Abstract
We describe a method turning scatterplot matrix visualizations into malleable graphical objects facilitating interaction and selection of pixelized data elements. The method relies on density estimation techniques [1,2] applied through standard image processing. A 2D scatterplot is considered as an image and is then transformed into nested regions that can be easily selected. Based on Wattenberg and Fisher [3], and as confirmed by our experience, we believe users have a good intuition interpreting and interacting with these multiscale graphical objects. Bio-molecular data serves here as a case study for our methodology. The method was discussed and designed in collaboration with experts in metabonomics and has proven to be useful and complementary to classical statistical methods.
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Jourdan, F., Paris, A., Koenig, PY., Melançon, G. (2007). Multiscale Scatterplot Matrix for Visual and Interactive Exploration of Metabonomic Data. In: Lévy, P.P., et al. Pixelization Paradigm. VIEW 2006. Lecture Notes in Computer Science, vol 4370. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71027-1_18
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DOI: https://doi.org/10.1007/978-3-540-71027-1_18
Publisher Name: Springer, Berlin, Heidelberg
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