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A network-based interface for the exploration of high-dimensional data spaces

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3 Author(s)
Zhiyuan Zhang ; Visual Analytics and Imaging Lab, Computer Science Department, Stony Brook University, NY, USA ; Kevin T. McDonnell ; Klaus Mueller

The navigation of high-dimensional data spaces remains challenging, making multivariate data exploration difficult. To be effective and appealing for mainstream application, navigation should use paradigms and metaphors that users are already familiar with. One such intuitive navigation paradigm is interactive route planning on a connected network. We have employed such an interface and have paired it with a prominent high-dimensional visualization paradigm showing the N-D data in undistorted raw form: parallel coordinates. In our network interface, the dimensions form nodes that are connected by a network of edges representing the strength of association between dimensions. A user then interactively specifies nodes/edges to visit, and the system computes an optimal route, which can be further edited and manipulated. In our interface, this route is captured by a parallel coordinate data display in which the dimension ordering is configured by the specified route. Our framework serves both as a data exploration environment and as an interactive presentation platform to demonstrate, explain, and justify any identified relationships to others. We demonstrate our interface within a business scenario and other applications.

Published in:

Visualization Symposium (PacificVis), 2012 IEEE Pacific

Date of Conference:

Feb. 28 2012-March 2 2012