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Thursday, January 17 • 11:00am - 12:30pm
Filling the Earth Science Cookbook: Discovery and registry of Earth Science workflows from public repositories

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Session Abstract:
The majority of scientific programming workflows are developed in isolation by graduate students and postdoctoral researchers. While packages and libraries in R and Python help support the advancement of scientific discovery, researchers are often challenged with combining and analysing data in new ways. Regardless, code use and re-use in the Earth Sciences is often complicated by the fact that few well-developed workflows exist as templates. Most code examples in R packages for example, use well-worn datasets that are not well suited to extrapolation for Earth Science applications. For this reason, the discovery and analysis of existing code resources, such as those undertaken by the FUNding Friday grant, become critical to providing resources to scientific programmers in the Earth Sciences.
This Session will introduce early-career researchers to the principle workflows for sharing code publicly, including discussion of some of the pros and cons of sharing code before it is “good enough”. The session will then provide an overview of work that has been undertaken to analyse a large number of Jupyter notebooks on GitHub, and then provide session members with an opportunity to help build the web of examples for coding resources, discussing what makes code useful as a “cookbook recipe” for Earth Sciences, what particular libraries or data resources are of interest, and how further automation might be undertaken.

Session Notes:

Session Takeaways (post-meeting):
1) Cultural knowledge around data use and storage can impact usage and keep data and use in ‘silos.’
2) There are a lot of people now that are putting notebooks on GitHub that are associated with a specific publication. The people that are doing this well are associating the DOI with the original publication and the people doing really well are setting this up so that the repository also has its own DOI.
3) Earth science data cookbook has an easy form to fill out information for earth science datasets and resources. This is intended to make these resources more accessible and clearly labeled. This thing is not live yet, but users can input keywords etc. available at https://bitly.com/esip2019-cookbook

avatar for Ben Galewsky

Ben Galewsky

Sr. Research Software Engineer, National Center for Supercomputing Applications

Thursday January 17, 2019 11:00am - 12:30pm EST
White Flint