iSphere: Focus+Context Sphere Visualization for Interactive Large Graph Exploration
Fan Du, Nan Cao, Yu-Ru Lin, Panpan Xu, Hanghang Tong

CHI'17: ACM CHI Conference on Human Factors in Computing Systems
Session: Big Data Intelligent Visualization Systems

Abstract:
Interactive exploration plays a critical role in large graph visualization. Existing techniques, such as zoom-and-pan on a 2D plane and hyperbolic browser facilitate large graph exploration by showing both the details of a focal area and its surrounding context that guides the exploration process. However, existing techniques for large graph exploration are limited in either providing too little context or presenting graphs with too much distortion. In this paper, we propose a novel focus+context technique, iSphere, to address the limitation. iSphere maps a large graph onto a Riemann Sphere that better preserves graph structures and shows greater context information. We conduct extensive experiment studies on different graph exploration tasks under various conditions. The results show that iSphere performs the best in task completion time compared to the baseline techniques in link and path exploration tasks. This research also contributes to understanding large graph exploration on small screens.

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