Open science

FAIR data:

We organize our data according to Fair principles: Findable, Accessible, Interoperable, Reusable. We also publish our data and articles open access either through the routes of the journal or through repositories. We value making all our findings accessible to anyone in the world. The core team ‘Open Science: Data Management’ develops novel ways for data management and sharing.

Data sharing:

We share data when possible, according to the standard of General Data Protection Regulation (GDPR)[]. Data of published manuscripts are available for re-analysis. We are also open to share data that is not yet published. We share the meta-data from all our projects (see project descriptions).

Transparency in the research process:

There is no golden standard for Open Science, but transparency is key. When possible, we pre-register our hypotheses and analysis plans to clearly describe which analyses are confirmatory and which analyses are exploratory. Both types of analyses are important, each contributes to the field in different ways. We share our codes using various channels such as Github and Neurovault. We use buddy systems where researchers help each other and check each other’s data and analyses. Because we work as a team, each data set is always accessible to multiple researchers.

Open communication:

All voices matter, independent of your position in the lab. We have an open atmosphere where we can talk about successes, mistakes, doubts, and ways in which we can improve our communication and collaboration. In case someone feels uncertain or unsafe, Erasmus University has a Vertrouwenspersoon who can be contacted, who keeps conversations private, and who helps with finding solutions.