School of Computer Science, Faculty of Life Sciences, University of Manchester, Manchester, UK.
Bioinformatics. 2010 Sep 15;26(18):i568-74. doi: 10.1093/bioinformatics/btq383.
In recent years, the gulf between the mass of accumulating-research data and the massive literature describing and analyzing those data has widened. The need for intelligent tools to bridge this gap, to rescue the knowledge being systematically isolated in literature and data silos, is now widely acknowledged.
To this end, we have developed Utopia Documents, a novel PDF reader that semantically integrates visualization and data-analysis tools with published research articles. In a successful pilot with editors of the Biochemical Journal (BJ), the system has been used to transform static document features into objects that can be linked, annotated, visualized and analyzed interactively (http://www.biochemj.org/bj/424/3/). Utopia Documents is now used routinely by BJ editors to mark up article content prior to publication. Recent additions include integration of various text-mining and biodatabase plugins, demonstrating the system's ability to seamlessly integrate on-line content with PDF articles.
近年来，积累的研究数据与描述和分析这些数据的大量文献之间的差距越来越大。现在人们广泛认识到，需要智能工具来弥合这一差距，从文献和数据孤岛中抢救系统隔离的知识。
为此，我们开发了 Utopia Documents，这是一种新颖的 PDF 阅读器，它将可视化和数据分析工具与已发表的研究文章语义集成。在与《生物化学杂志》（BJ）编辑的成功试点中，该系统已被用于将静态文档特征转换为可以链接、注释、可视化和交互式分析的对象（http://www.biochemj.org/bj/424/3/）。Utopia Documents 现在被 BJ 编辑常规用于在出版前标记文章内容。最近的新增功能包括集成各种文本挖掘和生物数据库插件，展示了系统能够将在线内容与 PDF 文章无缝集成的能力。
