Abstract
Nowadays, an abundance of sensors are used to collect very large datasets containing spatial points which can be mined and analysed to extract meaningful patterns and information. This article examines patterns which describe the dispersion of 2D data around a central tendency. Several state of the art patterns for point cluster analysis are presented and critiqued before a new pattern, the oriented spatial box plot, is defined. The oriented spatial box plot extends the classical one-dimensional box plot for summarising and visualising 2D point clusters. The pattern is suitable for detecting outliers and understanding the spatial density of point clusters.
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