IN12A:
Big Data Analytics I

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Session ID#: 16848

Session Description:
Big Data pose great challenges for Earth and Space sciences. Cloud Computing emerged as a promissing solution for supporting Big Data analytics in areas such as climate science, ocean science, atmospheric science, planetary science, and other geoscience domains for model simultion, data management, information mining, decision support, and visualization. This session is to capture the latest on applying Cloud Computing for Big Data Analytical problems in all Earth and space domains. Topics include demonstration, studies, methods, solutions and solution discussion on

  • Solutions for big data analytics
  • Big data mining
  • Application of open source technologies
  • Automated techniques for data analysis
  • Browser-based data analytics and visualization
  • Real time decision support

Contributions that fuse participatory social learning into the Geoscience R&D processes are also welcome.

Primary Convener:  Thomas Huang, NASA Jet Propulsion Laboratory, Pasadena, CA, United States
Conveners:  Chaowei Phil Yang, George Mason University Fairfax, Geography and Geoinformation Science, Fairfax, VA, United States, Tiffany C Vance, U.S. Integrated Ocean Observing System, Seattle, WA, United States and Christopher Lynnes, NASA Goddard Space Flight Center, Greenbelt, MD, United States
Chairs:  Christopher Lynnes, NASA Goddard Space Flight Center, Greenbelt, MD, United States, Chaowei Phil Yang, George Mason University Fairfax, Geography and Geoinformation Science, Fairfax, VA, United States and Thomas Huang, NASA Jet Propulsion Laboratory, Pasadena, CA, United States
OSPA Liaison:  Chaowei Phil Yang, George Mason University Fairfax, Geography and Geoinformation Science, Fairfax, VA, United States
Index Terms:

1914 Data mining [INFORMATICS]
1918 Decision analysis [INFORMATICS]
1926 Geospatial [INFORMATICS]
1976 Software tools and services [INFORMATICS]

Abstracts Submitted to this Session:

Feature Geo Analytics and Big Data Processing: Hybrid Approaches for Earth Science and Real-Time Decision Support (Invited) (119312)
Dawn J Wright, Mansour Raad, Erik Hoel, Michael Park, Adam Mollenkopf and Ricardo Trujillo, Environmental Systems Research Institute, Redlands, CA, United States
Sharing Planetary-Scale Data in the Cloud (Invited) (120851)
Joe Flasher, Amazon Web Services, Inc, Washington, DC, United States and Jed Sundwall, Amazon Web Services, Global Open Data Lead, Seattle, WA, United States
Using Browser Notebooks to Analyse Big Atmospheric Data-sets in the Cloud (156818)
Niall Robinson1, Jacob Tomlinson1, Alberto Arribas2, Rachel Prudden3 and Informatics Lab, (1)Met Office, Informatics Lab, Exeter, United Kingdom, (2)Met Office Hadley center for Climate Change, Exeter, United Kingdom, (3)Met Office, Informatics lab, Exeter, United Kingdom
OceanXtremes: Scalable Anomaly Detection in Oceanographic Time-Series (183732)
Brian D Wilson1, Edward M Armstrong2, Toshio Michael Chin1, Kevin Michael Gill3, Frank R Greguska III1, Thomas Huang2, Joseph Charles Jacob2 and Nga Chung2, (1)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, (2)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (3)Jet Propulsion Laboratory, Pasadena, CA, United States
Oceans 2.0: Interactive tools for the Visualization of Multi-dimensional Ocean Sensor Data (186768)
Ben Biffard, Mitozcelle Valenzuela, Patrick Conley, Melissa MacArthur, Stephen Tredger, Eric Guillemot and Benoit Pirenne, Ocean Networks Canada, Victoria, BC, Canada
Topological Methods for Pattern Detection in Climate Data (190528)
Grzegorz Muszynski, British Antarctic Survey, Cambridge, United Kingdom, Vitaliy Kurlin, University of Liverpool, Department of Computer Science, Liverpool, United Kingdom, Dmitriy Morozov, Lawrence Berkeley National Laboratory, Berkeley, United States and Mr Prabhat, Lawrence Berkeley National Laboratory, National Energy Research Scientific Computing Center (NERSC), Berkeley, CA, United States
Large Scale EOF Analysis of Climate Data (192973)
Alex Gittens1, Karthik Kashinath2, Nicholas R Cavanaugh3, Mr Prabhat3 and Michael Mahoney4, (1)University of California Berkeley, Statistics, Berkeley, CA, United States, (2)NVIDIA Corporation, Santa Clara, CA, United States, (3)Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (4)University of California Berkeley, Department of Statistics, Berkeley, United States

See more of: Earth and Space Science Informatics