For Python and R users: Citing your notebooks in your publication.

Jupyter Notebooks and R Markdown are increasingly being used for documenting research workflows and replicating relevant analyses. This workshop will outline some of the recommendations that are available to help guide authors through the process of sharing their Jupyter Notebooks and R Markdown when publishing their research. Presented at AGU Fall Meeting 2021, Thursday, 16 December 2021, 09:00 - 10:00, Convention Center - AGU Central: Connections and Collaboration Theater (B1), First Floor. This work is supported by Accelerating Open and FAIR Data Practices Across the Earth, Space, and Environmental Sciences: A Pilot with the NSF to Support Public Access to Research Data project funded by the National Science Foundation, Grant 2025364.

Keywords

R Markdown, Jupyter Notebooks

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average