Lee Bongshin, Parr Cynthia S, Plaisant Catherine, Bederson Benjamin B, Veksler Vladislav D, Gray Wayne D, Kotfila Christopher
Human-Computer Interaction Lab, Department of Computer Science, University of Maryland, College Park 20742, USA.
IEEE Trans Vis Comput Graph. 2006 Nov-Dec;12(6):1414-26. doi: 10.1109/TVCG.2006.106.
Despite extensive research, it is still difficult to produce effective interactive layouts for large graphs. Dense layout and occlusion make food webs, ontologies, and social networks difficult to understand and interact with. We propose a new interactive Visual Analytics component called TreePlus that is based on a tree-style layout. TreePlus reveals the missing graph structure with visualization and interaction while maintaining good readability. To support exploration of the local structure of the graph and gathering of information from the extensive reading of labels, we use a guiding metaphor of "Plant a seed and watch it grow." It allows users to start with a node and expand the graph as needed, which complements the classic overview techniques that can be effective at (but often limited to) revealing clusters. We describe our design goals, describe the interface, and report on a controlled user study with 28 participants comparing TreePlus with a traditional graph interface for six tasks. In general, the advantage of TreePlus over the traditional interface increased as the density of the displayed data increased. Participants also reported higher levels of confidence in their answers with TreePlus and most of them preferred TreePlus.
尽管进行了广泛的研究，但为大型图表生成有效的交互式布局仍然很困难。密集的布局和遮挡使得食物网、本体和社交网络难以理解和交互。我们提出了一种新的交互式视觉分析组件，称为TreePlus，它基于树状布局。TreePlus通过可视化和交互揭示缺失的图形结构，同时保持良好的可读性。为了支持对图形局部结构的探索以及从大量标签阅读中收集信息，我们使用了“种下一颗种子，看着它生长”的引导隐喻。它允许用户从一个节点开始，并根据需要扩展图形，这补充了经典的概述技术，这些技术在揭示集群方面可能有效（但通常有限）。我们描述了我们的设计目标，描述了界面，并报告了一项有28名参与者的对照用户研究，该研究针对六项任务将TreePlus与传统图形界面进行了比较。总体而言，随着显示数据密度的增加，TreePlus相对于传统界面的优势也在增加。参与者还报告说，使用TreePlus时他们对答案的信心更高，并且大多数人更喜欢TreePlus。
