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We’re thrilled to be introducing a new member of our team. Mark Padgham has joined rOpenSci as a Software Research Scientist working full-time from Münster, Germany. Mark will play a key role in research and development of statistical software standards and expanding our efforts in software peer review, enabled by new funding from the Sloan Foundation. He will work closely with Noam Ross, rOpenSci Leadership team member, and Scientist at EcoHealth Alliance and Karthik Ram, rOpenSci Project Lead....
The United States Deparment of Agriculture National Agricultural Statistics Service (USDA-NASS) provides a wide range of agricultural data that includes animal, crop, demographic, economic, and environmental measures across a number of geographies and time periods. This data is available by direct download or queriable via the Quick Stats interface. While the Quick Stats tool puts a large amount of data into the hands of users, the interface can be frustrating, especially when trying to access more than 50,000 records or hoping to automate downloading data when new data is released....
rOpenSci thrives because of volunteer contributions from community members - submitting and reviewing R packages, serving as editors for software peer review, writing blog posts, sharing information about packages and resources, contributing code and documentation and answering others’ questions. Recently our fiscal sponsor, NumFOCUS, gave us an opportunity to nominate two contributors for recognition at the NumFOCUS annual summit. Sometimes all we can do is publicly express our gratitude for the people who help make our software robust and sustainable, and make our community a welcoming place that adds value to people’s experiences....
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. It’s becoming more common for researchers to provide code along with published papers (but usually as Matlab scripts…ugh), but it is still typical for most analyses to be performed with code that stays in-house....
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 & A. As someone with a background in science, not software engineering, Steffi LaZerte will share her experiences using automated testing in R to ensure that packages do what they’re supposed to do, on all the operating systems they’re supposed to do it on, and that they handle weird stuff gracefully....
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