The objective of this session is to share innovative concepts, emerging solutions, and applications of Cloud Computing for Geoscience Analytics. The elasticity of Cloud Computing enables us to horizontally scale of big data analytic solutions to be able to handle more data at the same time. Topics include demonstration, studies, methods, solutions and/or architectural discussion on Architecture for big data analytic Application of open source technologies Automated techniques and solutions for data analysis Browser-based data analytics and visualization Real time decision support Invited speakers Mike Little - NASA ESTO, AIST Managed Cloud Environment Brett McLaughlin - ESDIS/N-GAP Brian Wilson/Thomas Huang - JPL - NEXUS - Deep Data Analytic Platform Fei Hu/Zhenlong Li- GMU - A High Performance Framework for Big Climate Data Analytics Hook Hua - JPL - Machine Learning applied on SAR processing
