For the better part of a year, I have been looking for an opportunity to use the rOpenSci package deposits in myrole as the Data Librarian at EcoHealth Alliance.I had done some initial testing with Mark Padgham, the brilliant person who developed this package, but there weren’t any projects ready for me to put deposits through its paces.Enter the Rift Valley Fever Virus in South Africa project, a ten year, multiple part study of humans,

What is renv RStudio’s renv package is a powerful dependency management toolkit for R. It allows you to create a lockfile that records the exact versions of R packages used in a given project, and provides tooling to install exactly those same versions on another machine, or at a later point in time. This is very useful to create an isolated project environment for reproducibility or production purposes.

I teach R to a lot of scientists, those that are new to science (i.e. students)as well as more established scientists, new to R.I find that after all their struggles of dealing with dates,or remembering where to put the comma, they’re so grateful to actual have an analysis,that they often forget or aren’t aware of the next steps.

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

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?

Studies of muscle physiology often rely on closed-source, proprietary software for not only recording data but also for data wrangling and analyses. Although specialized software might be necessary to record data from highly-specialized equipment, data wrangling and analyses should be free from this constraint.

To the uninitiated, software testing may seem variously boring, daunting or bogged down in obscure terminology. However, it has the potential to be enormously useful for people developing software at any level of expertise, and can often be put into practice with relatively little effort. Our 1-hour Call will include two speakers and at least 20 minutes for Q &

Ambitious workflows in R, such as machine learning analyses, can be difficult to manage. A single round of computation can take several hours to complete, and routine updates to the code and data tend to invalidate hard-earned results. You can enhance the maintainability, hygiene, speed, scale, and reproducibility of such projects with the drake R package.

Our 1-hour Call on Reproducible Research with R will include three speakers and 20 minutes for Q & A. Ben Marwick will introduce you to a research compendium, which accompanies, enhances, or is a scientific publication providing data, code, and documentation for reproducing a scientific workflow.

Introduction Open Trade Statistics (OTS) was created with the intention to lower the barrier to working with international economic trade data. It includes a public API, a dashboard, and an R package for data retrieval.