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rOpenSci - open tools for open science

rOpenSci - open tools for open science
Open Tools and R Packages for Open Science
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rOpenSci HQ What would you like to hear about in an rOpenSci Community Call? We are soliciting your “votes” and new ideas for Community Call topics and speakers. Find out how you can influence us by checking out our new Community Calls repository. Videos, speaker’s slides, resources and collaborative notes from our Community Call on Reproducible Workflows at Scale with drake are posted. Help wanted!

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We want to know how you use rOpenSci packages and resources so we can give them, their developers, and your examples more visibility. It’s valuable to both users and developers of a package to see how it has been used “in the wild”. This goes a long way to encouraging people to keep up development knowing there are others who appreciate and build on their work.

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Author Scott Chamberlain

If you have an R package on CRAN, you probably know about CRAN checks. Each package on CRAN, that is not archived on CRAN 1 , has a checks page, like this one for ropenaq:https://cloud.r-project.org/web/checks/check_results_ropenaq.html The table above is results of running R CMD CHECK on the package on a combination of different operating systems, R versions and compilers.

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Authors Scott Chamberlain, Brooke Anderson, Anna Krystalli, Lincoln Mullen, Karthik Ram, Noam Ross, Maëlle Salmon, Melina Vidoni

As announced in February, we now have an online book containing all things related to rOpenSci software review. Our goal is to update it approximately quarterly - it’s time to present the third version. You can read the changelog or this blog post to find out what’s new in our dev guide 0.3.0! Updates to our policies and guidance Scope We’ve introduced an important change for anyone thinking of submitting a package.

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The UCSC Xena platform provides an unprecedented resource for public omics data from big projects like The Cancer Genome Atlas (TCGA), however, it is hardfor users to incorporate multiple datasets or data types, integrate the selected data withpopular analysis tools or homebrewed code, and reproduce analysis procedures.

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Teaching collaborative software development In the University of British Columbia’s Master of Data Science program one of the courses we teach is called Collaborative Software Development, DSCI 524. In this course we focus on teaching how to exploit practices from collaborative software development techniques in data scientific workflows.

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rOpenSci HQ rOpenSci received a $678K award from the Sloan Foundation to expand Software Peer Review. We are hiring for a new position in statistical software testing and peer review. Join our next Community Call on Reproducible Workflows at Scale with drake September 24th. Videos, speakers’ slides, resources and collaborative notes from our Community Calls on Involving Multilingual Communities and Reproducible Research with R are posted.