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Proceedings Paper

Visual browsing of remote and distributed data
Author(s): Parthasarathy Krishnaswamy; Stephen G. Eick; Robert L. Grossman
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Paper Abstract

Data repositories around the world hold many thousands of datasets. A problem for remote dataset users is to browse the repositories and efficiently locate relevant datasets. In this note, we introduce the Iconic Remote Visual Data Exploration tool (IRVDX), which provides visual browsing for exploring the features of remote and distributed data without the necessity of downloading the entire dataset. IRVDX employs three kinds of visualizations: one provides a reduced representation of the datasets, which we call Dataset Icons. These icons show the important statistical characteristics of datasets and help to identify relevant datasets from distributed repositories. Another one is called the Remote Dataset Visual Browser that provides visualizations to browse remote data without downloading the complete dataset to identify its content. The final one provides visualizations to show the degree of similarity between two datasets and to visually determine whether a join of two remote datasets will be meaningful. In this paper, we describe the design and implementation of IRVDX in detail. We assess the benefits of our Dataset Icons against the traditional text-based interfaces and show the usefulness of IRVDX by conducting experiments with datasets from the UCI KDD Archive.

Paper Details

Date Published: 11 March 2005
PDF: 9 pages
Proc. SPIE 5669, Visualization and Data Analysis 2005, (11 March 2005); doi: 10.1117/12.584371
Show Author Affiliations
Parthasarathy Krishnaswamy, Univ. of Illinois at Chicago (United States)
Stephen G. Eick, Univ. of Illinois at Chicago (United States)
Robert L. Grossman, Univ. of Illinois at Chicago (United States)

Published in SPIE Proceedings Vol. 5669:
Visualization and Data Analysis 2005
Robert F. Erbacher; Jonathan C. Roberts; Matti T. Grohn; Katy Borner, Editor(s)

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