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Open Access Highly Accessed Software

Word add-in for ontology recognition: semantic enrichment of scientific literature

J Lynn Fink1*, Pablo Fernicola2, Rahul Chandran1, Savas Parastatidis2, Alex Wade2, Oscar Naim2, Gregory B Quinn3 and Philip E Bourne1

Author affiliations

1 Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, CA, 92093-0444 USA

2 External Research, MS 99/4618, Microsoft Corporation, 1 Microsoft Way, Redmond, WA, 98052 USA

3 San Diego Supercomputer Center, 10100 Hopkins Dr., San Diego, CA, 92093-0743 USA

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Citation and License

BMC Bioinformatics 2010, 11:103  doi:10.1186/1471-2105-11-103

Published: 24 February 2010

Abstract

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 webcite.

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.