Abstract
Science has a data management problem, as well as a project management problem. While industrial-grade data science teams have embraced the agile mindset, and adopted or created all kind of tools to create reproducible workflows, academia-based science is still (mostly) mired in a mindset that is focused on a single final product (a paper), without focusing on incremental improvement, on any specific problem or customer, or, paying any attention reproducibility. In this report we argue towards the adoption of the agile mindset and agile data science tools in academia, to make a more responsible, and over all, reproducible science.
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