Visual analytics of static and dynamic networks taking into account uncertainty and fuzzy clustering

该研究项目旨在开发和改进网络(图)的可视分析方法。重点是与网络不确定性可视化相关的研究问题。在这里，将解决与网络的聚类和比较相关的开放可视化问题。我们将同时考虑图属性中的不确定性和社区结构中的模糊性。除了单个图形的不确定性可视化之外，我们还将研究不确定性和模糊性如何影响两个图形的可视比较，以及如何将它们整合到可视分析过程中。在此背景下，动态图形的可视分析也将被讨论。图的视觉分析的基本研究问题将被生物网络的实际应用所补充。

This research project aims to develop and improve approaches to visual analytics of networks (graphs). The focal point are research questions related to the visualization of uncertainty in networks. Here, open visualization problems related to the clustering and comparison of networks will be addressed. We will consider both uncertainty in graph attributes and fuzziness in the community structures. Besides uncertainty visualization for individual graphs, we will investigate how uncertainty and fuzziness affect the visual comparison of two graphs and how they can be integrated into the visual analytics process. In this context, visual analytics of dynamic graphs will be addressed as well. The basic research questions of visual analytics of graphs will be complemented by the practical application to biological networks.