Advancing translational research with the Semantic Web.

Advancing translational research with the Semantic Web. Research Abstract Details 

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Advancing translational research with the Semantic Web. Abstract Text:

Alan Ruttenberg,Tim Clark,William Bug,Matthias Samwald,Olivier Bodenreider,Helen Chen,Donald Doherty,Kerstin Forsberg,Yong Gao,Vipul Kashyap,June Kinoshita,Joanne Luciano,M Scott Marshall,Chimezie Ogbuji,Jonathan Rees,Susie Stephens,Gwendolyn T Wong,Elizabeth Wu,Davide Zaccagnini,Tonya Hongsermeier,Eric Neumann,Ivan Herman,Kei-Hoi Cheung,

BACKGROUND: A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature. RESULTS: We present a scenario that shows the value of the information environment the Semantic Web can support for aiding neuroscience researchers. We then report on several projects by members of the HCLSIG, in the process illustrating the range of Semantic Web technologies that have applications in areas of biomedicine. CONCLUSION: Semantic Web technologies present both promise and challenges. Current tools and standards are already adequate to implement components of the bench-to-bedside vision. On the other hand, these technologies are young. Gaps in standards and implementations still exist and adoption is limited by typical problems with early technology, such as the need for a critical mass of practitioners and installed base, and growing pains as the technology is scaled up. Still, the potential of interoperable knowledge sources for biomedicine, at the scale of the World Wide Web, merits continued work.

Advancing translational research with the Semantic Web. Publishing Authors By Initials

A Ruttenberg,T Clark,W Bug,M Samwald,O Bodenreider,H Chen,D Doherty,K Forsberg,Y Gao,V Kashyap,J Kinoshita,J Luciano,MS Marshall,C Ogbuji,J Rees,S Stephens,GT Wong,E Wu,D Zaccagnini,T Hongsermeier,E Neumann,I Herman,KH Cheung,

For similar linguistics: semantics research abstracts see: linguistics: semantics research

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Advancing translational research with the Semantic Web. Journal Published:

PUBLICATION TYPE: Review

Journal: BMC bioinformatics

VOLUME: 8 Suppl 3

Page Numbers: S2

Journal Abbreviation: BMC Bioinformatics

ISSN: 1471-2105

DAY: 9

MONTH: 05

YEAR: 2007

Advancing translational research with the Semantic Web. Information

Number of References: 101

LANGUAGE: eng

NlmUniqueID: 100965194

Advancing translational research with the Semantic Web. Keywords Mesh Terms:

KEYWORDS: Semantics

MESH TERMS: organization & administration

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Grant and Affiliation Information for Advancing translational research with the Semantic Web.

AFFILIATION: Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>

Country: England

AGENCY: United States NCRR

GRANT: RR043050-S2

ACRONYM: RR

MEDLINETA: BMC Bioinformatics

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