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MoleView: An Attribute and Structure-Based Semantic Lens for Large Element-Based Plots
Dec. 2011 (vol. 17 no. 12)
pp. 2600-2609
Christophe Hurter, DSNA, IRIT, Toulouse France
Alexandru Telea, University of Groningen
Ozan Ersoy, University of Groningen
We present MoleView, a novel technique for interactive exploration of multivariate relational data. Given a spatial embedding of the data, in terms of a scatter plot or graph layout, we propose a semantic lens which selects a specific spatial and attribute-related data range. The lens keeps the selected data in focus unchanged and continuously deforms the data out of the selection range in order to maintain the context around the focus. Specific deformations include distance-based repulsion of scatter plot points, deforming straight-line node-link graph drawings, and as varying the simplification degree of bundled edge graph layouts. Using a brushing-based technique, we further show the applicability of our semantic lens for scenarios requiring a complex selection of the zones of interest. Our technique is simple to implement and provides real-time performance on large datasets. We demonstrate our technique with actual data from air and road traffic control, medical imaging, and software comprehension applications.

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Index Terms:
Semantic lenses, magic lenses, graph bundling, attribute filtering.
Citation:
Christophe Hurter, Alexandru Telea, Ozan Ersoy, "MoleView: An Attribute and Structure-Based Semantic Lens for Large Element-Based Plots," IEEE Transactions on Visualization and Computer Graphics, vol. 17, no. 12, pp. 2600-2609, Dec. 2011, doi:10.1109/TVCG.2011.223
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