The sampling lens: Making sense of saturated visualisations

Information visualisation systems frequently have to deal with large amounts of data and this often leads to saturated areas in the display with considerable overplotting. This paper introduces the Sampling Lens, a novel tool that utilizes random sampling to reduce the clutter within a moveable region, thus allowing the user to uncover any potentially interesting patterns and trends in the data while still being able to view the sample in context. We demonstrate the versatility of the tool by adding sampling lenses to scatter and parallel co-ordinate visualisations. We also consider some implementation issues and present initial user evaluation results.