Domain agnostic

The ACME-FAIR is to help those managing and delivering relevant professional services to self-assess how they are enabling researchers and their colleagues to do just that.

This checklist helps policy-makers to assess whether elements of their data policies are FAIR-enabling as well as providing recommendations on what should be addressed in policies.

This is a teaching and training handbook for higher education institutions to help universities to apply the competence framework to their specific situation and needs.

This model assess dataset maturity using indicators based on the FAIR principles

The FAIR Cookbook contains defined recipes for FAIRifying datasets, as well as more general topic guidance.

A methodology for FAIR-by-design production of learning materials based on the backward instructional process that is extended with additional activities focusing on the implementation of the FAIR guiding principles.

OGC RAINBOW is a Web accessible source of information about things (“Concepts”) the OGC defines or that communities ask the OGC to host on their behalf. It applies FAIR principles to the key concepts that underpin interoperability in systems using OGC specifications.

The F2DS is a unifying data space that is built by aggregating and enriching datasets from a set of multidisciplinary repositories, i.e. data sources, with the aim to facilitate data discovery and reuse. Although datasets are the primary focus of the resulting data space, other items are managed, including repositories and data sources, APIs, metadata schemas and ontologies

FAIR Connect is an Open Access publishing platform for the development and dissemination of good practices for professional FAIR-Data stewardship.

The FAIRassist tool, part of the FAIRsharing resource offers personalised guidance to discover resources such as data & metadata standards.

The CoreTrustSeal + FAIRenabling Capability Maturity Model was designed so that repositories can self assess their trustworthiness and FAIR enabling status simultaneously, with a view to developing and improving their practice.

The FAIRsFAIR service assessment framework helps users self-assess how well their research data infrastructure services support FAIR data.