Bales Michael E, Kaufman David R, Johnson Stephen B
Department of Biomedical Informatics, Columbia University, New York, NY, USA.
AMIA Annu Symp Proc. 2009 Nov 14;2009:24-8.
Searches of bibliographic databases generate lists of articles but do little to reveal connections between authors, institutions, and grants. As a result, search results cannot be fully leveraged. To address this problem we developed Sciologer, a prototype search and visualization system. Sciologer presents the results of any PubMed query as an interactive network diagram of the above elements. We conducted a cognitive evaluation with six neuroscience and six obesity researchers. Researchers used the system effectively. They used geographic, color, and shape metaphors to describe community structure and made accurate inferences pertaining to a) collaboration among research groups; b) prominence of individual researchers; and c) differentiation of expertise. The tool confirmed certain beliefs, disconfirmed others, and extended their understanding of their own discipline. The majority indicated the system offered information of value beyond a traditional PubMed search and that they would use the tool if available.
对文献数据库进行检索会生成文章列表,但在揭示作者、机构和资助之间的联系方面作用甚微。因此,检索结果无法得到充分利用。为解决这一问题,我们开发了Sciologer,这是一个原型检索与可视化系统。Sciologer将任何PubMed查询的结果呈现为上述元素的交互式网络图。我们对六位神经科学研究人员和六位肥胖症研究人员进行了认知评估。研究人员有效地使用了该系统。他们使用地理、颜色和形状隐喻来描述社区结构,并对以下方面做出了准确推断:a)研究小组之间的合作;b)个别研究人员的知名度;c)专业领域的差异。该工具证实了某些观点,否定了其他观点,并扩展了他们对自己学科的理解。大多数人表示,该系统提供了超越传统PubMed检索的有价值信息,并且如果有该工具,他们会使用它。