A goal-oriented method for FAIRification planning

The FAIR Principles provide guidance on how to improve the Findability, Accessibility, Interoperability, and Reusability of digital resources. Since the publication of the principles in 2016, several workflows have been proposed to support the process of making data FAIR (FAIRification). However, to respect the uniqueness of different communities, both the principles and the available workflows have been deliberately designed to remain agnostic in terms of standards, tools, and related implementation choices. Consequently, FAIRification needs to be properly planned in advance, and implementation details must be discussed with stakeholders and aligned with FAIRification objectives. To support this, this paper describes a method for identifying and refining FAIRification objectives. Leveraging on best practices and techniques from requirements and ontology engineering, the method aims at incrementally elaborating the most obvious aspects of the domain (e.g. the initial set of elements to be collected) into complex and comprehensive objectives. The definition of clear objectives enables stakeholders to communicate effectively and make informed implementation decisions, such as defining achievement criteria for distinct principles and identifying relevant metadata to be collected.