Wrote a ms citing @benmarwick 's #rstats reproducibility paper, so seems like a good time to re-tweet it. "Packaging data analytical work reproducibly using R (and friends)" https://t.co/EgMukdESFb
@noamross @mauro_lepore @JennyBryan @hadleywickham @rOpenSci The recent follow-up to the rrrpkg essay is https://t.co/Qd8g91OhjR with @cboettig & @lincolnmullen. But as @noamross notes, there's now a rich diversity of approaches to organizing research projects using #rstats for reproducibility, each suiting different types of research.
@tjowens @Ted_Underwood Looks like only one of those links came through. Here is the one on reproducible research, by @benmarwick, @cboettig, and me. https://t.co/SXGbXynCMv
@tjowens @Ted_Underwood On the specific details, here are articles about data sharing and reproducible research. While both are aimed at data scientists, I don't think there would be any meaningful difference for humanities data.
https://t.co/SXGbXynCMv
https://t.co/0rlcSctn5q
fabulous paper on organizing "Research compendia" using R packages "Packaging data analytical work reproducibly using R (and friends)" https://t.co/fdRUuoQ3P2 via @PeerJPreprints
@neuromusic We have a new paper that surveys some current practices of #rstats users on GitHub and how they organise research projects: https://t.co/TfoSJISyAY pre-print: https://t.co/C029piyzXm