FAIR_Trainer

Trainers design and deliver training programs to a variety of stakeholders ranging from researchers to business leaders and project teams across organisation functions (R&ED, but also development, clinical, franchises), with a focus on awareness and best practice implementation of FAIR data principles. The role supports compliance with corporate data governance policies, regulatory expectations, and scientific needs. It interfaces and interacts woth

Collaborate with data governance leads, technology leads, data architects, community managers and researcher teams to identify training needs aligned with corporate strategy; design tailored, role-specific training schedules; create high-quality, compliant, and FAIR-aligned learning materials (presentations, manuals, e-learning modules, job aids); deliver in-person, virtual, and hybrid sessions combining policy awareness with hands-on skills; promote company-approved and community recommended tools, standards, and workflows; adapt delivery for varied therapeutic areas, modalities, and stages of development (R&D, etc); establish continuous improvement processes through structured feedback and impact measurement. Keep track of FAIR training offering outside of the organisation.

Upside

Implementing FAIR principles would reduce these challenges and unlock efficiency, compliance, and reuse.

Downside

The lower the organisation FAIR maturity level, the higher the complexity of the role and the need to create awareness. Lack of clarity and alignment in terms of needs and requirements from the organisations can be expected.

At more advanced maturity levels, traning may become diversified and tuned to the needs of differen stakeholders, from business leaders, to researchers, to Data Stewards and Architects.

In a change management process, the value of the training, FAIR and data-centric approach may be challenged.

FAIR principles provide a strong foundation for trainers to embed best practices in data management and reusability across teams and organizations. By leveraging success stories, FAIR Trainers can effectively articulate the underlying rationale ('why') for FAIR training, fostering greater engagement and commitment. The re-use of FAIR-aligned training materials and the adoption of open standards are facilitated by highlighting real-world examples from FAIR implementation journeys and profiles. With well-defined metrics and frameworks such as FAIR indicators and the FAIR Maturity Model (FAIR MM), Trainers are able to assess both datasets and organizational adherence, offering tangible benchmarks for progress. The impact of training is ultimately heightened through the availability of FAIR-compliant data and implementation examples.