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Word add-in for ontology recognition: semantic enrichment of scientific literature
BACKGROUND: In the current era of scientific research, efficient communication of information is paramount. As such, the nature of scholarly and scientific communication is changing; cyberinfrastructure is now absolutely necessary and new media are allowing information and knowledge to be more inter...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2837026/ https://www.ncbi.nlm.nih.gov/pubmed/20181245 http://dx.doi.org/10.1186/1471-2105-11-103 |
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author | Fink, J Lynn Fernicola, Pablo Chandran, Rahul Parastatidis, Savas Wade, Alex Naim, Oscar Quinn, Gregory B Bourne, Philip E |
author_facet | Fink, J Lynn Fernicola, Pablo Chandran, Rahul Parastatidis, Savas Wade, Alex Naim, Oscar Quinn, Gregory B Bourne, Philip E |
author_sort | Fink, J Lynn |
collection | PubMed |
description | BACKGROUND: In the current era of scientific research, efficient communication of information is paramount. As such, the nature of scholarly and scientific communication is changing; cyberinfrastructure is now absolutely necessary and new media are allowing information and knowledge to be more interactive and immediate. One approach to making knowledge more accessible is the addition of machine-readable semantic data to scholarly articles. RESULTS: The Word add-in presented here will assist authors in this effort by automatically recognizing and highlighting words or phrases that are likely information-rich, allowing authors to associate semantic data with those words or phrases, and to embed that data in the document as XML. The add-in and source code are publicly available at http://www.codeplex.com/UCSDBioLit. CONCLUSIONS: The Word add-in for ontology term recognition makes it possible for an author to add semantic data to a document as it is being written and it encodes these data using XML tags that are effectively a standard in life sciences literature. Allowing authors to mark-up their own work will help increase the amount and quality of machine-readable literature metadata. |
format | Text |
id | pubmed-2837026 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-28370262010-03-12 Word add-in for ontology recognition: semantic enrichment of scientific literature Fink, J Lynn Fernicola, Pablo Chandran, Rahul Parastatidis, Savas Wade, Alex Naim, Oscar Quinn, Gregory B Bourne, Philip E BMC Bioinformatics Software BACKGROUND: In the current era of scientific research, efficient communication of information is paramount. As such, the nature of scholarly and scientific communication is changing; cyberinfrastructure is now absolutely necessary and new media are allowing information and knowledge to be more interactive and immediate. One approach to making knowledge more accessible is the addition of machine-readable semantic data to scholarly articles. RESULTS: The Word add-in presented here will assist authors in this effort by automatically recognizing and highlighting words or phrases that are likely information-rich, allowing authors to associate semantic data with those words or phrases, and to embed that data in the document as XML. The add-in and source code are publicly available at http://www.codeplex.com/UCSDBioLit. CONCLUSIONS: The Word add-in for ontology term recognition makes it possible for an author to add semantic data to a document as it is being written and it encodes these data using XML tags that are effectively a standard in life sciences literature. Allowing authors to mark-up their own work will help increase the amount and quality of machine-readable literature metadata. BioMed Central 2010-02-24 /pmc/articles/PMC2837026/ /pubmed/20181245 http://dx.doi.org/10.1186/1471-2105-11-103 Text en Copyright ©2010 Fink et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Fink, J Lynn Fernicola, Pablo Chandran, Rahul Parastatidis, Savas Wade, Alex Naim, Oscar Quinn, Gregory B Bourne, Philip E Word add-in for ontology recognition: semantic enrichment of scientific literature |
title | Word add-in for ontology recognition: semantic enrichment of scientific literature |
title_full | Word add-in for ontology recognition: semantic enrichment of scientific literature |
title_fullStr | Word add-in for ontology recognition: semantic enrichment of scientific literature |
title_full_unstemmed | Word add-in for ontology recognition: semantic enrichment of scientific literature |
title_short | Word add-in for ontology recognition: semantic enrichment of scientific literature |
title_sort | word add-in for ontology recognition: semantic enrichment of scientific literature |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2837026/ https://www.ncbi.nlm.nih.gov/pubmed/20181245 http://dx.doi.org/10.1186/1471-2105-11-103 |
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