The rising atmospheric concentration of the greenhouse gas carbon dioxide is a major factor in global warming. The Earth compensates by drawing down carbon dioxide in photosynthesis, yet the yearly variations in carbon dioxide fixation by vegetation, regional flux rates, and anomalies are not well understood. In fact, the global carbon balance sheet shows that the Earth is absorbing more carbon dioxide than all the known carbon sinks. With a data-intensive infrastructure, we can make major progress in the knowledge of global carbon cycle budgets. Reliable predictive models require inventories of standardized methods, color map standards, metadata standards, comparative analyses, and archival storage to enable researchers to reproduce simulation results.
Astronomy offers a different set of challenges.
While astronomers are experienced with high performance computing for numerically intensive applications such as simulating cosmic jets and galaxy collisions, data-intensive computing opens a new universe of possibilities. Large-area digital sky surveys, for example, are a recent development in astronomy that will combine teraflops computing and terabyte storage to store and analyze the results of optical, infrared, and radio surveys. This project also illustrates how data-handling tools can draw a community of researchers closer together. The project will begin with the Digital Palomar Observatory Sky Survey, the 2-Micron All Sky Survey, and the Sloan Digital Sky Survey. As other sky surveys become available, they will be able to take advantage of the architecture and software.