A goal-oriented method for FAIRification planning

Abstract

Abstract 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, we describe GO-Plan, 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. Experience has demonstrated that 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. This paper describes the GO-Plan method and reports on a real-world application in the development of a FAIR ontology catalogue.