We present a novel visualization methodology for graphs and high-dimensional data which combines the neighborhood preservation characteristics of the minimum spanning trees, with the grouping properties of dendrograms. We call the method 'minimum spanning dendrogram'. We highlight the ability of the mapping to accurately capture both neighborhood and cluster structures. The technique accommodates the interactive cluster formation at progressively more granular levels, allowing the user to explore data relationships at different resolutions. We also compare our work with other visualization methodologies, such as ISOMAP, and highlight the distinct merits of our approach. © 2010 IEEE.