PartyVote is a democratic music jukebox designed to give all participants an equal influence on the music played at social gatherings or parties. PartyVote is designed to provide appropriate music in established social groups with minimal user interventions and no pre-existing user profiles. The visualization uses dimensionality reduction to show song similarity and overlays information about how votes affect the music played. Visualizing voting decisions allows users to link music selections with individuals, providing social awareness. Traditional group norms can subsequently be leveraged to maintain fair system use and empower users.

Spatializations represent non-spatial data using a spatial layout similar to a map. We present an experiment comparing different visual representations of spatialized data, to determine which representations are best for a non-trivial search and point estimation task. Primarily, we compare point-based displays to 2D and 3D information landscapes. We also compare a colour (hue) scale to a grey (lightness) scale. For the task we studied, point-based spatializations were far superior to landscapes, and 2D landscapes were superior to 3D landscapes. Little or no benefit was found for redundantly encoding data using colour or greyscale combined with landscape height. 3D landscapes with no colour scale (height-only) were particularly slow and inaccurate. A colour scale was found to be better than a greyscale for all display types, but a greyscale was helpful compared to height-only. These results suggest that point-based spatializations should be chosen over landscape representations, at least for tasks involving only point data itself rather than derived information about the data space.