New EarthCube Peer-Reviewed Jupyter Notebooks Now Available
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A novel element of the EarthCube 2020 Annual Conference was a call for notebooks, which led to twelve peer-reviewed Jupyter notebooks that encompass an array of geoscience data tools, software, services, and libraries. Each notebook was reviewed by scholars within the geoscience and cyberinfrastructure community at the EarthCube 2020 Annual Conference.


These notebooks are now available on GitHub for interested researchers to view and execute, and they will soon be published in the Earth and Space Science Open Archive (ESSOAr).

“Open-source technologies such as these Jupyter notebooks allow the EarthCube community to create and share valuable insights with one another,” said Kenton McHenry, associate director for software at the National Center for Supercomputing Applications (NCSA). “We received more than 20 great submissions in response to our Call for Notebooks and selected these twelve for publication.”

“These notebooks represent a new element in the scholarly publishing system: they provide us with a means to easily share tested, user-friendly, and interactive workflows,” said Daniel S. Katz, NCSA chief scientist. “Further Calls for Notebooks are now underway and we encourage the community to participate, as well as to provide feedback about how we can better support notebooks in the peer-review and publishing systems.”

The selected notebooks are now available:

3D volume rendering of geophysical data using the yt platform


Christopher Havlin, Benjamin Holtzman, Kacper Kowalik, Madicken Munk, Sam Walkow, Matthew Turk

Jupyter Notebooks, the PmagPy Software Package and the Magnetics Information Consortium (MagIC) Database

Lisa Tauxe, Rupert Minnett, Nicholas Jarboe, Catherine Constable, Anthony Koppers, Lori Jonestrask, Nicholas Swanson-Hysell

An Interactive GUI for BALTO in a Jupyter notebook


Scott Dale Peckham, Maria Stoica, D. Sarah Stamps, James Gallagher, Nathan Potter, David Fulker

Multi-Cloud workflows with Pangeo and Dask Gateway

Tom Augspurger, Martin Durant, Ryan Abernathey, Joe Hamman

Semantic Annotation of Data using JSON Linked Data


Luigi Marini, Diego Calderon, Praveen Kumar