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Ontology Based Document Enrichment in Bioinformatics
Controlled vocabularies are common within bioinformatics resources. They can be used to give a summary of the knowledge held about a particular entity. They are also used to constrain values given for particular attributes of an entity. This helps create a shared understanding of a domain and aids i...
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Formato: | Texto |
Lenguaje: | English |
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Hindawi Publishing Corporation
2002
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447236/ https://www.ncbi.nlm.nih.gov/pubmed/18628876 http://dx.doi.org/10.1002/cfg.141 |
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author | Stevens, Robert |
author_facet | Stevens, Robert |
author_sort | Stevens, Robert |
collection | PubMed |
description | Controlled vocabularies are common within bioinformatics resources. They can be used to give a summary of the knowledge held about a particular entity. They are also used to constrain values given for particular attributes of an entity. This helps create a shared understanding of a domain and aids increased precision and recall during querying of resources. Ontologies can also provide such facilities, but can also enhance their utility. Controlled vocabularies are often simply lists of words, but may be viewed as a kind of ontology. Ideally ontologies are structurally enriched with relationships between terms within the vocabulary. Use of such rich forms of vocabularies in database annotation could enhance those resources usability by both humans and computers. The representation of the knowledge content of biological resources in a computationally accessible form opens the prospect of greater support for a biologist investigating new data. |
format | Text |
id | pubmed-2447236 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2002 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-24472362008-07-14 Ontology Based Document Enrichment in Bioinformatics Stevens, Robert Comp Funct Genomics Research Article Controlled vocabularies are common within bioinformatics resources. They can be used to give a summary of the knowledge held about a particular entity. They are also used to constrain values given for particular attributes of an entity. This helps create a shared understanding of a domain and aids increased precision and recall during querying of resources. Ontologies can also provide such facilities, but can also enhance their utility. Controlled vocabularies are often simply lists of words, but may be viewed as a kind of ontology. Ideally ontologies are structurally enriched with relationships between terms within the vocabulary. Use of such rich forms of vocabularies in database annotation could enhance those resources usability by both humans and computers. The representation of the knowledge content of biological resources in a computationally accessible form opens the prospect of greater support for a biologist investigating new data. Hindawi Publishing Corporation 2002-02 /pmc/articles/PMC2447236/ /pubmed/18628876 http://dx.doi.org/10.1002/cfg.141 Text en Copyright © 2002 Hindawi Publishing Corporation. http://creativecommons.org/licenses/by/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Stevens, Robert Ontology Based Document Enrichment in Bioinformatics |
title | Ontology Based Document Enrichment in Bioinformatics |
title_full | Ontology Based Document Enrichment in Bioinformatics |
title_fullStr | Ontology Based Document Enrichment in Bioinformatics |
title_full_unstemmed | Ontology Based Document Enrichment in Bioinformatics |
title_short | Ontology Based Document Enrichment in Bioinformatics |
title_sort | ontology based document enrichment in bioinformatics |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447236/ https://www.ncbi.nlm.nih.gov/pubmed/18628876 http://dx.doi.org/10.1002/cfg.141 |
work_keys_str_mv | AT stevensrobert ontologybaseddocumentenrichmentinbioinformatics |