IN13E:
Intelligent Systems for Geosciences: Accelerating Discovery and Building Community I: Lightning

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Possible Alternate Format: If this session is allocated an oral session, the convener can choose to have lightning style presentations that are quicker and more focused than a traditional session. Learn more


Session ID#: 33653

Session Description:
Intelligent Systems for Geosciences (IS-GEO) encompasses an emerging community of interdisciplinary researchers producing fundamental new capabilities for overcoming common challenges, while redefining the frontiers of discovery across fields and disciplines. Developments in machine learning, information integration, robotics, adaptive sensors, intelligent interfaces, and artificial intelligence, including knowledge extraction and representation, are thus advancing and transforming geoscience research. This session seeks approaches for collecting, integrating and visualizing heterogeneous data, in addition to ontological reasoning with scientific metadata, mathematical modeling, and knowledge discovery using machine learning and data mining methods. Participants should also consider potential uses for cyberinfrastructures and intelligent assistants that make scientists more efficient and facilitate information sharing, collaborative workflow design and management to support data analytics. We also welcome submissions describing successes, challenges, and lessons learned from the ongoing exchange of knowledge and collaborations across these disciplines.
Primary Convener:  Mariana Güereque, University of Texas at El Paso, El Paso, TX, United States
Conveners:  Sai Ravela, Massachusetts Institute of Technology, Department of Earth, Atmospheric and Planetary Sciences, Cambridge, United States, Anuj Karpatne, University of Minnesota Twin Cities, Department of Computer Science and Engineering, Minneapolis, MN, United States and Michael J Friedel, GNS Science, Lower Hutt, New Zealand
Chairs:  Sai Ravela, Massachusetts Institute of Technology, Department of Earth, Atmospheric and Planetary Sciences, Cambridge, United States and Daniel Garijo, University of Southern California, Information Sciences Institute, Los Angeles, CA, United States
OSPA Liaison:  Mariana Güereque, University of Texas at El Paso, El Paso, TX, United States

Cross-Listed:
  • A - Atmospheric Sciences
  • GC - Global Environmental Change
  • PA - Public Affairs
  • SI - Societal Impacts and Policy Sciences
Index Terms:

1920 Emerging informatics technologies [INFORMATICS]
1968 Scientific reasoning/inference [INFORMATICS]
1976 Software tools and services [INFORMATICS]
1999 General or miscellaneous [INFORMATICS]

Abstracts Submitted to this Session:

ClimateNet: A Machine Learning dataset for Climate Science Research (Invited) (214442)
Mr Prabhat1, Jim Biard2, Sangram Ganguly3, Sasha Ames4, Karthik Kashinath5, Soo Kyung Kim6, Samira Kahou7, Tegan Maharaj8, Christopher Beckham8, Prof. Travis Allen O'Brien9, Michael F Wehner10, Dean Norman Williams4, Kenneth Kunkel11 and William Drew Collins12, (1)University of California Berkeley, Earth and Planetary Sciences, Berkeley, CA, United States, (2)Cooperative Institute for Climate and Satellite North Carolina State, Asheville, NC, United States, (3)Bay Area Environmental Research Institute Moffett Field, Moffett Field, CA, United States, (4)Lawrence Livermore National Laboratory, Livermore, CA, United States, (5)NVIDIA Corporation, Santa Clara, CA, United States, (6)LLNL, Livermore, United States, (7)Microsoft Research, Montreal, Canada, (8)U. Montreal, Montreal, Canada, (9)Lawrence Berkeley National Lab, Climate & Ecosystem Sciences Division, Berkeley, United States, (10)Applied Mathematics and Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, United States, (11)CICS-NC/NCDC, Asheville, NC, United States, (12)Berkeley Lab and UC Berkeley, Berkeley, United States
Pacific Research Platform - Creation of a West Coast Big Data Freeway System Applied to the CONNected objECT (CONNECT) Data Mining Framework for Earth Science Knowledge Discovery (292043)
Scott L Sellars1, Phu Nguyen2, Joulien Tatar3, John Graham4, Brian Kawzenuk5, Thomas DeFanti4, Larry Smarr4, Soroosh Sorooshian6 and Test 7, (1)University of California San Diego, San Diego, CA, United States, (2)University of California, Irvine, Department of Civil and Environmental Engineering, Irvine, United States, (3)Office of Information technology, University of California, Irvine, Irvine, United States, (4)University of California San Diego, La Jolla, CA, United States, (5)University of California San Diego, San Diego, United States, (6)UC Irvine, Irvine, CA, United States, (7)Scripps Institution of Oceanography, Center for Western Weather and Water Extremes (CW3E), La Jolla, CA, United States
Building Daily 30-meter Spatial Resolution Maps of Surface Water Bodies from MODIS Data Using a Novel Technique for Transferring Information Across Space and Time (296493)
Ankush Khandelwal, University of Minnesota Twin Cities, Minneapolis, MN, United States, Anuj Karpatne, University of Minnesota Twin Cities, Department of Computer Science and Engineering, Minneapolis, MN, United States and Vipin Kumar, University of Minnesota Twin Cities, Department of Computer Science/Engineering, Minneapolis, United States
OntoSoft: A Software Registry for Geosciences (222842)
Daniel Garijo and Yolanda Gil, University of Southern California, Information Sciences Institute, Los Angeles, CA, United States
Flood AI: An Intelligent Systems for Discovery and Communication of Disaster Knowledge (280553)
Ibrahim Demir, Tulane University, River-Coastal Science and Engineering, New Orleans, United States and Yusuf Sermet, IIHR—Hydroscience and Engineering, Iowa City, IA, United States
Middle Rio Grande Water Sustainability in Extreme Drought: Using Provenance to Trace Modeling Scenarios Selected by Users (255293)
Deana D Pennington, Luis Garnica Chavira and Natalia Villanueva-Rosales, University of Texas at El Paso, El Paso, TX, United States
Advances and Directions for the Intelligent Systems for Geosciences Research Community: Updates and Opportunities from the NSF EarthCube IS-GEO RCN (288051)
Suzanne A Pierce, Texas Advanced Computing Center, Austin, TX, United States

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