Advances in digital imaging methods are revolutionizing a wide range of scientific disciplines by facilitating the acquisition of huge amounts of data that allow the visualization and analysis of complex, multi-dimensional images. Concurrently, modern computing technologies enable numerical modeling of a broad gamut of scientific phenomena, resulting in vast quantities of numerical data, which are just the starting point for the scientific exploration that modern computational and visualization methods enable. This is particularly true in the biological and geosciences, two seemingly very different disciplines. These capabilities come with a cost: increasing data size and complexity require more sophisticated methods for data analysis and visualization. This proposal, titled SI2-SSE: Wavelet-enabled progressive data Access and Storage Protocol (WASP), provides a common software framework for supporting a multi-scale progressive data refinement method based upon the representation of the data as a wavelet expansion, and enabling interactive exploration of large data sets for the bio- and geoscience communities. The University of California, San Diego, Center for Scientific Computation in Imaging (CSCI), in partnership with the National Center for Atmospheric Research (NCAR) will develop an open source toolkit for progressive data access and management of wavelet-encoded data.