The ultimate aim of this research and development programme is to optimise visualisation queries across multiple, large data sets derived from motivating applications in astrophysics, planetary-scale oceanographic simulations and human brain mapping. These concepts are coordinated within a data-visualisation pipeline which operates on component data blocks sized to fit within available computing resources. Compute-intensive tasks, such as rendering are executed on available supercomputers, while interacting with desktop GUIs. Parallel efforts, underway in related groups, focus on scalable, rapid iso-contouring algorithms which can extend the more usual paradigms. We aim to coordinate with those efforts to combine the surface and volume visualisation tools.
Research challenges in the science application domain provide the motivation to develop such tools.
Current planetary-scale oceanographic simulations have resolutions limited to 2 deg. latitude and 2 deg. With Teraflop computing resources coming on line, such simulations will be conducted at 10x and 100x resolution, soon yielding multiple sets of 100 Gbyte data output. In mapping the human brain, up to four distinct imaging modalities are used, with datasets already at 10s of GBytes. The immediate research challenge is composite these. Then there is the need to find visualisation metaphors and tools for navigation, feature finding and analysis within these dense, rich volumes.