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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...

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Detalles Bibliográficos
Autores principales: Fink, J Lynn, Fernicola, Pablo, Chandran, Rahul, Parastatidis, Savas, Wade, Alex, Naim, Oscar, Quinn, Gregory B, Bourne, Philip E
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
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.
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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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