Standardized upper ontologies available for use include BFO, BORO method, Dublin Core, GFO, Cyc, SUMO, UMBEL, the Unified Foundational Ontology (UFO), and DOLCE. Ontology (information science)_sentence_54

WordNet has been considered an upper ontology by some and has been used as a linguistic tool for learning domain ontologies. Ontology (information science)_sentence_55

Hybrid ontology Ontology (information science)_section_7

The Gellish ontology is an example of a combination of an upper and a domain ontology. Ontology (information science)_sentence_56

Visualization Ontology (information science)_section_8

A survey of ontology visualization methods is presented by Katifori et al. Ontology (information science)_sentence_57

An updated survey of ontology visualization methods and tools was published by Dudás et al. Ontology (information science)_sentence_58

The most established ontology visualization methods, namely indented tree and graph visualization are evaluated by Fu et al. Ontology (information science)_sentence_59

A visual language for ontologies represented in OWL is specified by the Visual Notation for OWL Ontologies (VOWL). Ontology (information science)_sentence_60

Engineering Ontology (information science)_section_9

Main article: Ontology engineering Ontology (information science)_sentence_61

Ontology engineering (also called ontology building) is a set of tasks related to the development of ontologies for a particular domain. Ontology (information science)_sentence_62

It is a subfield of 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. Ontology (information science)_sentence_63

Ontology engineering aims to make explicit the knowledge contained in software applications, and organizational procedures for a particular domain. Ontology (information science)_sentence_64

Ontology engineering offers a direction for overcoming semantic obstacles, such as those related to the definitions of business terms and software classes. Ontology (information science)_sentence_65

Known challenges with ontology engineering include: Ontology (information science)_sentence_66

Ontology (information science)_ordered_list_1

  1. Ensuring the ontology is current with domain knowledge and term useOntology (information science)_item_1_9
  2. Providing sufficient specificity and concept coverage for the domain of interest, thus minimizing the content completeness problemOntology (information science)_item_1_10
  3. Ensuring the ontology can support its use casesOntology (information science)_item_1_11

Editors Ontology (information science)_section_10

Ontology editors are applications designed to assist in the creation or manipulation of ontologies. Ontology (information science)_sentence_67

It is common for ontology editors to use one or more ontology languages. Ontology (information science)_sentence_68

Aspects of ontology editors include: visual navigation possibilities within the knowledge model, inference engines and 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. Ontology (information science)_sentence_69

Learning Ontology (information science)_section_11

Main article: Ontology learning Ontology (information science)_sentence_70

Ontology learning is the automatic or semi-automatic creation of ontologies, including extracting a domain's terms from natural language text. Ontology (information science)_sentence_71

As building ontologies manually is extremely labor-intensive and time-consuming, there is great motivation to automate the process. Ontology (information science)_sentence_72

Information extraction and text mining have been explored to automatically link ontologies to documents, for example in the context of the BioCreative challenges. Ontology (information science)_sentence_73

Languages Ontology (information science)_section_12

Main article: Ontology language Ontology (information science)_sentence_74

An ontology language is a formal language used to encode an ontology. Ontology (information science)_sentence_75

There are a number of such languages for ontologies, both proprietary and standards-based: Ontology (information science)_sentence_76

Ontology (information science)_unordered_list_2

  • 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.Ontology (information science)_item_2_12
  • Common logic is ISO standard 24707, a specification of a family of ontology languages that can be accurately translated into each other.Ontology (information science)_item_2_13
  • The Cyc project has its own ontology language called CycL, based on first-order predicate calculus with some higher-order extensions.Ontology (information science)_item_2_14
  • DOGMA (Developing Ontology-Grounded Methods and Applications) adopts the fact-oriented modeling approach to provide a higher level of semantic stability.Ontology (information science)_item_2_15
  • The Gellish language includes rules for its own extension and thus integrates an ontology with an ontology language.Ontology (information science)_item_2_16
  • IDEF5 is a software engineering method to develop and maintain usable, accurate, domain ontologies.Ontology (information science)_item_2_17
  • 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.Ontology (information science)_item_2_18
  • MOF and UML are standards of the OMGOntology (information science)_item_2_19
  • Olog is a category theoretic approach to ontologies, emphasizing translations between ontologies using functors.Ontology (information science)_item_2_20
  • OBO, a language used for biological and biomedical ontologies.Ontology (information science)_item_2_21
  • OntoUML is an ontologically well-founded profile of UML for conceptual modeling of domain ontologies.Ontology (information science)_item_2_22
  • 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.Ontology (information science)_item_2_23
  • Rule Interchange Format (RIF) and F-Logic combine ontologies and rules.Ontology (information science)_item_2_24
  • Semantic Application Design Language (SADL) captures a subset of the expressiveness of OWL, using an English-like language entered via an Eclipse Plug-in.Ontology (information science)_item_2_25
  • SBVR (Semantics of Business Vocabularies and Rules) is an OMG standard adopted in industry to build ontologies.Ontology (information science)_item_2_26
  • TOVE Project, TOronto Virtual Enterprise projectOntology (information science)_item_2_27

Published examples Ontology (information science)_section_13

Ontology (information science)_unordered_list_3

  • Arabic Ontology, a linguistic ontology for Arabic, which can be used as an Arabic Wordnet but with ontologically-clean content.Ontology (information science)_item_3_28
  • 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.Ontology (information science)_item_3_29
  • BabelNet, a very large multilingual semantic network and ontology, lexicalized in many languagesOntology (information science)_item_3_30
  • Basic Formal Ontology, a formal upper ontology designed to support scientific researchOntology (information science)_item_3_31
  • BioPAX, an ontology for the exchange and interoperability of biological pathway (cellular processes) dataOntology (information science)_item_3_32
  • BMO, an e-Business Model Ontology based on a review of enterprise ontologies and business model literatureOntology (information science)_item_3_33
  • SSBMO, 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).Ontology (information science)_item_3_34
  • 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)Ontology (information science)_item_3_35
  • CContology (Customer Complaint Ontology), an e-business ontology to support online customer complaint managementOntology (information science)_item_3_36
  • CIDOC Conceptual Reference Model, an ontology for cultural heritageOntology (information science)_item_3_37
  • 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.Ontology (information science)_item_3_38
  • Computer Science Ontology, an automatically generated ontology of research topics in the field of Computer ScienceOntology (information science)_item_3_39
  • Cyc, a large Foundation Ontology for formal representation of the universe of discourseOntology (information science)_item_3_40
  • Disease Ontology, designed to facilitate the mapping of diseases and associated conditions to particular medical codesOntology (information science)_item_3_41
  • DOLCE, a Descriptive Ontology for Linguistic and Cognitive EngineeringOntology (information science)_item_3_42
  • Drammar, ontology of dramaOntology (information science)_item_3_43
  • Dublin Core, a simple ontology for documents and publishingOntology (information science)_item_3_44
  • Financial Industry Business Ontology (FIBO), a business conceptual ontology for the financial industryOntology (information science)_item_3_45
  • Foundational, Core and Linguistic OntologiesOntology (information science)_item_3_46
  • Foundational Model of Anatomy, an ontology for human anatomyOntology (information science)_item_3_47
  • Friend of a Friend, an ontology for describing persons, their activities and their relations to other people and objectsOntology (information science)_item_3_48
  • Gene Ontology for genomicsOntology (information science)_item_3_49
  • 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.Ontology (information science)_item_3_50
  • 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 .Ontology (information science)_item_3_51
  • GAO (General Automotive Ontology) - an ontology for the automotive industry that includes 'car' extensionsOntology (information science)_item_3_52
  • GOLD, General Ontology for Linguistic DescriptionOntology (information science)_item_3_53
  • GUM (Generalized Upper Model), a linguistically motivated ontology for mediating between clients systems and natural language technologyOntology (information science)_item_3_54
  • IDEAS Group, a formal ontology for enterprise architecture being developed by the Australian, Canadian, UK and U.S. Defence Depts.Ontology (information science)_item_3_55
  • Linkbase, a formal representation of the biomedical domain, founded upon Basic Formal Ontology.Ontology (information science)_item_3_56
  • LPL, Landmark Pattern LanguageOntology (information science)_item_3_57
  • NCBO Bioportal, biological and biomedical ontologies and associated tools to search, browse and visualiseOntology (information science)_item_3_58
  • NIFSTD Ontologies from the Neuroscience Information Framework: a modular set of ontologies for the neuroscience domain.Ontology (information science)_item_3_59
  • OBO-Edit, an ontology browser for most of the Open Biological and Biomedical OntologiesOntology (information science)_item_3_60
  • OBO Foundry, a suite of interoperable reference ontologies in biology and biomedicineOntology (information science)_item_3_61
  • OMNIBUS Ontology, an ontology of learning, instruction, and instructional designOntology (information science)_item_3_62
  • Ontology for Biomedical Investigations, an open-access, integrated ontology of biological and clinical investigationsOntology (information science)_item_3_63
  • ONSTR, Ontology for Newborn Screening Follow-up and Translational Research, Newborn Screening Follow-up Data Integration Collaborative, Emory University, Atlanta.Ontology (information science)_item_3_64
  • Plant Ontology for plant structures and growth/development stages, etc.Ontology (information science)_item_3_65
  • POPE, Purdue Ontology for Pharmaceutical EngineeringOntology (information science)_item_3_66
  • PRO, the Protein Ontology of the Protein Information Resource, Georgetown UniversityOntology (information science)_item_3_67
  • ProbOnto, knowledge base and ontology of probability distributions.Ontology (information science)_item_3_68
  • Program abstraction taxonomyOntology (information science)_item_3_69
  • Protein Ontology for proteomicsOntology (information science)_item_3_70
  • RXNO Ontology, for name reactions in chemistryOntology (information science)_item_3_71
  • Sequence Ontology, for representing genomic feature types found on biological sequencesOntology (information science)_item_3_72
  • SNOMED CT (Systematized Nomenclature of Medicine—Clinical Terms)Ontology (information science)_item_3_73
  • Suggested Upper Merged Ontology, a formal upper ontologyOntology (information science)_item_3_74
  • Systems Biology Ontology (SBO), for computational models in biologyOntology (information science)_item_3_75
  • SWEET, Semantic Web for Earth and Environmental TerminologyOntology (information science)_item_3_76
  • ThoughtTreasure ontologyOntology (information science)_item_3_77
  • TIME-ITEM, Topics for Indexing Medical EducationOntology (information science)_item_3_78
  • Uberon, representing animal anatomical structuresOntology (information science)_item_3_79
  • UMBEL, a lightweight reference structure of 20,000 subject concept classes and their relationships derived from OpenCycOntology (information science)_item_3_80
  • WordNet, a lexical reference systemOntology (information science)_item_3_81
  • YAMATO, Yet Another More Advanced Top-level OntologyOntology (information science)_item_3_82

The W3C Linking Open Data community project coordinates attempts to converge different ontologies into worldwide Semantic Web. Ontology (information science)_sentence_77

Libraries Ontology (information science)_section_14

The development of ontologies has led to the emergence of services providing lists or directories of ontologies called ontology libraries. Ontology (information science)_sentence_78

The following are libraries of human-selected ontologies. Ontology (information science)_sentence_79

Ontology (information science)_unordered_list_4

  • COLORE is an open repository of first-order ontologies in Common Logic with formal links between ontologies in the repository.Ontology (information science)_item_4_83
  • DAML Ontology Library maintains a legacy of ontologies in DAML.Ontology (information science)_item_4_84
  • Ontology Design Patterns portal is a wiki repository of reusable components and practices for ontology design, and also maintains a list of exemplary ontologies.Ontology (information science)_item_4_85
  • Protégé Ontology Library contains a set of OWL, Frame-based and other format ontologies.Ontology (information science)_item_4_86
  • SchemaWeb is a directory of RDF schemata expressed in RDFS, OWL and DAML+OIL.Ontology (information science)_item_4_87

The following are both directories and search engines. Ontology (information science)_sentence_80

Ontology (information science)_unordered_list_5

  • OBO Foundry is a suite of interoperable reference ontologies in biology and biomedicine.Ontology (information science)_item_5_88
  • Bioportal (ontology repository of NCBO)Ontology (information science)_item_5_89
  • OntoSelect Ontology Library offers similar services for RDF/S, DAML and OWL ontologies.Ontology (information science)_item_5_90
  • 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).Ontology (information science)_item_5_91
  • Swoogle is a directory and search engine for all RDF resources available on the Web, including ontologies.Ontology (information science)_item_5_92
  • Open Ontology Repository initiativeOntology (information science)_item_5_93
  • ROMULUS is a foundational ontology repository aimed at improving semantic interoperability. Currently there are three foundational ontologies in the repository: DOLCE, BFO and GFO.Ontology (information science)_item_5_94

Examples of applications Ontology (information science)_section_15

In general, ontologies can be used beneficially in several fields. Ontology (information science)_sentence_81

Ontology (information science)_unordered_list_6

  • 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.Ontology (information science)_item_6_95
  • Geographic information systems bring together data from different sources and benefit therefore from ontological metadata which helps to connect the semantics of the data.Ontology (information science)_item_6_96
  • 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. 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.Ontology (information science)_item_6_97

See also Ontology (information science)_section_16

Ontology (information science)_description_list_7

Ontology (information science)_unordered_list_8


Credits to the contents of this page go to the authors of the corresponding Wikipedia page: en.wikipedia.org/wiki/Ontology (information science).