Evaluation on interactive visualization data with scatterplots

Visual Informatics

David Arness¹  Natalie Miller²  Simeon Simoff³  Quang Vinh Nguyen⁴  Weidong Huang⁵  Mao Lin Huang⁵ 

[1] Correspondence to: School of Computer, Data and Mathematical Sciences Western Sydney University Parramatta, NSW, Australia.;School of Computer, Data and Mathematical Sciences, Western Sydney University, Australia;Faculty of Transdisciplinary Innovation, University of Technology, Sydney, Australia;MARCS Institute, Western Sydney University, Australia;School of Psychology, Western Sydney University, Australia;

关键词: Multivariate data visualization;    Multidimensional data visualization;    Scatterplots;    Scatterplot matrix;    Controlled study;   

DOI  :  

来源: DOAJ

【 摘 要 】

Scatterplots and scatterplot matrix methods have been popularly used for showing statistical graphics and for exposing patterns in multivariate data. A recent technique, called Linkable Scatterplots, provides an interesting idea for interactive visual exploration which provides a set of necessary plot panels on demand together with interaction, linking and brushing. This article presents a controlled study with a mixed-model design to evaluate the effectiveness and user experience on the visual exploration when using a Sequential-Scatterplots who a single plot is shown at a time, Multiple-Scatterplots who number of plots can be specified and shown, and Simultaneous-Scatterplots who all plots are shown as a scatterplot matrix. Results from the study demonstrated higher accuracy using the Multiple-Scatterplots visualization, particularly in comparison with the Simultaneous-Scatterplots.​ While the time taken to complete tasks was longer in the Multiple-Scatterplots technique, compared with the simpler Sequential-Scatterplots, Multiple-Scatterplots is inherently more accurate. Moreover, the Multiple-Scatterplots technique is the most highly preferred and positively experienced technique in this study. Overall, results support the strength of Multiple-Scatterplots and highlight its potential as an effective data visualization technique for exploring multivariate data.

【 授权许可】

Unknown