The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2105/8/S3/S2
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Subject: Advancing Translational Research with the Semantic Web
Resource: BMC Bioinformatics: Open Access

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Alan Ruttenberg¹ , Tim Clark² , William Bug³ , Matthias Samwald⁴ , Olivier Bodenreider⁵ , Helen Chen⁶ , Donald Doherty⁷ , Kerstin Forsberg⁸ , Yong Gao⁹ , Vipul Kashyap¹⁰ , June Kinoshita¹¹ , Joanne Luciano¹² , M Scott Marshall¹³ , Chimezie Ogbuji¹⁴ , Jonathan Rees¹⁵ , Susie Stephens¹⁶ , Gwendolyn T Wong¹¹ , Elizabeth Wu¹¹ , Davide Zaccagnini¹⁷ , Tonya Hongsermeier¹⁰ , Eric Neumann¹⁸ , Ivan Herman¹⁹ and Kei-Hoi Cheung²⁰

¹Millennium Pharmaceuticals, Cambridge, MA, USA

²Initiative in Innovative Computing, Harvard University, Cambridge, MA, USA

³Laboratory for Bioimaging and Anatomical Informatics, Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, PA, USA

⁴Section on Medical Expert and Knowledge-Based Systems, Medical University of Vienna, Vienna, Austria

⁵National Library of Medicine, Bethesda, MD, USA

⁶Agfa Healthcare, Waterloo, Ontario, Canada

⁷Brainstage Research, Pittsburgh, PA, USA

⁸AstraZeneca, Mölndal, Sweden

⁹MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Charlestown, MA, USA

¹⁰Partners HealthCare System, Wellesley, MA, USA

¹¹Alzheimer Research Forum, Boston, MA, USA

¹²Harvard Medical School, Boston, MA, USA

¹³Integrative Bioinformatics Unit, University of Amsterdam, Amsterdam, The Netherlands

¹⁴Cleveland Clinic Foundation, Cleveland, OH, USA

¹⁵Science Commons, Cambridge, MA, USA

¹⁶Oracle, Burlington, MA, USA

¹⁷Language & Computing, Reston, VA, USA

¹⁸Teranode Corporation, Seattle, WA, USA

¹⁹World Wide Web Consortium (W3C)

²⁰Center for Medical Informatics, Yale University School of Medicine, New Haven, CT, USA

author email corresponding author email

BMC Bioinformatics 2007, 8(Suppl 3):S2doi:10.1186/1471-2105-8-S3-S2

Abstract

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.