TY - GEN
T1 - A network-based interface for the exploration of high-dimensional data spaces
AU - Zhang, Zhiyuan
AU - McDonnell, Kevin T.
AU - Mueller, Klaus
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - correlation
KW - linked displays
KW - multivariate data
KW - network-based
KW - parallel coordinates
KW - Visual analytics
UR - https://www.scopus.com/pages/publications/84860661829
U2 - 10.1109/PacificVis.2012.6183569
DO - 10.1109/PacificVis.2012.6183569
M3 - Conference contribution
AN - SCOPUS:84860661829
SN - 9781467308649
T3 - IEEE Pacific Visualization Symposium 2012, PacificVis 2012 - Proceedings
SP - 17
EP - 24
BT - IEEE Pacific Visualization Symposium 2012, PacificVis 2012 - Proceedings
T2 - 5th IEEE Pacific Visualization Symposium 2012, PacificVis 2012
Y2 - 28 February 2012 through 2 March 2012
ER -