Friday, July 23, 2021 From rOpenSci (https://ropensci.org/blog/2021/07/23/ropensci-news-digest-july-2021/). Except where otherwise noted, content on this site is licensed under the CC-BY license.
Dear rOpenSci friends, it’s time for our monthly news roundup!
You can read this post on our blog. Now let’s dive into the activity at and around rOpenSci!
Great news for fans of statistics and software!
rOpenSci’s peer-review system has now expanded to include review of packages implementing statistical routines and algorithms.
We are thrilled to start this new chapter, for which we’ve developed a series of new standards and tools, and recruited a new board of experts to oversee.
Authors of statistical software should begin by reading the Stats Software Dev Guide, which describes the categories of statistical software we now accept (Regression, Machine Learning, Exploratory Data Analysis, and more!), along with the procedures for preparing statistical software for peer review.
It also introduces our automation tools, such as the
pkgcheck package, which confirms that statistical software is ready to be submitted for review.
Authors submitting statistical software to review should start by opening a pre-submission inquiry on our main software review repository.
Inquiries are welcome well before packages are ready for submittal.
We hope authors make use of our standards and tools throughout the development process so as to make review straightforward.
To volunteer as a reviewer, fill our short form.
For any question, you can post on the rOpenSci forum or contact the statistical software team (Mark Padgham, mark<at>ropensci.org, and Noam Ross, ross<at>ecohealthalliance.org).
On another topic, if you find yourself with more time for learning this summer, why not dig into the rOpenSci community calls archive? Every topic comes with a 1-hour video, speakers’ slides, links to related resources, and a document with questions and answers from participants. As of March 2020, video recordings have closed captions.
Find out about events.
The following two packages recently became a part of our software suite:
awardFindR, developed by Michael McCall: Queries a number of scientific awards databases. Collects relevant results based on keyword and date parameters, returns list of projects that fit those criteria as a data frame. Sources include: Arnold Ventures, Carnegie Corp, Federal RePORTER, Gates Foundation, MacArthur Foundation, Mellon Foundation, NEH, NIH, NSF, Open Philanthropy, Open Society Foundations, Rockefeller Foundation, Russell Sage Foundation, Robert Wood Johnson Foundation, Sloan Foundation, Social Science Research Council, John Templeton Foundation, and USASpending.gov. It has been reviewed by João Martins, Kara Woo.
katex, developed by Jeroen Ooms: Convert latex math expressions to HTML and MathML for use in markdown documents or package manual pages. The rendering is done in R using the V8 engine (i.e. server-side), which eliminates the need for embedding the MathJax library into your web pages. In addition a math-to-rd wrapper is provided to automatically render beautiful math in R documentation files. It is available on CRAN.
The following eighteen packages have had an update since the latest newsletter: gert (
v1.3.1), awardFindR (
1.0), BaseSet (
v0.0.17), beastier (
v2.4.3), fingertipsR (
v1.0.7), GSODR (
v3.1.2), ijtiff (
v2.2.7), lightr (
v1.6.0), plotly (
v22.214.171.124), rcol (
v0.2.0), stantargets (
0.0.3), stats19 (
v1.4.3), stplanr (
v0.8.3), tarchetypes (
0.2.1), targets (
0.6.0), taxa (
v0.4.0), taxlist (
v0.2.2), tic (
There are twelve recently closed and active submissions and 5 submissions on hold. Issues are at different stages:
One at ‘6/approved’:
Four at ‘3/reviewer(s)-assigned’:
One at ‘1/editor-checks’:
Find out more about Software Peer Review and how to get involved.
How to create your personal CRAN-like repository on R-universe by Jeroen Ooms. Explanation of the few simple steps needed to launch your universe (create a git repository with a special JSON file, install a GitHub app).
How We Curate Our Monthly Newsletter by Maëlle Salmon. Our workflow for preparing and sending our monthly newsletter, partly automatically.
New package katex: rendering math to HTML and MathML in R by Jeroen Ooms. Convert LaTeX math expressions to HTML and MathML for use in Markdown documents or package documentation.
No new citations added to our database this month (browse all citations).
Five use cases of our packages and resources have been reported since we sent the last newsletter.
Mapping Asian elephant observations with rgbif. Reported by Tuija Sonkkila.
Environment Canada air temperature using weathercan. Reported by Alexandre Bevington.
Historical dataviz recreations with a sprinkle of magick. Reported by Matt Dray.
pdftools + tesseract para extraer texto en español. Reported by Silvia Gutiérrez.
pdftools + map to download & read multiple pdfs. Reported by Silvia Gutiérrez.
There’s no open call for new maintainers at this point but you can refer to our contributing guide for finding ways to get involved!
As the maintainer of an rOpenSci package, feel free to contact us on Slack or email
[email protected] to get your call for maintainer featured in the next newsletter.
Some useful tips for R package developers. 👀
What R version should your package support? The rOpenSci development guide does not have any specific guidance for that (whereas e.g. the tidyverse policy is to support the current version, the devel version, and four previous versions of R). If you follow the Tidyverse example, then it’d make sense to test your package in those R versions on continuous integration.
Now if your choice of a recent R version as a minimal version stems from a newer base function, you might be interested in the backports package maintained by Michel Lang, that provides reimplementations of Functions Introduced Since R-3.0.0. Its README explains how to use it in packages. The README also has a list of the re-implementations, which is fun to look at for R history sake!
It takes a village to… write an R package, or at least it can: creator, authors, reviewers, contributors, copyrightholders, etc.
In an R package DESCRIPTION you can use the roles found in
utils:::MARC_relator_db_codes_used_with_R: aut, com, cph, cre, ctb, ctr, dtc, fnd, rev, ths, trl.
The current list of roles accepted for R packages are always listed in the output of
The official recognition of the reviewer role is something rOpenSci asked for and that we recommend in our development guide.
We also advise pairing names with ORCID IDs.
Now, how to easily re-use information from the DESCRIPTION file without copy-pasting it? Enter the desc package by Gábor Csárdi, a tip shared by Hao Ye in rOpenSci semi-open slack: you can use desc to synchronise information between DESCRIPTION and a README.Rmd! This can be handy for package development, but also off-the-label use of package development tooling for e.g. lesson development using pkgdown.
Thanks for reading! If you want to get involved with rOpenSci, check out our Contributing Guide that can help direct you to the right place, whether you want to make code contributions, non-code contributions, or contribute in other ways like sharing use cases.