A FAIRification activity is an instantiation of the Common FAIRification Framework to address a particular use case or FAIR-related challenge; it is a focused piece of work on a specific digital object, set of digital objects, service, or data management practice to address FAIR-related use cases or project objectives, such as optimising hosting, content, formats, metadata, or access.
The first step is to define what is being FAIRified. This involves defining the unit of what is being made more FAIR, how the assessment of improvement is to be made, and the implementation options within the given context. This unit may be a dataset, a collection of datasets, a software release, a computational workflow, an ontology version, a service endpoint specification, a repository record, or another digital object relevant to the use case.
This scoping step should be completed before assessment begins. It clarifies what exactly is being FAIRified, at what level of granularity, and with what boundaries or end points. Without this agreement, assessments may produce ambiguous results and workplans that are difficult to execute.
A FAIRification activity should target the level at which the resource is sufficiently FAIR to support its intended uses — no more and no less. This is the “FAIR enough” approach. For example, a dataset published alongside a paper may need to be findable, citable and accessible to readers, while a dataset intended for cross-study harmonisation across a research community may need stronger alignment with community standards, identifiers, vocabularies and data models. While the latter situation would also incorporate and be preferable to the former, scoping may preclude its implementation, for example due to time constraints, lack of community standards, or lack of available personnel expertise.
In practice, a FAIRification activity moves through three connected stages:
- Scope the activity
Define the resource, its intended use, the current FAIR-related barriers, and the capabilities and resources available to the FAIRificaion activity. - Assess and FAIRify the resource
Assess the current state, set a realistic FAIRification goal, (optional) select relevant Template steps, implement improvements, and review whether the resource is now FAIR enough for its intended use. Iteration may be required where target FAIRification levels have not been achieved. - Share lessons learned
Capture the decisions, tools, standards, resources, barriers and outcomes from the activity so they can inform future FAIRification work and contribute to the library of interoperability stories.
The Template lists a generic and logical set of implementation strategies that can be executed across a diverse set of resource types. It is organised as capability dimension categories, and can help during scoping and project examination phases. They can also help decide which strategies are under the project’s control and which are external, for example those that depend on repositories, discovery services, hosting environments, standards, or other external resources. For example, a project team may be able to improve metadata completeness, reuse community identifiers, or align data with a standard format. However, improvements to search, retrieval, access control, repository validation, or cross-resource discovery may depend on the capabilities of the hosting environment. Recognising these dependencies early helps define a realistic FAIRification goal and a practical Workplan.