Word add-in for ontology recognition: semantic enrichment of scientific literature
Identifieur interne : 000858 ( Main/Exploration ); précédent : 000857; suivant : 000859Word add-in for ontology recognition: semantic enrichment of scientific literature
Auteurs : J Lynn Fink [États-Unis] ; Pablo Fernicola [États-Unis] ; Rahul Chandran [États-Unis] ; Savas Parastatidis [États-Unis] ; Alex Wade [États-Unis] ; Oscar Naim [États-Unis] ; Gregory B. Quinn [États-Unis] ; Philip E. Bourne [États-Unis]Source :
- BMC Bioinformatics [ 1471-2105 ] ; 2010.
English descriptors
- KwdEn :
- MESH :
Abstract
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.
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
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.
Url:
DOI: 10.1186/1471-2105-11-103
PubMed: 20181245
PubMed Central: 2837026
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream Pmc, to step Corpus: 000276
- to stream Pmc, to step Curation: 000276
- to stream Pmc, to step Checkpoint: 000538
- to stream PubMed, to step Corpus: 000065
- to stream PubMed, to step Curation: 000065
- to stream PubMed, to step Checkpoint: 000065
- to stream Ncbi, to step Merge: 000123
- to stream Ncbi, to step Curation: 000123
- to stream Ncbi, to step Checkpoint: 000123
- to stream Main, to step Merge: 000860
- to stream Main, to step Curation: 000858
Le document en format XML
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<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p>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.</p>
</sec>
<sec><title>Results</title>
<p>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 <ext-link ext-link-type="uri" xlink:href="http://www.codeplex.com/UCSDBioLit">http://www.codeplex.com/UCSDBioLit</ext-link>
.</p>
</sec>
<sec><title>Conclusions</title>
<p>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.</p>
</sec>
</div>
</front>
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</TEI>
<affiliations><list><country><li>États-Unis</li>
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<region><li>Californie</li>
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