Analysis and visualization of large data sets play an important role in scientific discovery. Efficient, and broadly available tools to accomplish these tasks are crucial fora wide range of scientific and educational fields. However, efficient management of large data for analysis and visualization is a non-trivial problem as the size and complexity of data increases. This proposal addresses this challenge through a general progressive access, multi-scale data representation for efficient handling of these data sets across a range of science domains. The development is based upon a wavelet-based data representation developed by NCAR for geoscience applications. The tools will utilize the very flexible and open source standard NetCDF format, and the methods will be documented as a set of conventions and a toolkit developed that incorporates and integrates these components for dissemination. In addition to an open source toolkit, these tools will be integrated into the VAPOR (NCAR) and STK (CSCI) platforms, thus expanding the capabilities and efficiencies of these platforms for the geo- and bio- sciences communities, respectively. Advancements generated by this project will be openly disseminated to the user community and through an open source toolkit. The development of a general toolkit for wavelet-based representations of data will allow the multi-scale analysis, storage, and visualization for data collected in a wide range of fields and on a multitude of platforms, from high-end computing facilities to laptop computers used by students, field biologists, and others.