Self-Organising Maps are utilised in many data mining and knowledge management applications. Although various visualisations have been proposed for SOM, these techniques lack in distinguishing between the items mapped to the same unit. Here we present a novel technique for the visualisation of Self-Organising Maps that displays inputs not in the centre of the map units, but shifts them towards the closest neighbours, the degree of the movement depending on the similarity to the neighbours. The night-sky visualisation facilitates betteru nderstanding of the underlying data. We report results from applying our method on two synthetic and a real-life data set.