Advancing translational research with the Semantic Web.
Advancing translational research with the Semantic Web.
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DOI：
10.1186/1471-2105-8-s3-s2
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发表时间：
2007-05-09
影响因子：
3
通讯作者：
Cheung KH
中科院分区：
文献类型：
--
作者：
Ruttenberg A;Clark T;Bug W;Samwald M;Bodenreider O;Chen H;Doherty D;Forsberg K;Gao Y;Kashyap V;Kinoshita J;Luciano J;Marshall MS;Ogbuji C;Rees J;Stephens S;Wong GT;Wu E;Zaccagnini D;Hongsermeier T;Neumann E;Herman I;Cheung KH
美国国立卫生研究院（NIH）“路线图”的一个基本目标是加强转化研究，将基础研究的发现转化为临床应用。转化研究的一个重要障碍是缺乏跨相关生物医学领域的统一结构化数据。语义网是当前网络的扩展，它通过自动过程实现对数字资源的导航和有意义的使用。它基于支持聚合和集成来自不同来源的数据的通用格式。在此基础上建立了各种各样的技术，它们共同支持对广泛的生物医学数据进行识别、表示和推理。语义网医疗保健和生命科学兴趣小组（HCLSIG）在万维网联盟框架内成立，旨在探索这些技术在各个领域的应用。子小组的重点是使生物医学数据在RDF中可用，与生物医学本体合作，建立临床决策支持系统原型，致力于药物安全性和有效性交流，以及支持疾病研究人员导航和注释大量潜在相关文献。我们提出了一个场景，显示了语义网可以支持的信息环境的价值，以帮助神经科学研究人员。然后，我们报告了HCLSIG成员的几个项目，在这个过程中说明了语义网技术在生物医学领域的应用范围。语义Web技术既有希望也有挑战。当前的工具和标准已经足以实现从工作台到病床的愿景。另一方面，这些技术还很年轻。标准和实现方面的差距仍然存在，并且早期技术的典型问题限制了采用，例如需要大量的从业人员和安装基础，以及随着技术的扩展而增长的烦恼。尽管如此，在万维网的规模上，生物医学的互操作知识来源的潜力值得继续努力。
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. 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. 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.