Evaluation of 1D Selection Techniques for Mobile Visualizations

BSTRACT In spite of growing demand for mobile data visualization, few design guidelines exist to address its many challenges including small screens and low touch interaction precision. Both of these challenges can restrict the number of data points a user can reliably select and view in more detail, which is a core requirement for interactive data visualization. In this study, we present a comparison of the conventional tap technique for selection with three variations including visual feedback to understand which interaction technique allows for optimal selection accuracy. Based on the results of the user study, we provide actionable solutions to improve interaction design for mobile visualizations. We find that visual feedback, such as selection with a handle, improves selection accuracy three- to fourfold compared to tap selection. With a 75% accuracy, users could select a target item among 176 items total using the handle, but only from 60 items using tap. On the other hand, techniques with visual feedback took about twice as long per selection when compared to tap. We conclude designers should use selection techniques with visual feedback when the data density is high and improved selection precision is required for a visualization.