CHI '86 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Pad: an alternative approach to the computer interface
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
Space-scale diagrams: understanding multiscale interfaces
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Reading of electronic documents: the usability of linear, fisheye, and overview+detail interfaces
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Improving focus targeting in interactive fisheye views
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Graph Visualization and Navigation in Information Visualization: A Survey
IEEE Transactions on Visualization and Computer Graphics
Halo: a technique for visualizing off-screen objects
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
SpaceTree: Supporting Exploration in Large Node Link Tree, Design Evolution and Empirical Evaluation
INFOVIS '02 Proceedings of the IEEE Symposium on Information Visualization (InfoVis'02)
Toolkit Design for Interactive Structured Graphics
IEEE Transactions on Software Engineering
The vacuum: facilitating the manipulation of distant objects
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Topological Fisheye Views for Visualizing Large Graphs
IEEE Transactions on Visualization and Computer Graphics
Fisheye Tree Views and Lenses for Graph Visualization
IV '06 Proceedings of the conference on Information Visualization
Comparing visualizations for tracking off-screen moving targets
CHI '07 Extended Abstracts on Human Factors in Computing Systems
Wedge: clutter-free visualization of off-screen locations
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Melange: space folding for multi-focus interaction
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Sigma lenses: focus-context transitions combining space, time and translucence
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Topology-aware navigation in large networks
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
“Search, Show Context, Expand on Demand”: Supporting Large Graph Exploration with Degree-of-Interest
IEEE Transactions on Visualization and Computer Graphics
Route Visualization Using Detail Lenses
IEEE Transactions on Visualization and Computer Graphics
A comparison of navigation techniques across different types of off-screen navigation tasks
INTERACT'07 Proceedings of the 11th IFIP TC 13 international conference on Human-computer interaction - Volume Part II
Off-screen visualization techniques for class diagrams
Proceedings of the 5th international symposium on Software visualization
Smooth and efficient zooming and panning
INFOVIS'03 Proceedings of the Ninth annual IEEE conference on Information visualization
EdgeLens: an interactive method for managing edge congestion in graphs
INFOVIS'03 Proceedings of the Ninth annual IEEE conference on Information visualization
GravNav: using a gravity model for multi-scale navigation
Proceedings of the International Working Conference on Advanced Visual Interfaces
Comparison of off-screen visualization techniques with representation of relevance on mobile devices
BCS-HCI '13 Proceedings of the 27th International BCS Human Computer Interaction Conference
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Maintaining both overview and detail while navigating in graphs, such as road networks, airline route maps, or social networks, is difficult, especially when targets of interest are located far apart. We present a navigation technique called Dynamic Insets that provides context awareness for graph navigation. Dynamic insets utilize the topological structure of the network to draw a visual inset for off-screen nodes that shows a portion of the surrounding area for links leaving the edge of the screen. We implement dynamic insets for general graph navigation as well as geographical maps. We also present results from a set of user studies that show that our technique is more efficient than most of the existing techniques for graph navigation in different networks.