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Draft:Outline of ontologies

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The following outline is provided as an overview of and topical guide to ontologies:

In information science, an ontology encompasses a representation, formal naming, and definitions of the categories, properties, and relations between the concepts, data, or entities that pertain to one, many, or all 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 terms and relational expressions that represent the entities in that subject area. The field which studies ontologies so conceived is sometimes referred to as applied ontology.

Every academic discipline or field, in creating its terminology, thereby lays the groundwork for an ontology. Each uses ontological assumptions to frame explicit theories, research and applications. Improved ontologies may improve problem solving within that domain, interoperability of data systems, and discoverability of data. 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. For instance, the definition and ontology of economics is a primary concern in Marxist economics, but also in other subfields of economics. 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).

What type of thing is an ontology?

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Ontologies can be described as all of the following:

  • A type of tool of knowledge representation and reasoning (KR) – KR is a field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can utilize to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language. Examples of knowledge representation formalisms include semantic nets, frames, rules, and ontologies.

Types of ontologies

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Ontology engineering

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Ontology engineering – building ontologies, and the field that studies the methods and methodologies for building ontologies.

Ontology design and modeling

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Ontology components

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Ontology components

  • Individuals – instances or objects (the basic or "ground level" objects)
  • Classes – sets, collections, concepts, types of objects, or kinds of things.[1]
  • Attributes – aspects, properties, features, characteristics, or parameters that objects (and classes) can have
  • Relations – ways in which classes and individuals can be related to one another
  • Function terms – complex structures formed from certain relations that can be used in place of an individual term in a statement
  • Restrictions – formally stated descriptions of what must be true in order for some assertion to be accepted as input
  • Rules – statements in the form of an if-then (antecedent-consequent) sentence that describe the logical inferences that can be drawn from an assertion in a particular form
  • Axioms – assertions (including rules) in a logical form 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 these disciplines, axioms include only statements asserted as a priori knowledge. As used here, "axioms" also include the theory derived from axiomatic statements.
  • Events – the changing of attributes or relations
  • Ontology notation – ontologies are commonly encoded using ontology languages.

Ontology methods

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Ontology tools

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Ontology languages

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Ontology language – formal language used to construct ontologies, that allows the encoding of knowledge about specific domains. An ontology language may include reasoning rules that support the processing of that knowledge.

Applications of ontologies

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Applied ontology

Linguistics applications

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Reasoning applications

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Search applications

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Examples of ontologies

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Examples of biological and biomedical ontologies

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  • Gene Ontology for genomics
  • BioPAX[10] – ontology for the exchange and interoperability of biological pathway (cellular processes) data
  • CCO and GexKB[11] – Application Ontologies (APO) that integrate diverse types of knowledge with the Cell Cycle Ontology (CCO) and the Gene Expression Knowledge Base (GexKB)
  • Disease Ontology[12] – ontology designed to facilitate the mapping of diseases and associated conditions to particular medical codes. It was originally developed at Northwestern University and is associated with the Open Biomedical Ontologies Foundry.
  • Foundational Model of Anatomy[13] – reference ontology for the domain of anatomy. It is a symbolic representation of the canonical, phenotypic structure of an organism; a spatial-structural ontology of anatomical entities and relations which form the physical organization of an organism at all salient levels of granularity.
  • NCBO Bioportal,[14] 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. See http://neuinfo.org
  • OBO-Edit,[15] an ontology browser for most of the Open Biological and Biomedical Ontologies
  • OBO Foundry,[16] a suite of interoperable reference ontologies in biology and biomedicine
  • ONSTR,[17] Ontology for Newborn Screening Follow-up and Translational Research , Newborn Screening Follow-up Data Integration Collaborative, Emory University, Atlanta, GA. See also https://nbsdc.org/projectmission.php
  • Plant Ontology[18] for plant structures and growth/development stages, etc.
  • POPE, Purdue Ontology for Pharmaceutical Engineering
  • SNOMED CT (Systematized Nomenclature of Medicine -- Clinical Terms)
  • Systems Biology Ontology (SBO) – for computational models in biology
  • SWEET[19] – Semantic Web for Earth and Environmental Terminology
  • TIME-ITEM (Topics for Indexing Medical Education) –
  • Uberon[20] – representing animal anatomical structures

Examples of upper ontologies

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Upper ontology – ontology which describes very general concepts that are the same across all knowledge domains. Examples of upper ontologies include:

  • Basic Formal Ontology,[21] a formal upper ontology designed to support scientific research
  • COSMO,[22] 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.
  • DOLCE, a Descriptive Ontology for Linguistic and Cognitive Engineering
  • GOLD,[23] General Ontology for Linguistic Description
  • GUM (Generalized Upper Model),[24] a linguistically motivated ontology for mediating between clients systems and natural language technology
  • Suggested Upper Merged Ontology (SUMO) – formal upper ontology
  • YAMATO,[25] Yet Another More Advanced Top-level Ontology

History of ontologies

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History of ontologies

Ontology organizations

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Ontology publications

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Persons influential in ontologies

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  • Adam Pease – American computer scientist doing research in ontology and formal reasoning. He is best known as the Technical Editor of the Suggested Upper Merged Ontology (SUMO) upper ontology intended as a foundation ontology for a variety of computer information processing systems.

See also

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References

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  1. ↑ See Class (set theory), Class (computer science), and Class (philosophy), each of which is relevant but not identical to the notion of a "class" here.
  2. ↑ Osterwalder, Alexander; Pigneur, Yves (June 17–19, 2002). "An e-Business Model Ontology for Modeling e-Business" (PDF). 15th Bled eConference, Slovenia. {{cite journal}}: Cite journal requires |journal= (help)CS1 maint: location (link)
  3. ↑ "CContology". Retrieved 10 February 2011.
  4. ↑ "The CIDOC Conceptual Reference Model (CRM)". Retrieved 10 February 2011.
  5. ↑ "Foundational, Core and Linguistic Ontologies". Retrieved 10 February 2011.
  6. ↑ "The IDEAS Group Website". Retrieved 10 February 2011.
  7. ↑ "OMNIBUS Ontology". Retrieved 10 February 2011.
  8. ↑ "PRO". Retrieved 10 February 2011.
  9. ↑ "Protein Ontology". Retrieved 10 February 2011.
  10. ↑ "BioPAX". Retrieved 10 February 2011.
  11. ↑ "About CCO and GexKB". Semantic Systems Biology.
  12. ↑ "Disease Ontology". Sourceforge. Retrieved 10 February 2011.
  13. ↑ "Foundational Model of Anatomy". Retrieved 10 February 2011.
  14. ↑ "Bioportal". National Center for Biological Ontology (NCBO).
  15. ↑ "Ontology browser for most of the Open Biological and Biomedical Ontologies". Berkeley Bioinformatics Open Source Project (BBOP).
  16. ↑ "The Open Biological and Biomedical Ontologies". Berkeley Bioinformatics Open Source Project (BBOP).
  17. ↑ "ONSTR". Retrieved 16 April 2014.
  18. ↑ "Plant Ontology". Retrieved 10 February 2011.
  19. ↑ "Semantic Web for Earth and Environmental Terminology (SWEET)" (PDF). Retrieved 14 April 2026.
  20. ↑ "UBERON". Retrieved 10 July 2012.
  21. ↑ "Basic Formal Ontology (BFO)". Institute for Formal Ontology and Medical Information Science (IFOMIS).
  22. ↑ "COSMO". MICRA Inc. Retrieved 10 February 2011.
  23. ↑ "GOLD". Retrieved 10 February 2011.
  24. ↑ "Generalized Upper Model". Retrieved 10 February 2011.
  25. ↑ "YAMATO". Retrieved 10 February 2011.

Further reading

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