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Publishing perishing? Towards tomorrows information architecture

机译:出版灭亡?迈向明天的信息架构

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摘要

Scientific articles are tailored to present information in human-readable aliquots. Although the Internet has revolutionized the way our society thinks about information, the traditional text-based framework of the scientific article remains largely unchanged. This format imposes sharp constraints upon the type and quantity of biological information published today. Academic journals alone cannot capture the findings of modern genome-scale inquiry.Like many other disciplines, molecular biology is a science of facts: information inherently suited to database storage. In the past decade, a proliferation of public and private databases has emerged to house genome sequence, protein structure information, functional genomics data and more; these digital repositories are now a vital component of scientific communication. The next challenge is to integrate this vast and ever-growing body of information with academic journals and other media. To truly integrate scientific information we must modernize academic publishing to exploit the power of the Internet. This means more than online access to articles, hyperlinked references and web-based supplemental data; it means making articles fully computer-readable with intelligent markup and Structured Digital Abstracts.Here, we examine the changing roles of scholarly journals and databases. We present our vision of the optimal information architecture for the biosciences, and close with tangible steps to improve our handling of scientific information today while paving the way for an expansive central index in the future.
机译:专门设计了科学文章,以人类可读的等分形式呈现信息。尽管互联网彻底改变了我们社会对信息的思考方式,但传统的基于文本的科学文章框架在很大程度上保持不变。这种格式对当今出版的生物信息的类型和数量施加了严格的限制。像其他许多学科一样,分子生物学是一门事实科学:与生俱来适合数据库存储的信息。在过去的十年中,已经出现了许多公共和私人数据库,以容纳基因组序列,蛋白质结构信息,功能基因组学数据等。这些数字资源库现在是科学传播的重要组成部分。下一个挑战是将庞大且不断增长的信息与学术期刊和其他媒体整合在一起。为了真正整合科学信息,我们必须现代化学术出版,以利用互联网的力量。这意味着不仅可以在线访问文章,超链接参考和基于Web的补充数据;这意味着要使用智能标记和结构化数字摘要使文章完全在计算机上可读。在这里,我们研究了学术期刊和数据库的角色变化。我们提出了对生物科学最佳信息架构的愿景,并以切实可行的步骤来结束,以改善我们今天对科学信息的处理,同时为将来扩展的中心索引铺平道路。

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