Data Analysis and Visualization

Generated by a RAL scientist preparing for an unprecedented global weather modeling experiment, the image depicts kinetic energy colored by potential temperature with surface pressure contours below. The CISL Data Analysis and Visualization Lab provides computing resources and consulting expertise to meet the interactive data exploration needs of the entire UCAR scientific community. CISL's state-of-the-art data analysis capabilities play an integral role in the scientific discovery process for groundbreaking research in the geosciences.

The Data Analysis and Visualization Lab enhances scientific workflow by providing UCAR's research community with a highly advanced computing environment tailored for the specialized needs of interactive data post-processing, analysis, and visualization. This evolving environment provides a unified state-of-the-art computing environment comprised of powerful, closely coupled, interactive processing and visualization engines and large-capacity high-performance global file systems. We provide direct support to the research community by developing algorithms for relevant visualization and analysis methods and by producing animations and imagery on behalf of the scientific staff.

The goals of this effort are focused on addressing the growing sizes and complexity of scientific problems being researched at UCAR. We have seen a significant increase in resolution and data set sizes that require not only the enhancement of NCAR computational resource capability and capacity, but that also challenge us to provide advanced services and tools. The Data Analysis Services Group works not only to provide a suitable computational environment but also works directly with users to help develop new techniques and algorithms that allow scientists to push the boundaries of discovery. This work supports NCAR's strategic priorities of "Developing and providing advanced services and tools" and "Maintaining an innovative and creative workplace."

The evolution of this facility from a collection of dedicated standalone resources into a tightly coupled unified computing environment is a multi-year process. In FY 2006 we made great strides in identifying and testing large-scale shared storage solutions and more powerful computational resources. The first enhancement to the visualization capabilities has been completed, and the initial storage and computational enhancements are nearing release to friendly users. The completion of this integration with an additional computational and visualization enhancement next year will offer the data post-processing, analysis, and visualization community an entirely new and well-designed facility to tackle today's larger challenges. The investigation will move forward in FY 2007 with research into higher-performance storage and file system solutions focused on enhancing the performance and capacity of the available resources.

This ongoing service is supported by NSF Core funds including CSL funding.