Navigating in large geometric spaces---such as maps, social networks, or long documents---typically require a sequence of pan and zoom actions. However, this strategy is often ineffective and cumbersome, especially when trying to study and compare several distant objects. We propose a new distortion technique that folds the intervening space to guarantee visibility of multiple focus regions. The folds themselves show contextual information and support unfolding and paging interactions. We conducted a study comparing the space-folding technique to existing approaches, and found that participants performed significantly better with the new technique. We also describe how to implement this distortion technique, and give an in-depth case study on how to apply it to the visualization of large-scale 1D time-series data.

Interaction and navigation in large geometric spaces typically require a sequence of pan and zoom actions. This strategy is often ineffective and cumbersome, especially when trying to study several distant objects. We propose a new distortion technique that folds the intervening space to guarantee visibility of multiple focus regions. The folds themselves show contextual information and support unfolding and paging interactions. Compared to previous work, our method provides more context and distance awareness. We conducted a study comparing the space-folding technique to existing approaches, and found that participants performed significantly better with the new technique.