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, multidimensional 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 project will conduct research that will lead to 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 development of a general toolkit for wavelet based representations of data will have broad impact, allowing 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.
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 for a wide range of scientific and educational fields. However, efficient analysis and visualization is a non trivial problem as the size and complexity of data increases. This research addresses this challenge through a general progressive access, multi scale data representation for efficient handling of structured data sets across a range of science domains. The development is based upon a wavelet enabled 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 through an open source toolkit.
