A short practical guide for preparing and sharing your analysis code

With the increasing popularity of open science practices, it is now more and more common to openly share data processing and analysis code along with more traditional scientific objects such as papers. There are many benefits to doing so: it makes your work more easily verifiable, reproducible, and reusable. But what are the best ways to create an understandable, openly accessible, findable, citable, and stable archive of your code? In this post, we look at what you need to do to prepare your code folder and then how to upload it to Zenodo.

Building a FAIR Expertise Hub for the social sciences

It is increasingly common for researchers to rely on the use of data sets that were not originally intended for research purposes. These data sets often lack appropriate documentation and information about how they were created and are often less reliable. The project ‘Building a FAIR Expertise Hub for the social sciences’, which was recently awarded funding by the Platform Digitale Infrastructuur Social Science and Humanities (PDI-SSH), is aimed at targeting this issue by supporting the data providers in the social sciences in improving the Findability, Accessibility, Interoperability and Reusability (FAIRness) of their data.