Before revision:  Here, we introduce a new data visualization and exploration method, TMAP (tree-map), which exploits locality sensitive hashing, Kruskal's minimum-spanning-tree algorithm, and a multilevel multipole-based graph layout algorithm to represent large and high dimensional data sets as a tree structure, which is readily understandable and explorable.
After revision: The chemical sciences are producing an unprecedented amount of large, high-dimensional data sets containing chemical structures and associated properties. However, there are currently no algorithms to visualize such data while preserving both global and local features with a sufficient level of detail to allow for human inspection and interpretation. Here, we introduce a new data visualization and exploration method, TMAP (tree-map), which exploits locality sensitive hashing, Kruskal's minimum-spanning-tree algorithm, and a multilevel multipole-based graph layout algorithm to represent large and high dimensional data sets as a tree structure, which is readily understandable and explorable.