Determine goal for FAIRification in terms of desired usability of data that isn’t currently possible
L

DEFINE FAIRIfiCATION

GOAL

Examine in detail a dataset's current and expected data requirements as well as available resources and expertise
L

PROJECT

EXAMINATION

Iteratively design and implement FAIRification tasks to reach the original goals
L

INTERACTIVE FAIRIfiCATION

CYCLES

Review outcomes and asses success against original goals
L

POST FAIRIfiCATION

REVIEW

DEFINE FAIRIFICATION

GOAL

PROJECT

EXAMINATION

INTERACTIVE FAIRIfiCATION

CYCLES

POST FAIRIFICATION

REVIEW

Welcome to the FAIRplus FAIRification Framework

Helping organisations, projects and teams establish FAIRer data management habits through reusable templates, processes and guidance

On this page, you will find a step-by-step guide to help you plan the work to improve the FAIR level of datasets you produce. The FAIRplus FAIRification framework will teach you how to identify your current FAIR maturity level, identify practical measures your organisation or project can take to improve and provide structured processes and guidance on how to perform the technical work necessary to execute these measures.

The core resources we will talk about are: 

You can also find a preprint of our upcoming publication on Zenodo. It is part of the FAIRplus collection, which also contains copies of all the images and diagrams related to the framework.