The combination of high throughput computation and machine learning has led to a new
paradigm in materials design by allowing for the direct screening of vast portions of
structural, chemical, and property spaces. The use of these powerful techniques leads to the
generation of enormous amounts of data, which in turn calls for new techniques to efficiently
explore and visualize the materials space to help identify underlying patterns. In this work,
we develop a unified framework to hierarchically visualize the compositional and structural …