Star Coordinates : A Multi-dimensional Visualization Technique with Uniform Treatment of Dimensions Rohit Kelapure & David Tussedorf.

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Presentation transcript:

Star Coordinates : A Multi-dimensional Visualization Technique with Uniform Treatment of Dimensions Rohit Kelapure & David Tussedorf

Multi-dimensional Data Treats each dimension uniformly Follows the Info-Viz. Mantra : Overview First Zoom and Filter Details on Demand

Star Co-ordinates : Curvilinear Co-ordinate System Name Co-ordinate Axes on a Circle with equal Angles . Model-Year MPG Data-Points Scaled to Length of axis. Minimum Mapping : Origin Maximum mapping : Other end of Axis Acceleration Cylinders Weight Displacement Horsepower

Calculation of data point location for an 8-dimensional dataset Name- 1 Star Cartesian Model-Year-8 MPG - 2 d j3 d j2 d j4 ON (x,y) O(x,y) and sequence of N Two dimensional Vectors. An = < a1, a2, a3……. an > d j1 d j5 Accl.-7 Cylinders -3 p d j8 d j6 Data-element Dj Point Pj d j7 Weight -6 Displacement- 4 Horsepower – 5 Pj : Sum of all unit Vectors Ui = ( uxi , uyi )on each co-ordinate multiplied by the value of that data element for that co-ordinate

Hierarchially Clustered Datasets Transformations : Scaling Rotations Queries Applications : Hierarchially Clustered Datasets Multifactor Analysis

Comparison Parallel Star Dimension inc. Space needed inc. Space needed is constant. Data- elements  Lines showing exact Data Values Data-elements  Simpler & Space Efficient points.