The Impact of Interactivity on Comprehending 2D and 3D Visualizations of Movement Data

Abstract

GPS, RFID, and other technologies have made it increasingly common to track the positions of people and objects over time as they move through two-dimensional spaces. Visualizing such spatio-temporal movement data is challenging because each person or object involves three variables (two spatial variables as a function of the time variable), and simply plotting the data on a 2D geographic map can result in overplotting and occlusion that hides details. This also makes it difficult to understand correlations between space and time. Software such as GeoTime can display such data with a three-dimensional visualization, where the 3rd dimension is used for time. This allows for the disambiguation of spatially overlapping trajectories, and in theory, should make the data clearer. However, previous experimental comparisons of 2D and 3D visualizations have so far found little advantage in 3D visualizations, possibly due to the increased complexity of navigating and understanding a 3D view. We present a new controlled experimental comparison of 2D and 3D visualizations, involving commonly performed tasks that have not been tested before, and find advantages in 3D visualizations for more complex tasks. In particular, we tease out the effects of various basic interactions and find that the 2D view relies significantly on "scrubbing" the timeline, whereas the 3D view relies mainly on 3D camera navigation. Our work helps to improve understanding of 2D and 3D visualizations of spatio-temporal data, particularly with respect to interactivity.

ON THE USABILITY AND USEFULNESS OF 3D (GEO)VISUALIZATIONS – A FOCUS ON VIRTUAL REALITY ENVIRONMENTS

“…When we consider an empirical result, we should pay attention to what type of 3D has been tested. Furthermore, as in all visualizations, related design choices (Oh et al, 2011) such as interactivity (e.g., Amini et al, 2014), use of color (e.g., Brychtová & Çöltekin, 2016), or degree of realism e.g., phototextures, virtual environments (e.g., Boér et al, 2013;Smallman & Cook, 2011).…”

Improving Spatial Awareness for Human Trajectory Visualization in Space-Time Cubes

“…Moreover, users have shown a significantly higher preference towards a variant that combines 2D and 3D views. This further supports the importance of studying the advantages of combining both types of techniques [1,7], which may, in turn, be useful for developers and analysts needing to decide which features to use on a given technique for trajectory visualization. Nevertheless, further studies should still be conducted.…”

“…STCs represent both spatial and temporal information within a cube, where the x-y axes usually represent spatial information (e.g., latitude/longitude), while the z-axis represents time [8]. Typically, time increases along the z-axis, implying that the higher the information is within the cube, the most recent it is [10,1]. Similarly to 2D maps, trajectories can be displayed as a sequence of symbols, graphically encoded to represent variations in the thematic attributes.…”

Visualizing Personal Progress in Participatory Sports Cycling Events

“…Cheap wearable RFID devices allow live checkpoint timing of runners, cyclists and swimmers in multi-stage races. Equally, new approaches to visualizing the data generated by these sensors has provided opportunities to make meaningful patterns of space-time trajectories salient 1 . Drawing on my own experience of participating in long distance cycling events, in this paper I explore some of the design choices that allow individuals to visualize their own progress in mass participation sporting events.…”