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应对健康科学数据的信息过载:图书馆的结构化利用、数据库中的分布式知识与网络内容

Dealing with an information overload of health science data: structured utilisation of libraries, distributed knowledge in databases and Web content.

作者信息

Hoelzer Simon, Schweiger Ralf K, Rieger Joerg, Meyer Michael

机构信息

Institute of Medical Informatics, Justus-Liebig-University of Giessen, Germany.

出版信息

Stud Health Technol Inform. 2006;124:549-54.

Abstract

The organizational structures of web contents and electronic information resources must adapt to the demands of a growing volume of information and user requirements. Otherwise the information society will be threatened by disinformation. The biomedical sciences are especially vulnerable in this regard, since they are strongly oriented toward text-based knowledge sources. Here sustainable improvement can only be achieved by using a comprehensive, integrated approach that not only includes data management but also specifically incorporates the editorial processes, including structuring information sources and publication. The technical resources needed to effectively master these tasks are already available in the form of the data standards and tools of the Semantic Web. They include Rich Site Summaries (RSS), which have become an established means of distributing and syndicating conventional news messages and blogs. They can also provide access to the contents of the previously mentioned information sources, which are conventionally classified as 'deep web' content.

摘要

网络内容和电子信息资源的组织结构必须适应信息量不断增长的需求以及用户的要求。否则,信息社会将受到虚假信息的威胁。生物医学科学在这方面尤其脆弱,因为它们高度依赖基于文本的知识来源。在这里,只有通过采用全面、综合的方法才能实现可持续的改进,这种方法不仅包括数据管理,还特别纳入编辑流程,包括构建信息源和出版。有效完成这些任务所需的技术资源已经以语义网的数据标准和工具的形式存在。它们包括丰富站点摘要(RSS),这已成为分发和联合传统新闻消息和博客的既定手段。它们还可以提供对上述信息源内容的访问,这些内容通常被归类为“深网”内容。

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