IN23F:
Big Data Analysis and Challenges for Earth and Space Sciences II

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Session ID#: 34963

Session Description:
Big Data poses great challenges for Earth and Space sciences.  It demands for scale computational and infrastructures, support new methods for deriving scientific inferences, and shift towards integrated analytic. NASA’s EOSDIS system manages over 15PB of data while the Solar Dynamics Observatory (SDO) has been generating 2TB of data daily since 2010. The new SWOT mission will generate over 23PB of data in just 3 years. Meanwhile models supporting and employing Earth or planetary observations can produce petascale datasets per run. Many community-driven efforts have emerged, including the NIST Big Data, USGEO DMWG, and NOAA’s Big Data Project, etc. The NASA’s Big Data Task Force has recently completed a series of studies and recommendations for the agency. The traditional methods for science can’t scale to the overwhelming volume of data. The shift toward integrated analytics transforms the existing architectures. Topics include but are not limited to studies, techniques, and applications.
Primary Convener:  Thomas Huang, NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States
Conveners:  Neal E Hurlburt, Lockheed Martin Solar and Astrophysics Laboratory, Palo Alto, CA, United States, Tiffany C Vance, U.S. Integrated Ocean Observing System, Seattle, WA, United States and Brian D Wilson, NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States
Chairs:  Neal E Hurlburt, Lockheed Martin Solar and Astrophysics Laboratory, Palo Alto, CA, United States, Tiffany C Vance, U.S. Integrated Ocean Observing System, Seattle, WA, United States, Brian D Wilson, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States and Thomas Huang, NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States
OSPA Liaison:  Brian D Wilson, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States

Cross-Listed:
  • A - Atmospheric Sciences
  • P - Planetary Sciences
  • SH - SPA-Solar and Heliospheric Physics
  • SM - SPA-Magnetospheric Physics
Index Terms:

1916 Data and information discovery [INFORMATICS]
1920 Emerging informatics technologies [INFORMATICS]
1932 High-performance computing [INFORMATICS]
1998 Workflow [INFORMATICS]

Abstracts Submitted to this Session:

Enabling Data-Driven Methodologies Across the Data Lifecycle and Ecosystem (Invited) (255526)
Richard J Doyle and Daniel Crichton, NASA Jet Propulsion Laboratory, Pasadena, CA, United States
The Data Science Landscape (248039)
Chris Mentzel, Gordon and Betty Moore Foundation, Palo Alto, CA, United States
Statistics and Informatics in Space Astrophysics (258951)
Eric Feigelson, Pennsylvania State University Main Campus, University Park, PA, United States
Design Patterns to Achieve 300x Speedup for Oceanographic Analytics in the Cloud (288065)
Joseph Charles Jacob1, Frank R Greguska III1, Thomas Huang2, Nga Chung1 and Brian D Wilson2, (1)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, (2)NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States
Visual Analytics for Heterogeneous Geoscience Data (287477)
Lina Yu1, Feiyu Zhu1, Michael Lee Rilee2, Yu Pan1, Kwo-Sen Kuo3, Hengle Jiang1 and Hongfeng Yu1, (1)University of Nebraska Lincoln, Lincoln, NE, United States, (2)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (3)Bayesics, LLC, Bowie, MD, United States
Airborne electromagnetics data interactive visualisation and exploratory data analysis using Cloud technologies (238652)
Pavel Golodoniuc, CSIRO, Mineral Resources, Kensington, Western Australia, Australia, Aaron C Davis, CSIRO, Mineral Resources, Kensington, WA, Australia and Jens F Klump, CSIRO Earth Science Resource Engineering, Perth, Australia

See more of: Earth and Space Science Informatics