Structured digital tables on the Semantic Web: toward a structured digital literature

In parallel to the growth in bioscience databases, biomedical publications have increased exponentially in the past decade. However, the extraction of high‐quality information from the corpus of scientific literature has been hampered by the lack of machine‐interpretable content, despite text‐mining...

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Bibliographic Details
Published inMolecular systems biology Vol. 6; no. 1; pp. 403 - n/a
Main Authors Gerstein, Mark B, Samwald, Matthias, Auerbach, Raymond K, Cheung, Kei-Hoi
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 24.08.2010
John Wiley & Sons, Ltd
EMBO Press
Nature Publishing Group
Springer Nature
Subjects
bioinformatics
data integration
Database Management Systems
Digitization
EMBO10
Hierarchies
Internet
Kinases
Mass spectrometry
Ontology
Peer Review, Research
Perspective
Protein Structure, Tertiary
Proteins
Publishing
Researchers
Resource Description Framework-RDF
Saccharomyces cerevisiae - metabolism
Scientific imaging
semantic publishing
Semantic Web
Semantics
Tables
triplification
Web Ontology Language-OWL
semantic publishing
Semantic Web
triplification
data integration
bioinformatics
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Summary:In parallel to the growth in bioscience databases, biomedical publications have increased exponentially in the past decade. However, the extraction of high‐quality information from the corpus of scientific literature has been hampered by the lack of machine‐interpretable content, despite text‐mining advances. To address this, we propose creating a structured digital table as part of an overall effort in developing machine‐readable, structured digital literature. In particular, we envision transforming publication tables into standardized triples using Semantic Web approaches. We identify three canonical types of tables (conveying information about properties, networks, and concept hierarchies) and show how more complex tables can be built from these basic types. We envision that authors would create tables initially using the structured triples for canonical types and then have them visually rendered for publication, and we present examples for converting representative tables into triples. Finally, we discuss how ‘stub’ versions of structured digital tables could be a useful bridge for connecting together the literature with databases, allowing the former to more precisely document the later.
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ISSN:1744-4292
1744-4292
DOI:10.1038/msb.2010.45