%0期刊文章@ 1438- 8871% I JMIR Publicat卡塔尔世界杯8强波胆分析ions Inc. %V 18% N 1% P e13% T自然语言搜索接口:健康数据需要单域变量搜索%A Jay,Caroline %A Harper,Simon %A Dunlop,Ian %A Smith,Sam %A Sufi,Shoaib %A Goble,Carole %A Buchan,Iain %+信息管理组，曼彻斯特大学计算机科学学院，曼彻斯特牛津路Kilburn大楼，M13 9PL，英国，44 1612750599，simon.harper@manchester.ac.uk %K搜索行为%K搜索引擎%K研究数据档案%K用户计算机界面%D 2016 %7 14.01.2016 %9原始论文%J J医学Internet Res %G英文%X背景:数据发现，特别是关键变量及其相互关系的发现，是二次数据分析的关键，反过来，也是数据科学不断发展的领域。界面设计人员假定他们的用户是领域专家，因此他们提供了复杂的界面来支持这些“专家”。这样的界面回到了搜索第一次就需要准确的时代，因为每次搜索都有很高的计算成本。我们的工作是医疗和社会研究资助机构之间的一项政府研究倡议的一部分，该倡议旨在改善医疗研究中社会数据的使用。目标:数据科学的跨学科性质不能对特定科学家的领域专业知识做出假设，他们的兴趣可能涉及多个领域。在这里，我们考虑科学家寻求存档数据进行二次分析的共同需求。这更符合“谷歌一代”的搜索需求，而不是他们的单一领域、单一工具的祖先。我们的研究比较了类似google的界面和在数据存档中搜索不复杂健康数据的传统方法。 Methods: Two user interfaces are evaluated for the same set of tasks in extracting data from surveys stored in the UK Data Archive (UKDA). One interface, Web search, is “Google-like,” enabling users to browse, search for, and view metadata about study variables, whereas the other, traditional search, has standard multioption user interface. Results: Using a comprehensive set of tasks with 20 volunteers, we found that the Web search interface met data discovery needs and expectations better than the traditional search. A task × interface repeated measures analysis showed a main effect indicating that answers found through the Web search interface were more likely to be correct (F1,19=37.3, P<.001), with a main effect of task (F3,57=6.3, P<.001). Further, participants completed the task significantly faster using the Web search interface (F1,19=18.0, P<.001). There was also a main effect of task (F2,38=4.1, P=.025, Greenhouse-Geisser correction applied). Overall, participants were asked to rate learnability, ease of use, and satisfaction. Paired mean comparisons showed that the Web search interface received significantly higher ratings than the traditional search interface for learnability (P=.002, 95% CI [0.6-2.4]), ease of use (P<.001, 95% CI [1.2-3.2]), and satisfaction (P<.001, 95% CI [1.8-3.5]). The results show superior cross-domain usability of Web search, which is consistent with its general familiarity and with enabling queries to be refined as the search proceeds, which treats serendipity as part of the refinement. Conclusions: The results provide clear evidence that data science should adopt single-field natural language search interfaces for variable search supporting in particular: query reformulation; data browsing; faceted search; surrogates; relevance feedback; summarization, analytics, and visual presentation. %M 26769334 %R 10.2196/jmir.4912 %U //www.mybigtv.com/2016/1/e13/ %U https://doi.org/10.2196/jmir.4912 %U http://www.ncbi.nlm.nih.gov/pubmed/26769334