Advancing translational research with the Semantic Web.
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.


CONCLUSIONS
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.
Ruttenberg
Alan
A
Millennium Pharmaceuticals, Cambridge, MA, USA. alanruttenberg@gmail.com <alanruttenberg@gmail.com>
Clark
Tim
T
Bug
William
W
Samwald
Matthias
M
Bodenreider
Olivier
O
Chen
Helen
H
Doherty
Donald
D
Forsberg
Kerstin
K
Gao
Yong
Y
Kashyap
Vipul
V
Kinoshita
June
J
Luciano
Joanne
J
Marshall
M Scott
MS
Ogbuji
Chimezie
C
Rees
Jonathan
J
Stephens
Susie
S
Wong
Gwendolyn T
GT
Wu
Elizabeth
E
Zaccagnini
Davide
D
Hongsermeier
Tonya
T
Neumann
Eric
E
Herman
Ivan
I
Cheung
Kei-Hoi
KH
D035843:Biomedical Research / Q000379:methods* / Q000458:organization & administration; D016208:Databases, Factual; D004282:Documentation / Q000379:methods; D033181:Information Dissemination / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D038622:Internationality; D020407:Internet; D009323:Natural Language Processing; D009488:Neurosciences / Q000379:methods* / Q000458:organization & administration; D012106:Research / Q000458:organization & administration; D012107:Research Design; D012660:Semantics