Share Email Print
cover

Proceedings Paper

Multi-focus and multi-window techniques for interactive network exploration
Author(s): Priya Krishnan Sundarararajan; Ole J. Mengshoel; Ted Selker
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Networks analysts often need to compare nodes in different parts of a network. When zoomed to fit a computer screen, the detailed structure and node labels of even a moderately-sized network (say, with 500 nodes) can become invisible or difficult to read. Still, the coarse network structure typically remains visible, and helps orient an analyst’s zooming, scrolling, and panning operations. These operations are very useful when studying details and reading node labels, but in the process of zooming in on one network region, an analyst may lose track of details elsewhere. To address such problems, we present in this paper multi-focus and multi-window techniques that improve interactive exploration of networks. Based on an analyst’s selection of focus nodes, our techniques partition and selectively zoom in on network details, including node labels, close to the focus nodes. Detailed data associated with the zoomed-in nodes can thus be more easily accessed and inspected. The approach enables a user to simultaneously focus on and analyze multiple node neighborhoods while keeping the full network structure in view. We demonstrate our technique by showing how it supports interactive debugging of a Bayesian network model of an electrical power system. In addition, we show that it can simplify visual analysis of an electrical power network as well as a medical Bayesian network.

Paper Details

Date Published: 4 February 2013
PDF: 15 pages
Proc. SPIE 8654, Visualization and Data Analysis 2013, 86540O (4 February 2013); doi: 10.1117/12.2005659
Show Author Affiliations
Priya Krishnan Sundarararajan, Carnegie Mellon Silicon Valley (United States)
Ole J. Mengshoel, Carnegie Mellon Silicon Valley (United States)
Ted Selker, Carnegie Mellon Silicon Valley (United States)


Published in SPIE Proceedings Vol. 8654:
Visualization and Data Analysis 2013
Pak Chung Wong; David L. Kao; Ming C. Hao; Chaomei Chen, Editor(s)

© SPIE. Terms of Use
Back to Top