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New EarthCube Peer-Reviewed Jupyter Notebooks Now Available

Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages.

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.”

The selected notebooks are now available as follows (click on each title for access):

3D volume rendering of geophysical data using the yt platform – Christopher Havlin, Benjamin Holtzman, Kacper Kowalik, Madicken Munk, Sam Walkow, Matthew Turk

An Interactive GUI for BALTO in a Jupyter notebook – Scott Dale Peckham, Maria Stoica, D. Sarah Stamps, James Gallagher, Nathan Potter, David Fulker

Argovis API exposed in a Python Jupyter notebook: an easy access to Argo profiles, weather events, and gridded products – Tyler Tucker, Donata Giglio, Megan Scanderbeg

Big Arrays, Fast: Profiling Cloud Storage Read Throughput – Ryan Abernathey

CMIP6 without the interpolation: Grid-native analysis with Pangeo in the cloud – Julius Busecke, Ryan Abernathey

Intake / Pangeo Catalog: Making It Easier To Consume Earth’s Climate and Weather Data – Anderson Banihirwe, Charles Blackmon-Luca, Ryan Abernathey, Joseph Hamman

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

Multi-Cloud workflows with Pangeo and Dask Gateway – Tom Augspurger, Martin Durant, Ryan Abernathey, Joe Hamman

Processing digital elevation data for deep learning models using Keras Spatial – Aiman Soliman and Jeffrey Terstriep

Scikit-downscale: an open source Python package for scalable climate downscaling – Joseph Hamman and Julia Kent

Semantic Annotation of Data using JSON Linked Data – Luigi Marini, Diego Calderon, Praveen Kumar

Vertical Regridding and Remapping – C. Spencer Jones, Julius Busecke, Takaya Uchida, Ryan Abernathey

“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.”

-Kimberly Mann Bruch

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