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Published on Jul 17, 2015
Even though exploring data visually is an integral part of the data analytic pipeline, we struggle to visually explore data once the number of dimensions go beyond three. This talk will focus on showcasing techniques to visually explore multi dimensional data p 3. The aim would be show examples of each of following techniques, potentially using one exemplar dataset.
Standard 2D/3D Approaches
Aesthetics e.g. Color, Size, Shape Small Multiples e.g. Trellis / Facets Matrices Views e.g. SPLOMs 3D Scatterplot Geometric Transformation Approaches
Alternate Coordinates e.g. Parallel, Star Projections e.g. Dimensionality Reduction Tablelens Glyph based Approaches
Star glyphs Stick Figures Pixel based Approaches
Pixel bar charts Space filling curves Stacked based Approaches
Dimensional Stacking Hierarchical Axis Treemaps The talk will also explore the role of interaction approaches to enhance our ability to visually explore the multi dimensional data.