Spherule diagrams: A matrix-based set visualization compared with Euler diagrams

Mithileysh Sathiyanarayanan, Donato Pirozzi
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引用次数: 6

Abstract

The explosive growth of the internet, the overall computerization of the engineering, medical, business and defense sectors have created a widespread need of visualization techniques to explore large and complex datasets. As the data keeps growing in complexity, users find it difficult to navigate and understand the relationships between the sets. There are limitations such as scalability and sub-optimal layouts being produced with the state-of-the-art visualization methods such as Euler diagrams, Treemap diagrams and ConSets. So, an effective visual method is in great need to produce an optimal layout and identify set properties with ease. This motivated us to develop a novel visual method called “Spherule diagrams” to improve the analysis of set relationships effectively. Then a small-scale user preference study was conducted to compare Euler diagrams with Spherule diagrams, where 80% participants preferred Spherule diagrams for its simplicity, navigation, better layout and set ordering characteristics. The other results based on error rate and rating, Spherule diagrams outperformed Euler diagrams. Thus, we provide evidence that Spherule diagrams are preferred over Euler diagrams for visualizing set relations.
球规则图:与欧拉图相比,基于矩阵的集合可视化
互联网的爆炸式增长,工程、医疗、商业和国防部门的全面计算机化,创造了对可视化技术的广泛需求,以探索大型和复杂的数据集。随着数据的复杂性不断增加,用户发现很难导航和理解集合之间的关系。使用最先进的可视化方法(如欧拉图、Treemap图和conset)产生的可扩展性和次优布局等限制是存在的。因此,迫切需要一种有效的可视化方法来生成最优布局,并方便地识别集合属性。这促使我们开发了一种新的可视化方法,称为“球规则图”,以有效地改进集合关系的分析。然后进行了小规模的用户偏好研究,将Euler图与Spherule图进行比较,80%的参与者更喜欢Spherule图,因为它简单,导航,更好的布局和集合顺序特征。其他基于错误率和评级的结果显示,球规则图优于欧拉图。因此,我们提供的证据表明,球规则图比欧拉图更适合于可视化集合关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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