Pairwise Visual Comparison of Directed Acyclic Graphs: A Human-Computer Interaction Perspective

这个项目的目标是通过新的认知驱动的设计准则来改善两两网络比较的可视化。该项目将特别关注节点链接图中有向无环图的视觉比较。例如，在分析生物学中的系统发育树或评估金融网络中的传染时，就需要进行这种比较。在这些情况下，领域专家专注于寻找被比较的两个网络之间的共性和差异。这种分析通常以可视化的形式进行。视觉探索能够识别差异所在，从而从这些差异中提取见解。有效的视觉网络比较需要一个设计良好的可视化。有效的可视化使用指南，这些指南除其他外来自认知心理学和人机交互（HCI）的研究。到目前为止，人工智能的研究主要集中在推导单个网络可视化的指导方针。关于节点链接图中两个或多个网络的比较，仍有许多尚未解决的研究问题。在这个项目中，我们将对并行节点链接显示中两两网络比较的感知和认知方面进行研究。我们将集中讨论具有单根节点的有向无环图对的比较。我们将分析小图和大图中结构和节点标签差异的识别。设想的项目结果是网络比较可视化的新指南，特别是比较有向无环图。该指南将改进网络的可视化比较，特别是在生物学和金融稳定性分析中的应用。我们将确定一组影响各种类型（未标记、分类和标记）的小图和大图的图差异检测和解释的因素。我们还将为HCI中的视觉网络比较研究提供新的基准数据集。本项目将网络可视化与认知研究相结合。因此，这需要两个领域的专家密切合作。因此，我们在D-A-CH方案中提出了一个联合项目，由两位主要研究者（Landesberger von Antburg博士，德国，网络可视化）和（Margit Pohl教授，奥地利，认知和HCI）组成。

The goal of this project is to improve visualizations for pairwise network comparisons via new cognition-driven design guidelines.The project will specifically concentrate on the visual comparison of directed acyclic graphs in node-link diagrams. Such comparison is needed, for example, in the analysis of phylogenetic trees in biology or in the assessment of contagion in financial networks. In these cases, the domain experts concentrate on finding commonalities and differences between the two networks being compared. This analysis is often undertaken in a visualized form. Visual exploration enables to identify where the differences are located and thereby to extract insights from these differences.Effective visual network comparison requires a well-designed visualization. Effective visualization uses guidelines, which are inter alia derived from research in cognitive psychology and human-computer interaction (HCI). Until now, HCI research has mainly focused on deriving guidelines for the visualization of single networks. There are still many open research questions concerning the comparison of two or more networks in node-link diagrams. In this project, we will conduct studies on perceptual and cognitive aspects of pairwise network comparison in a side-by-side node-link display. We will concentrate on the comparison of pairs of directed acyclic graphs with single root nodes. We will analyze the recognition of structural and node label differences in small and large graphs. The envisaged project results are novel guidelines for the visualization of network comparison, specifically for comparing directed acyclic graphs. The guidelines will improve visual comparison of networks, particularly applied in biology and financial stability analysis. We will identify a set of factors influencing detection and interpretation of graph differences in small and large graphs of various types (unlabeled, categorical and labeled). We will also present new benchmark datasets for visual network comparison studies in HCI. This project combines network visualization and cognition research. It therefore requires a close cooperation between experts from both fields. We thus propose a joint project in D-A-CH scheme, with two principal investigators (Dr. Landesberger von Antburg, Germany, network visualization) and (Prof. Margit Pohl, Austria, cognition and HCI).