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Science Storms the Cloud
  • +5
  • Chelle Leigh Gentemann,
  • Chris Holdgraf,
  • Ryan Abernathey,
  • Daniel Crichton,
  • James Colliander,
  • Edward Joseph Kearns,
  • Yuvi Panda,
  • Richard P. Signell
Chelle Leigh Gentemann
Farallon Institute, Farallon Institute, Farallon Institute, Farallon Institute

Corresponding Author:[email protected]

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Chris Holdgraf
2i2c, 2i2c, 2i2c, 2i2c
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Ryan Abernathey
Columbia University, Columbia University, Columbia University, Columbia University
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Daniel Crichton
Jet Propulsion Laboratory, Jet Propulsion Laboratory, Jet Propulsion Laboratory, NASA, Jet Propulsion Laboratory, NASA
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James Colliander
2i2c, 2i2c, 2i2c, 2i2c
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Edward Joseph Kearns
First Street Foundation, First Street Foundation, First Street Foundation, First Street Foundation
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Yuvi Panda
2i2c, 2i2c, 2i2c, 2i2c
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Richard P. Signell
United States Geological Survey, United States Geological Survey, United States Geological Survey, United States Geological Survey
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Abstract

The core tools of science (data, software, and computers) are undergoing a rapid and historic evolution, changing what questions scientists ask and how they find answers. Earth science data are being transformed into new formats optimized for cloud storage that enable rapid analysis of multi-petabyte datasets. Datasets are moving from archive centers to vast cloud data storage, adjacent to massive server farms. Open source cloud-based data science platforms, accessed through a web-browser window, are enabling advanced, collaborative, interdisciplinary science to be performed wherever scientists can connect to the internet. Specialized software and hardware for machine learning and artificial intelligence (AI/ML) are being integrated into data science platforms, making them more accessible to average scientists. Increasing amounts of data and computational power in the cloud are unlocking new approaches for data-driven discovery. For the first time, it is truly feasible for scientists to bring their analysis to data in the cloud without specialized cloud computing knowledge. This shift in paradigm has the potential to lower the threshold for entry, expand the science community, and increase opportunities for collaboration while promoting scientific innovation, transparency, and reproducibility. Yet, we have all witnessed promising new tools which seem harmless and beneficial at the outset become damaging or limiting. What do we need to consider as this new way of doing science is evolving?
Jun 2021Published in AGU Advances volume 2 issue 2. 10.1029/2020AV000354