Working together to push science forward
Happy rOpenSci users can be found at
Version 7.0.0 of drake just arrived on CRAN, and it is faster and easier to use than previous releases. install.packages("drake") 🔗 Recap Data analysis can be slow. A round of scientific computation can take several minutes, hours, or even days to complete. After it finishes, if you update your code or data, your hard-earned results may no longer be valid. How much of that valuable output can you keep, and how much do you need to update?...
Our next Community Call, on March 27th, aims to help people learn about using rOpenSci’s R packages to access and analyze taxonomy and biodiversity data, and to recognize the breadth and depth of their applications. We also aim to learn from the discussion how we might improve these tools. Presentations will start with an introduction to the topic and details on some specific packages and we’ll hear from several people about their “use cases in the wild”....
Citations are a crucial piece of scholarly work. They hold metadata on each scholarly work, including what people were involved, what year the work was published, where it was published, and more. The links between citations facilitate insight into many questions about scholarly work. Citations come in many different formats including BibTex, RIS, JATS, and many more. This is not to be confused with citation styles such as APA vs. MLA and so on....
🔗 Introduction stats19 is a new R package enabling access to and working with Great Britain’s official road traffic casualty database, STATS19. We started the package in late 2018 following three main motivations: The release of the 2017 road crash statistics, which showed worsening road safety in some areas, increasing the importance of making the data more accessible. The realisation that many researchers were writing ad hoc code to clean the data, with a huge amount of duplicated (wasted) effort and potential for mistakes to lead to errors in the labelling of the data (more on that below)....
The ssh package provides a native ssh client for R. You can connect to a remote server over SSH to transfer files via SCP, setup a secure tunnel, or run a command or script on the host while streaming stdout and stderr directly to the client. The intro vignette provides a brief introduction. This week version 0.4 has been released, so you can install it directly from CRAN: install.packages("ssh") The NEWS file shows that this is mostly a bugfix release:...
Happy rOpenSci users can be found at