Goal-models to support communication, planning and guiding of FAIRification

Implementing the FAIR principles makes data ready for efficient analysis with other data. Workflows for the process of making data FAIR (‘FAIRification’) describe how the principles can be realised. As a multidisciplinary activity, FAIRification relies on good communication with different expertise involved. However, FAIRification workflows currently do not specify methods to meet this need. We are designing a method that uses ‘goal-oriented models’ to support the FAIRification ‘objective identification’ and ‘conceptual modelling’ steps. In the former, the motivation(s) for the need for FAIR data are identified. In the latter, goal models are used to define the scope, identify important concepts and validate the resulting conceptual model. The method will also describe best practices and activities for conceptual modelling.