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

有向无环图的成对视觉比较：人机交互视角

基本信息

批准号：
283588368
负责人：
Professorin Dr.-Ing. Tatiana Landesberger von Antburg
金额：
--
依托单位：
Abteilung Informatik
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2016
资助国家：
德国
起止时间：
2015-12-31 至 2018-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/283588368?language=en
关键词：
Pairwise Visual Comparison Directed Acyclic

项目摘要

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).

这个项目的目标是通过新的认知驱动的设计准则来改进成对网络比较的可视化。该项目将特别关注节点链接图中有向无环图的可视化比较。例如，在分析生物学系统发育树或评估金融网络的传染性时，就需要进行这种比较。在这些情况下，领域专家集中精力寻找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精心设计的可视化。有效的可视化使用的指导方针，其中除其他外，来自认知心理学和人机交互研究。到目前为止，HCI研究主要集中在导出单个网络可视化的指导方针。在节点链接图中，关于两个或多个网络的比较仍然有许多开放的研究问题。在这个项目中，我们将在并排节点链接显示中进行成对网络比较的感知和认知方面的研究。我们将集中在有向无环图对与单根节点的比较。我们将分析识别小图和大图中的结构和节点标签差异。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。该指南将改善网络的视觉比较，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检测和解释各种类型（未标记，分类和标记）的小图和大图中的图差异的因素。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。该项目结合了网络可视化和认知研究。因此，这需要两个领域的专家密切合作。因此，我们提出了一个D-A-CH计划的联合项目，有两个主要研究者（Landesberger von Antburg博士，德国，网络可视化）和（Margit Pohl教授，奥地利，认知和HCI）。

项目成果

期刊论文数量（6）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Crowdsourcing for Information Visualization: Promises and Pitfalls

DOI：
10.1007/978-3-319-66435-4_5
发表时间：
2017-09
期刊：
影响因子：
0
作者：
R. Borgo;Bongshin Lee;Benjamin Bach;S. Fabrikant;R. Jianu;A. Kerren;S. Kobourov;F. McGee;L. Micallef;T. V. Landesberger;K. Ballweg;S. Diehl;Paolo Simonetto;Michelle X. Zhou
通讯作者：
R. Borgo;Bongshin Lee;Benjamin Bach;S. Fabrikant;R. Jianu;A. Kerren;S. Kobourov;F. McGee;L. Micallef;T. V. Landesberger;K. Ballweg;S. Diehl;Paolo Simonetto;Michelle X. Zhou

Investigating Graph Similarity Perception: A Preliminary Study and Methodological Challenges