In Situ Exploration of Large Dynamic Networks
In Situ Exploration of Large Dynamic Networks
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DOI：
10.1109/tvcg.2011.213
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发表时间：
2011-12
影响因子：
5.2
通讯作者：
S. Hadlak;Hans-Jörg Schulz;H. Schumann
中科院分区：
文献类型：
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作者：
S. Hadlak;Hans-Jörg Schulz;H. Schumann
从大型僵尸网络到社交网络，大型动态网络的分析在许多领域都是一个挑战。由于动态网络表现出不同的特性，例如，由于具有稀疏或密集的结构，或者具有连续或离散的时间线，已经专门设计了各种可视化技术来处理网络结构和时间的这些不同方面。这种广泛的现有技术是合理的，因为很少有一个单一的可视化是适合涵盖整个可视化分析。相反，在动态图的探索过程中，随着分析的重点在数据的时间和结构方面之间转移，视觉表示经常被切换。为了支持这样的切换在一个无缝和直观的方式，我们介绍了原位可视化的概念-一种新的策略，紧密结合现有的可视化技术的动态网络。它通过允许用户在基础可视化中交互式地选择一个区域来实现，然后针对该区域应用不同的可视化技术并将其嵌入到所做的选择中。这允许改变本地选择的一组数据项（如节点或时间点）的显示方式-就在它们所处的位置，从而支持用户的整体心理地图。使用这种方法，用户可以在不同的视觉表示之间无缝切换，以使基础可视化的区域适应其中数据的细节或当前分析焦点。本文提出并讨论了动态图形可视化的原位可视化策略及其影响。此外，它说明了它的有用性，采用它的可视化探索动态网络从两个不同的领域：模型版本和无线网状网络。
The analysis of large dynamic networks poses a challenge in many fields, ranging from large bot-nets to social networks. As dynamic networks exhibit different characteristics, e.g., being of sparse or dense structure, or having a continuous or discrete time line, a variety of visualization techniques have been specifically designed to handle these different aspects of network structure and time. This wide range of existing techniques is well justified, as rarely a single visualization is suitable to cover the entire visual analysis. Instead, visual representations are often switched in the course of the exploration of dynamic graphs as the focus of analysis shifts between the temporal and the structural aspects of the data. To support such a switching in a seamless and intuitive manner, we introduce the concept of in situ visualization- a novel strategy that tightly integrates existing visualization techniques for dynamic networks. It does so by allowing the user to interactively select in a base visualization a region for which a different visualization technique is then applied and embedded in the selection made. This permits to change the way a locally selected group of data items, such as nodes or time points, are shown - right in the place where they are positioned, thus supporting the user's overall mental map. Using this approach, a user can switch seamlessly between different visual representations to adapt a region of a base visualization to the specifics of the data within it or to the current analysis focus. This paper presents and discusses the in situ visualization strategy and its implications for dynamic graph visualization. Furthermore, it illustrates its usefulness by employing it for the visual exploration of dynamic networks from two different fields: model versioning and wireless mesh networks.