  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.
