VISUS, University of Stuttgart, Germany.
IEEE Trans Vis Comput Graph. 2011 Dec;17(12):2344-53. doi: 10.1109/TVCG.2011.226.
We present a novel dynamic graph visualization technique based on node-link diagrams. The graphs are drawn side-byside from left to right as a sequence of narrow stripes that are placed perpendicular to the horizontal time line. The hierarchically organized vertices of the graphs are arranged on vertical, parallel lines that bound the stripes; directed edges connect these vertices from left to right. To address massive overplotting of edges in huge graphs, we employ a splatting approach that transforms the edges to a pixel-based scalar field. This field represents the edge densities in a scalable way and is depicted by non-linear color mapping. The visualization method is complemented by interaction techniques that support data exploration by aggregation, filtering, brushing, and selective data zooming. Furthermore, we formalize graph patterns so that they can be interactively highlighted on demand. A case study on software releases explores the evolution of call graphs extracted from the JUnit open source software project. In a second application, we demonstrate the scalability of our approach by applying it to a bibliography dataset containing more than 1.5 million paper titles from 60 years of research history producing a vast amount of relations between title words.
我们提出了一种新颖的基于节点链接图的动态图可视化技术。这些图从左到右并排绘制，作为一系列与水平时间线垂直放置的窄条。图的层次化组织的顶点排列在垂直的平行线之间，这些线界定了条纹；有向边从左到右连接这些顶点。为了解决大型图中大量边的重叠问题，我们采用了一种散射方法，将边转换为基于像素的标量场。该场以可扩展的方式表示边密度，并通过非线性颜色映射进行描绘。可视化方法通过交互技术得到补充，这些技术支持通过聚合、过滤、刷选和选择性数据缩放来进行数据探索。此外，我们形式化了图模式，以便可以根据需要交互式地突出显示它们。一个关于软件版本的案例研究探索了从 JUnit 开源软件项目中提取的调用图的演变。在第二个应用中，我们通过将其应用于包含 60 年研究历史中超过 150 万篇论文标题的文献数据集，展示了我们方法的可扩展性，生成了大量标题词之间的关系。
