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2001 IEEE Symposium on Information Visualization (InfoVis 2001)
Pixel Bar Charts: A New Technique for Visualizing Large Multi-Attribute Data Sets without Aggregation
San Diego, CA
October 22-October 23
ISBN: 0-7695-1342-5
Daniel Keim, University of Constance
Ming Hao, Hewlett Packard Research Laboratories
Umesh Dayal, Hewlett Packard Research Laboratories
Meichun Hsu, Hewlett Packard Research Laboratories
Julain Ladisch, Goethestr.4
Simple presentation graphics are intuitive and easy-to-use, but show only highly aggregated data and present only a very limited number of data values (as in the case of bar charts). In addition, these graphics may have a high degree of overlap which may occlude a significant portion of the data values (as in the case of the x-y plots). In this paper, we therefore propose a generalization of traditional bar charts and x-y-plots which allows the visualization of large amounts of data. The basic idea is to use the pixels within the bars to present the detailed information of the data records. Our so-called pixel bar charts retain the intuitiveness of traditional bar charts while allowing very large data sets to be visualized in an effective way. We show that, for an effective pixel placement, we have to solve complex optimization problems, and present an algorithm which efficiently solves the problem. Our application using real-world e-commerce data shows the wide applicability and usefulness of our new idea.
Index Terms:
Pixel Bar Charts, Multi-attributes Visualization, No-aggregation, No-overlapping
Citation:
Daniel Keim, Ming Hao, Umesh Dayal, Meichun Hsu, Julain Ladisch, "Pixel Bar Charts: A New Technique for Visualizing Large Multi-Attribute Data Sets without Aggregation," ieee_infovis, pp.113, 2001 IEEE Symposium on Information Visualization (InfoVis 2001), 2001
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