Science has a data management 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 manage reproducible workflows, academia-based science is still (mostly) mired in a mindset that's focused on a single final product (a paper), without focusing on incremental improvement and, over all, 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, sustainable, and above all, reproducible science.
Agile (data) science: a (draft) manifesto