Proposal of BBS with Visual Representation for Online Data Analysis

Authors: Yasufumi Takama and Yuta Seo,  Tokyo Metropolitan University

A concept of bulletin board system (BBS) equipped with information visualization techniques is proposed for supporting online data analysis. Al-though a group discussion is known to be effective for analyzing data from various viewpoints, the number of participants has to be limited in terms of time and space constraints. To solve the problem, this paper proposes to augment BBS, which is one of popular tools on the Web. In order for discussion participants to share the data online, the system provides them with a visual representation of target data, which contribute to derive the comments from participants, as well as to compare the obtained comments. In order to show the potential of the concept, a BBS equipped with KeyGraph is also developed for supporting online chance discovery. It has functions for making visual annotations on the KeyGraph, as well as a function for retrieving similar scenarios. The experi-mental result shows the effectiveness of the BBS in terms of the usefulness of scenario generation support functions as well as that of scenario retrieval engines.