SA23C:
Identifying and Mitigating Challenges Related to “Big Data” in Space Science Posters


Submit an Abstract to this Session


Session ID#: 52211

Session Description:
Ever larger volumes of many types of observational data are becoming available to the space science community due to the continual addition of ground-based sensors (e.g. photometers, ionosondes, MST radar, etc.) and the growing popularity of CubeSat constellation concepts.  The intent of this session is to explore various aspects of this topic such as: 1) Applying “Big Data” techniques and architecture to current and future constellations and ground sensor networks, 2) Linking available large ground and/or space-based data sets to their ability to address specific science topics alone or in combination, 3) Present ideas for global coverage metrics for specific types of observations, 4) Address the potential of cumulative errors resulting from ingestion of large volume data from sensor networks including their impact on global models.  We welcome presentations that address any of the four listed areas as well observational/modelling science studies utilizing large and multi-sensor data sets.
Primary Convener:  Rebecca L Bishop, Aerospace Corporation Los Angeles, Los Angeles, CA, United States
Conveners:  Romina Nikoukar, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States, Kshitija Deshpande, Embry-Riddle Aeronautical University, Department of Physical Sciences, Daytona Beach, FL, United States and Cheryl Y Huang, Air Force Research Laboratory, Albuquerque, United States
Primary Liaison:  Rebecca L Bishop, The Aerospace Corporation, Los Angeles, United States
Chairs:  Rebecca L Bishop, The Aerospace Corporation, Los Angeles, United States and Romina Nikoukar, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States
OSPA Liaison:  Kshitija Deshpande, Embry-Riddle Aeronautical University, Daytona Beach, FL, United States

Cross-Listed:
  • IN - Earth and Space Science Informatics
  • SH - SPA-Solar and Heliospheric Physics
  • SM - SPA-Magnetospheric Physics
Index Terms:

1910 Data assimilation, integration and fusion [INFORMATICS]
2494 Instruments and techniques [IONOSPHERE]
2794 Instruments and techniques [MAGNETOSPHERIC PHYSICS]
7999 General or miscellaneous [SPACE WEATHER]

Abstracts Submitted to this Session:

Data analytics and ‘deep time’: Determining statistically reproducible properties of space climate over the last five solar cycles (Invited) (364605)
Sandra C Chapman1, Nicholas W Watkins2,3 and Elizabeth Tindale2, (1)University of Warwick, Centre for Fusion, Space and Astrophysics, Department of Physics, Coventry, CV4, United Kingdom, (2)University of Warwick, Centre for Fusion, Space and Astrophysics, Department of Physics, Coventry, United Kingdom, (3)London School of Economics, Centre for Analysis of Time Series, London, United Kingdom
Using dynamical networks to characterize the full spatio-temporal dynamics and information propagation across 100+ SuperMAG ground based magnetometers (365885)
Sandra C Chapman1, Lauren Orr1 and Jesper W Gjerloev2, (1)University of Warwick, Centre for Fusion, Space and Astrophysics, Department of Physics, Coventry, CV4, United Kingdom, (2)Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States
Pushing the limits of the Empirical Canadian High Arctic Ionospheric Model (E-CHAIM) - How far can empirical models get us? (370913)
David Russel Themens, University of New Brunswick, Fredericton, Canada and Periyadan T Jayachandran, University of New Brunswick, Department of Physics, Fredericton, NB, Canada
Ushering in a new frontier in geospace through Data Science (Invited) (384279)
Ryan Michael McGranaghan1, Anthony J Mannucci2, Chris A Mattmann1 and Brian D Wilson3, (1)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (2)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, (3)NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States
New Perspective of the Ionosphere and Plasmasphere from GNSS Sensor Constellations (439917)
Rebecca L Bishop, Aerospace Corporation Los Angeles, Los Angeles, CA, United States, Ian Hoeck, University of Michigan Ann Arbor, Ann Arbor, MI, United States, Drew L Turner, The Aerospace Corporation, El Segundo, CA, United States, Romina Nikoukar, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States, Cadence Payne, Massachusetts Institute of Technology, Cambridge, MA, United States, Paul R Straus, Aerospace Corp, Los Angeles, CA, United States and Lynette J Gelinas, The Aerospace Corporation, Space Science Applications Laboratory, Los Angeles, United States
Data Mining for Vortices on the Earth's Magnetosphere - Algorithm Application for Detection and Analysis (440035)
Yaireska M Collado-Vega, NASA Goddard Space Flight Center, Moon to Mars Space Weather Analysis Office, Greenbelt, MD, United States, Virginia L. Kalb, NASA Goddard Space Flight Center, Greenbelt, United States, David G Sibeck, NASA Goddard Space Flight Center, NASA, Greenbelt, United States, Kyoung-Joo Hwang, Southwest Research Institute, San Antonio, United States and Lutz Rastaetter, NASA Goddard Space Flight Center, Community Coordinated Modeling Center, Greenbelt, MD, United States

See more of: SPA-Aeronomy