The COVID-19 pandemic has dramatically impacted all of our lives in a very short period of time.Spring and summer are usually very busy as students prepare to go the field to engage in various data collection efforts.The pandemic has also disrupted these carefully planned activities as travel is suspended and local and remote field stations have closed indefinitely.A lost field season can be a major setback for a dissertation timeline and

Our website is based on Markdown content rendered with Hugo.Markdown content is in some cases knit from R Markdown, but with less functionality than if one rendered R Markdown to html as in the blogdown default.In particular, we cannot use the usual BibTex + CSL + Pandoc-citeproc dance to handle a bibliography.Thankfully, using the rOpenSci package RefManageR, we can still make our own bibliography from a BibTeX file without formatting

Thanks to a quite overdue update of Hugo on our build system ¹ , our website can now harness the full power of Hugo code highlighting for Markdown-based content.What’s code highlighting apart from the reason behind a tongue-twister in this post title?In this post we shall explain how Hugo’s code highlighter, Chroma, helps you prettify your code (i.e. syntax highlighting ), and accentuate parts of your code (i.e. line

Whilst working on the blog guide, Stefanie Butland and I consolidated knowledge we had already gained, but it was also the opportunity to up our Rmd/Hugo technical game.Our website uses Hugo but not blogdown ¹ to render posts: every post is based on an .md file that is either written directly or knit from an .Rmd file.We wanted to provide clear guidance for both options, and to stick to the well-documented Hugo way of e.g. inserting

The R language has become very popular among scientists and analystsbecause it enables the rapid development of software and empowersscientific investigation. However, regardless of the language used,data analysis is usually complicated. Because of various projectcomplexities and time constraints, analytical software often reflectsthese challenges. “What did I measure? What analyses are relevant tothe study? Do I need to transform the data?

🔗rOpenSci HQ The recording, collaborative notes and links to community discussion and resources are up for our latest Community Call on Maintaining an R package. Panel moderated by Julia Silge included Elin Waring, Erin Grand, Leonardo Collado-Torres, and Scott Chamberlain.   🔗Software Peer Review 1 staff-contributed package passed software peer review. parzer - Parse messy geographic coordinates. Author: Scott Chamberlain;

One of the first things I took on when I started at the Cornell Lab of Ornithology was creating the auk R package for accessing eBird data. The entire eBird dataset can be downloaded as a massive text file, called the eBird Basic Dataset (EBD), and auk pulls out manageable chunks of the dataset based on various spatial, temporal, or taxonomic filters.

rOpenSci Software Peer Review’s guidance has been compiled in an online book for more than one year now. We’ve just released its fourth version.To find out what’s new in our dev guide 0.4.0, you can read the changelog,or this blog post for more digested information. 🔗Policy and governance changes Some aspects of the software review process changed.

After soliciting, reviewing, and publishing over 100 blog posts and tech notes by rOpenSci community members, we have created the rOpenSci Blog Guide for Authors and Editors to address many frequently asked questions and frequently given suggestions. Technically, we structured the content as a bookdown gitbook.

parzer is a new package for handling messy geographic coordinates.The first version is now on CRAN, with binaries coming soon hopefully (seenote about installation below). The package recently completed rOpenScireview. 🔗parzer motivation The idea for this package started with a tweet from Noam Ross(https://twitter.com/noamross/status/1070733367522590721) about 15 months ago.

“Continuous Integration” (CI) has become a standard for proper software development.Checking the integrity of software after changes have been made is essential to ensure its proper functionality.Also, CI helps catch problems introduced by dependencies early when executed on a regular basis (usually done via scheduled CRON runs). Multiple professional providers exist (Travis CI, AppVeyor CI, Circle CI, etc.) which offer CI services to the