AVEDA: Statistical Tests for Finding Interesting Visualisations

Authors:
Katharina Tschumitschew;Frank Klawonn
Affiliations:
Department of Computer Science, University of Applied Sciences Braunschweig/Wolfenbuettel, Wolfenbuettel, Germany D-38302;Department of Computer Science, University of Applied Sciences Braunschweig/Wolfenbuettel, Wolfenbuettel, Germany D-38302 and Department for Cell Biology, Helmholtz Centre for Infection Research, ...
Venue:
KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part I
Year:
2009

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Abstract

Visualisation is usually one of the first steps in handling any data analysis problem. Visualisations are an intuitive way to discover inconsistencies, outliers, dependencies, interesting patterns and peculiarities in the data. However, due to modern computer technology, a vast number of visualisation techniques is available nowadays. Even if only simple scatterplots, plotting pairs of variables against each other, are considered, the number of scatterplots is too large for high-dimensional data to visually inspect each scatterplot. In this paper, we propose a system architecture called AVEDA (Automatic Visual Exploratory Data Analysis) which computes a large number of visualisations, filters out those ones that might contain special patterns and shows only these interesting visualisations to the user. The filtering process for the visualisations is based on statistical tests and statistical measures.