Knowledge Graphs have become a ubiquitous technology powering search engines, recommender systems, connected objects, corporate knowledge management and Open Data. They rely on small units of information named triples that can be combined to form higher level statements across datasets following information needs. But data producers face a problem: reconstituting chains of triples has a high cognitive cost, which hinders them from gaining meaningful overviews of their own datasets. We introduce path outlines: conceptual objects characterizing sequences of triples with descriptive statistics. We interview 11 data producers to evaluate their interest. We present Path Outlines, a tool to browse path-based summaries, based on coordinated views with 2 novel visualisations. We compare Path Outlines with the current baseline technique in an experiment with 36 participants. We show that it is 3 times faster, leads to better task completion, less errors, that participants prefer it, and find tasks easier with it.
翻译:知识图已成为一个无处不在的技术动力搜索引擎、建议系统、连接对象、企业知识管理和开放数据。它们依赖名为三倍的小型信息单位,这些单位可以结合成更高层次的根据信息需求跨数据集的报表。但数据制作者面临一个问题:重建三连串的认知成本很高,这阻碍他们获得对其自身数据集有意义的概览。我们引入了路径大纲:以三连串描述性统计数据为特征的三连串序列的概念性对象。我们采访了11个数据制作者,以评估他们的兴趣。我们展示了路径大纲,这是根据两个新颖的可视化观点浏览路径摘要的工具。我们在一次实验中将路径大纲与当前基线技术比对36个参与者。我们显示,它速度是3倍,比3倍快,导致更好的任务完成,减少错误,使参与者更喜欢它,并更容易找到任务。