Editing Ontology (information science) (section)

== 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 [[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.<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|bibcode=2001IJGIS..15..667F |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 book|pmc=4300097|pmid=15759615|doi=10.1142/9789812704856_0016|isbn=978-981-238-598-7 |chapter=Biomedical Ontologies |title=Biocomputing 2004 |date=2003 |last1=Bodenreider |first1=O. |last2=Mitchell |first2=J. A. |last3=McCray |first3=A. T. |journal=<!-- --> |pages=164–165 }}</ref>