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Interactive Data Visualization using Mondrian

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  • Theus, Martin

Abstract

This paper presents the Mondrian data visualization software. In addition to standard plots like histograms, barcharts, scatterplots or maps, Mondrian offers advanced plots for high dimensional categorical (mosaic plots) and continuous data (parallel coordinates). All plots are linked and offer various interaction techniques. A special focus is on the seamless integration of categorical data. Unique is Mondrian's special selection technique, which allows advanced selections in complex data sets. Besides loading data from local (ASCII) files it can connect to databases, avoiding a local copy of the data on the client machine. Mondrian is written in 100% pure JAVA.

Suggested Citation

  • Theus, Martin, 2002. "Interactive Data Visualization using Mondrian," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 7(i11).
    • Handle: RePEc:jss:jstsof:v:007:i11
    DOI: http://hdl.handle.net/10.18637/jss.v007.i11
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    Cited by:

    1. Kumasaka, Natsuhiko & Shibata, Ritei, 2008. "High-dimensional data visualisation: The textile plot," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3616-3644, March.
    2. Tomokazu Fujino, 2007. "SVG+Ajax+R: a new framework for WebGIS," Computational Statistics, Springer, vol. 22(4), pages 511-520, December.
    3. Matthias Templ & Andreas Alfons & Peter Filzmoser, 2012. "Exploring incomplete data using visualization techniques," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(1), pages 29-47, April.
    4. John W. Emerson, 2008. "Interactive and Dynamic Graphics for Data Analysis: With R and GGobi by COOK, D. and SWAYNE, D," Biometrics, The International Biometric Society, vol. 64(4), pages 1301-1303, December.
    5. C. Hurley & R. Oldford, 2011. "Eulerian tour algorithms for data visualization and the PairViz package," Computational Statistics, Springer, vol. 26(4), pages 613-633, December.
    6. Simon Urbanek, 2009. "How to talk to strangers: ways to leverage connectivity between R, Java and Objective C," Computational Statistics, Springer, vol. 24(2), pages 303-311, May.

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