Beyond the Tabletop: Improving the Spatial Awareness of Multi-Tablet Visualization

In our research on post-tabletop multi-tablet sensemaking, we found that users working with tablets can be equally effective as those working with a large tabletop [26]. However, they also can have difficulties with using multiple tablets in parallel for multiple coordinated views and with assigning content, visualizations, and functionality across devices or team members [18]. We briefly summarize these findings from our user studies and prototypes and propose the potential solution of making post-tabletop multi-tablet visualization systems more spatially-aware [19, 20]. In future, spatially-aware systems could not only detect the spatial locations and configurations of users and devices but also use machine learning approaches to learn which visualizations and functions are most popular or helpful in specific spatial contexts. By this, systems could possibly learn over time and ideally make helpful recommendations for the choice of devices, views, and functionality and how to better manage multi-tablet visualization.