4.0 Article

Exploring the limits of complexity: A survey of empirical studies on graph visualisation

期刊

VISUAL INFORMATICS
卷 2, 期 4, 页码 264-282

出版社

ELSEVIER
DOI: 10.1016/j.visinf.2018.12.006

关键词

Graph visualisation; Network visualisation; node-link diagrams; Cognitive scalability; Evaluations; Empirical studies

资金

  1. EPSRC [EP/N005724/1]
  2. European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant [747985]
  3. Australian Research Council [DP140100077]
  4. Marie Curie Actions (MSCA) [747985] Funding Source: Marie Curie Actions (MSCA)
  5. EPSRC [EP/N005724/1] Funding Source: UKRI

向作者/读者索取更多资源

For decades, researchers in information visualisation and graph drawing have focused on developing techniques for the layout and display of very large and complex networks. Experiments involving human participants have also explored the readability of different styles of layout and representations for such networks. In both bodies of literature, networks are frequently referred to as being 'large' or 'complex', yet these terms are relative. From a human-centred, experiment point-of-view, what constitutes 'large' (for example) depends on several factors, such as data complexity, visual complexity, and the technology used. In this paper, we survey the literature on human-centred experiments to understand how, in practice, different features and characteristics of node-link diagrams affect visual complexity. (C) 2019 Zhejiang University and Zhejiang University Press. Published by Elsevier B.V.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.0
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据