OKFestival

Research is becoming increasingly data intensive and computation driven across the board, from the life sciences to physics. There is also added pressure from funders and publishers for researchers to better document and share the outputs of their work, but despite a push for better practice, we’re still facing a gap between what computational skills (analysis, versioning, data management) researchers are expected to know and what they’re being taught at the university level.

There are a number of training programs out there (Software Carpentry, rOpenSci, Open Science Training Initiative, School of Data) working to provide additional support to researchers. But how do those skills map into the vision for more open, reproducible science? This session will explore both, providing hands on training and examples as well as fostering a discussion about how these skills lead to the vision of open research we’re all striving for.