Given the magnitude of the current crisis of replicability and reproducibility, it’s only sensible that any attempt to solve this crisis must involve opening up our work. That includes many different aspects along the research cycle, which, let’s be honest, can feel like a big burden to a researcher who already works too much unpaid overtime. I argue in this presentation that there a some things you can tackle now that I believe can help a lot with a very reasonable amount of time and effort. And these things involve how we deal with and manage our data. This is where the Frictionless Data project comes into play. It is an open source project by the Open Knowledge Foundation, which involves a set of specifications for data and metadata, but also a set of software libraries, mainly developed in Python but adapted to other programming languages, and a set of data management best practices. All of that ensures the interoperability of your data.