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

BMC Bioinformatics

Software

Pablo Fernicola¹  Alex Wade¹  Savas Parastatidis¹  Oscar Naim¹  Gregory B Quinn²  Rahul Chandran³  J Lynn Fink³  Philip E Bourne³ 

[1] External Research, MS 99/4618, Microsoft Corporation, 1 Microsoft Way, 98052, Redmond, WA, USA;San Diego Supercomputer Center, 10100 Hopkins Dr, 92093-0743, San Diego, CA, USA;Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, 92093-0444, San Diego, CA, USA;

关键词: Protein Data Bank;    Ontology Term;    Hairy Cell Leukemia;    Semantic Data;    Family Health History;   

DOI  :  10.1186/1471-2105-11-103

 received in 2009-12-16, accepted in 2010-02-24,  发布年份 2010

来源: Springer

【 摘 要 】

BackgroundIn 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.ResultsThe 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.ConclusionsThe 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.

【 授权许可】

CC BY   
© Fink et al; licensee BioMed Central Ltd. 2010