May 31 – June 2 Big Data and The Earth Sciences: Grand Challenges Workshop

April 17, 2017

Abstract deadline extended to April 21st

The Center for Western Weather and Water Extremes (CW3E) of UC San Diego’s Scripps Institution of Oceanography and the Pacific Research Platform (PRP) is excited to announce the organization of a workshop focused on earth sciences and information technology at the University of California San Diego. The workshop is a three-day Grand Challenges workshop May 31 to June 2 in La Jolla, Calif., on the topic of “Big Data and the Earth Sciences”.

CW3E is focused on advancing science and technology to support the unique information needs related to western U.S. extreme weather and water events, such as California’s recent flooding and multi-year drought and associated potential for subseasonal-to-seasonal forecasting. PRP is a consortium of universities in the western U.S. that is building a “science-driven, high-capacity data-centric freeway system on a large regional scale.” Funded by the National Science Foundation, PRP is based in the California Institute for Telecommunications and Information Technology (Calit2), a partnership of UC San Diego and UC Irvine. The workshop will take place in UC San Diego’s Atkinson Hall, headquarters of the Qualcomm Institute (the UCSD division of Calit2).

The goal of the The Big Data and Earth Sciences: Grand Challenges Workshop is to bring thought leaders in Big Data and Earth Sciences together for a three day, intensive workshop to discuss what is needed to advance our understanding and predictability of the Earth systems and to highlight key technological advances and methods that are readily available or in the final stages of development.

Sessions will include:

  • Big data collaborations;
  • Big data research platforms, networks, technologies and visualization;
  • Big data and predictability challenges in earth science data;
  • Pattern detection, segmentation and object recognition for earth sciences;
  • Structuring unstructured data in the earth sciences; as well as
  • Data mining and discovery, machine learning and predictive modeling.

For more information please visit:


Official workshop website:

Please send abstracts to

Abstracts are restricted to one page. Please include the abstract title, authors’ names and affiliations. A word document or .pdf is preferred.