Journal papers and polished computer animations on TV and in the movies make the process of scientific visualization look easy. Just click a few buttons and a beautiful, well-lit, and instantly informative animation pops out. Unfortunately, this is rarely the case. This case study looks at the steps and problems involved in a large data volume visualization of star and emission nebula evolution for a planetarium show at the Hayden Planetarium at the American Museum of Natural History. The visualization involved four simulations, three sites, two supercomputers, 30,000 data files, 116,000 rendered images, 1,152 processors, 8.5 CPU years of rendering, and 7 terabytes of data.
Tree and graph structures are often visualized as 2D linear tree diagrams with labeled dots and connecting lines. But when the data grows beyond several dozen nodes, these diagrams become large and awkward. This article looks at a 3D Cone Tree scheme for visualizing trees and graphs with several thousand nodes. I outline the layout algorithm, show examples, and discuss strengths and weaknesses for the approach.