New papers out about 'Practical Reproducibility in Geo' and the 'Rockerverse'

Two papers have been published this week by o2r team members Daniel and Edzer. They shed a light on the practical aspects of publishing computational geospatial research in a reproducible way and the enourmous number of projects and opportunities of using containers with R to achieve reproducibility. Please share widely!

Practical Reproducibility in Geography and Geosciences

Daniel Nüst and Pebesma, Edzer. 2020. Practical reproducibility in geography and geosciences. Annals of the American Association of Geographers. doi:10.1080/24694452.2020.1806028

The article is not Open Access, but there is an 👉 author accepted manuscript PDF 🔓.

This paper is part of a collection of papers solicited after a workshop early last year. We recommend to look at the other works, as they provide very interesting perspectives that complement the quite technical and practical approach in Daniel and Edzer’s article. Join the discussion on Twitter:

Today is a fun week of announcements. Another paper is out! 🥳 This time about "Practical Reproducibility in Geography and Geosciences" together with @edzerpebesmahttps://t.co/8WgKvuENwx#ReproducibleResearch #Geography #Geosciences pic.twitter.com/4NtPaxPuhF

— Daniel Nüst (@nordholmen) October 14, 2020

The Rockerverse: Packages and Applications for Containerisation with R

Daniel Nüst, Dirk Eddelbuettel, Dom Bennett, Robrecht Cannoodt, Dav Clark, Gergely Daróczi, Mark Edmondson, Colin Fay, Ellis Hughes, Lars Kjeldgaard, Sean Lopp, Ben Marwick, Heather Nolis, Jacqueline Nolis, Hong Ooi, Karthik Ram, Noam Ross, Lori Shepherd, Péter Sólymos, Tyson Lee Swetnam, Nitesh Turaga, Charlotte Van Petegem, Jason Williams, Craig Willis and Nan Xiao. The Rockerverse: Packages and Applications for Containerisation with R. The R Journal (2020), 12:1, pages 437-461. doi:10.32614/RJ-2020-007

This paper was actually inspired by a post in this blog four years ago and turned into a massive collaborative effort which is now published as Open Access in The R Journal. Join the discussion on Twitter:

🥳 A paper is out (or rather the DOI 10.32614/RJ-2020-007 just now resolves..)!
It feels anticlimactic with the preprint out for quite a while, but I'm grateful the #RJournal accepted this great and large collaborative effort:https://t.co/qlCMAU45SV #rstats #Docker @Docker https://t.co/VrO8En1HXx pic.twitter.com/Nr0xJaAeE1

— Daniel Nüst (@nordholmen) October 13, 2020