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

Subject Area Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
Term from 2016 to 2019
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 283588368
 
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).
DFG Programme Research Grants
International Connection Austria
 
 

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