A Tool for Analyzing Categorical Data Visually with Granular Representation

Authors:
Kousuke Shiraishi;Kazuo Misue;Jiro Tanaka
Affiliations:
Department of Computer Science, University of Tsukuba, Tsukuba, Japan 305-8573;Department of Computer Science, University of Tsukuba, Tsukuba, Japan 305-8573;Department of Computer Science, University of Tsukuba, Tsukuba, Japan 305-8573
Venue:
Proceedings of the Symposium on Human Interface 2009 on Human Interface and the Management of Information. Information and Interaction. Part II: Held as part of HCI International 2009
Year:
2009

Citing 6
Cited 0

Readings in information visualization: using vision to think

Readings in information visualization: using vision to think
Visualizing Categorical Data

Visualizing Categorical Data
Tree-Maps: a space-filling approach to the visualization of hierarchical information structures

VIS '91 Proceedings of the 2nd conference on Visualization '91
Dust & magnet: multivariate information visualization using a magnet metaphor

Information Visualization
Interactive Quantification of Categorical Variables in Mixed Data Sets

IV '08 Proceedings of the 2008 12th International Conference Information Visualisation
Mapping nominal values to numbers for effective visualization

INFOVIS'03 Proceedings of the Ninth annual IEEE conference on Information visualization

Quantified Score

Hi-index	0.00

Visualization

Abstract

Categorical data appears in various places, and dealing with it has been a major concern in analysis fields. However, representing not only global trends but also local trends of data simultaneously by conventional techniques is difficult. We propose a visualization method called "granular representation" for analyzing categorical data visually. Our approach visually represents data as a set of objects and allows intuitive analysis instead of the traditional way with tables of numbers. We developed a tool by integrating granular representation and bar charts. The effectiveness of the tool is demonstrated using real data about media consumption.