Extension of star coordinates into three dimensions

Selected References Traditional Star Coordinates displays a multi-variate data set by mapping it to two Cartesian dimensions. This technique facilitates cluster discovery and multi-variate analysis, but binding to two dimensions hides features of the data. Threedimensional Star Coordinates spreads out data elements to reveal features. This allows the user more intuitive freedom to explore and process the data sets. Three-dimensional Star Coordinates is implemented by extending the data structures and transformation facilities of traditional Star Coordinates. We have given high priority to maintaining the simple, traditional interface. We simultaneously extend existing features, such as scaling of axes, and add new features, such as system rotation in three dimensions. These extensions and additions enhance data visualization and cluster discovery. We use three examples to demonstrate the advantage of three-dimensional Star Coordinates over the traditional system. First, in an analysis of customer churn data, system rotation in three dimensions gives the user new insight into the data. Second, in cluster discovery of car data, the additional dimension allows the true shape of the data to be seen more easily. Third, in a multi-variate analysis of cities, the perception of depth increases the degree to which multivariate analysis can occur. We have presented three-dimensional Star Coordinates as a valuable extension of two-dimensional Star Coordinates. It retains all the utility of traditional 2D Star Coordinates and has several advantages over the two-dimensional technique. First, system rotation allows for configurations of data to be maintained while considering different views. Second, the infinitely enlarged space of volumes relative to surfaces allows the structure of the data to be discovered more easily. Third, depth cues provide attribute references which may be used to perform more complex multi-variate analysis. These features significantly enhance cluster discovery and data analysis. These features have been provided by extending Kandogan’s implementation of Star Coordinates in significant ways. In traditional 2D Star Coordinates, the underlying representation of the data is inherently twodimensional, the display is inherently two-dimensional, and the input device (mouse) is inherently two-dimensional. We overcome these limitations through a combination of methods and techniques. Three-dimensional Star Coordinates maintains the intuitiveness of two-dimensional Star Coordinates while providing and capitalizing on the new, three-dimensional aspects of the system. 1. Develop a three-dimensional visualization technique 2. System must be interactive 3. Build on a successful two-dimensional system, preserving the desirable features of the interface