2.2 UV-CDAT Re-sharable Analyses and Diagnostics (U-ReAD): a framework to create and share UV-CDAT plugins

Monday, 7 January 2013: 4:30 PM
Room 12B (Austin Convention Center)
Charles Doutriaux, LLNL, Livermore, CA; and A. Chaudhary, H. Krishnan, K. Marvel, T. P. Maxwell, J. Painter, G. L. Potter, and D. Williams

Some of today's greatest challenges to the scientific community are “big data”, “reproducibility/transparency” and “code sharing”. The state-of-the-art Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT) environment addresses the first two issues with new visualizations and techniques to address big data and provenance. This talk addresses code re-sharing and re-distribution by introducing the UV-CDAT Re-sharable Analyses and Diagnoses (U-ReAD). U-ReAD will offer scientists a complete set of tools (framework) based on the Python programming language along with a code repository. U-ReAD's goal is to use structured documentation to help build the interface between UV-CDAT and a diagnostic, with few or no changes to the original code. This framework will allow scientists to quickly and seamlessly re-implement their diagnostics so that they will fit perfectly into the UV-CDAT environment. As a result U-ReAD-enhanced diagnostics will be automatically provenance-enabled, making it easy to reproduce any set of results exactly and transparently, a crucial functionality considering today's increased scrutiny toward scientific results. This talk aims to demonstrate how easy it can be to plug any diagnostic into UV-CDAT using U-ReAD. We will show how few changes are necessary to create these plugins and how “augmented” the diagnostics are in return. U-ReAD's developers also hope to create a central repository of U-ReAD-enhanced tools so that scientists can easily share their tools. This talk will show what is in store along these lines.
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