The Metroline - Steps for your FAIRification Workflow

STATUS: IN DEVELOPMENT WG REVIEW

The FAIR principles aim to make data Findable, Accessible, Interoperable and Reusable, to maximize the reuse of (research) data. See this page for more information on FAIR.

But, where do you start to make data FAIR? What steps are involved? What do these steps mean and, importantly, how do you implement these steps? The FAIR Metroline provides practical guidance to help you reach your FAIR goals and make your data more FAIR.

Based on a variety of models and publications (see below), the FAIR Metroline entails an extensive list of FAIR steps. Depending on your project and goals only a select number of steps may be relevant. Consequently, each project will have its specific workflow:

The FAIR Metroline is under development, in alignment with the development of the Dutch National Health Data Catalogue. Over the coming months, we will add detailed how-to descriptions and real-life examples of FAIR Metroline that will particularly help projects and initiatives to onboard (meta)data to the Dutch National Health Data Catalogue. This already is a first effective step to make your data more FAIR. We also collaborate with the health domain funders and their efforts to stimulate incorporating FAIR into projects from the start.

For the current status of the steps see this page.

Overview Metroline steps

Models and further reading 

• The Metroline - Steps for your FAIRification Workflow

• Critical Steps towards Large-Scale Implementation of the FAIR Data Principles

• Model: Generic

• Model: De Novo

• Model: Trust Framework (unpublished)

• Model: FAIRopoly

• Model: FAIR Plus

• Model: GO FAIR

• Model: 5 Pillars of FAIRification (unpublished)