Clustering algorithms group data objects together based on some notion of distance or similarity. This resembles visual tasks that are easy for humans: spotting a cluster of stars in the night sky or identifying a cluster of old houses within a modern city. The human visual system “has evolved to facilitate quick and considered detection of the visually like and unlike through a wide variety of cues – e.g. location and relative proximity, movement, shape, colour, texture, and matching against predetermined patterns. Consequently, visualization is a natural and powerful resource for cluster analysis; it is especially valuable in identifying unanticipated structure”.