This paper presents a new interactive scatter plot visualization for multi-dimensional data analysis. We apply Rough Set Theory (RST) to reduce the visual complexity through dimensionality reduction. We use an innovative point-to-region mouse click concept to enable direct interactions with scatter points that are theoretically impossible. To show the decision trend we use a virtual Z dimension to display a set of linear flows showing approximation of the decision trend. We conducted case studies to demonstrate the effectiveness and usefulness of our new technique for analyzing the property of three popular data sets including wine quality, wages and cars. The paper also includes a pilot usability study to evaluate parallel coordinate visualization with scatter plot matrices visualization with RST results.

Item Type:	Refereed Article
Keywords:	visualization, visual analytics
Research Division:	Information and Computing Sciences
Research Group:	Library and information studies
Research Field:	Human information interaction and retrieval
Objective Division:	Expanding Knowledge
Objective Group:	Expanding knowledge
Objective Field:	Expanding knowledge in the information and computing sciences
UTAS Author:	Huang, W (Dr Tony Huang)
ID Code:	105463
Year Published:	2016
Web of Science® Times Cited:	4
Deposited By:	Information and Communication Technology
Deposited On:	2016-01-05
Last Modified:	2018-03-20
Downloads:	0