A Tool for Analyzing Categorical Data Visually with Granular Representation

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.

• Type: Journal
• Year: 2009
• Where: HCI
• Authors: Kousuke Shiraishi, Kazuo Misue, Jiro Tanaka
• Keywords: Categorical Data, Granular Representation, HCI 2009, Human Computer Interaction, Major Concern