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Short description

Building upon the findings from on the pre-FAIR assessment, this step provides defines a structured approach to addressing identified gaps in FAIR compliance. A well-defined solution plan ensures that all necessary It transforms assessment insights into an actionable solution plan, ensuring technical, organisational, and procedural aspects are systematically considered, leading to an effective and sustainable transition towards FAIR data. By transforming assessment insights into actionable strategies, this step provides a clear roadmap for implementationconsidered. It helps your team allocate resources efficiently and prepare for upcoming challenges. The outcome is a clear roadmap that enhances data management and prepares for improved FAIRification.

Why is this step important 

Following the The pre-FAIR assessment , where identifies key gaps and improvement areas are identified, this challenges in FAIR compliance, such as incomplete metadata, lack of a data storage strategy, or missing documentation practices. If left unaddressed, these issues can hinder data quality, interoperability, and reuse. This step ensures that those assessment insights are systematically addressed. Without a well-defined plan, FAIRification efforts can become translated into a structured plan, preventing fragmented and ineffective . This step transforms assessment findings into actionable solutions, helping to:

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FAIRification efforts. A well-defined solution plan helps to:

• provide a structured approach to tackling complex data issues and aligning stakeholders on a shared approach,strategy;

• Optimise optimise the use of available resources and infrastructure,Define define success criteria to measure progress,Facilitate long-term sustainability and interoperability of FAIR datatrack progress;

• enhance data quality, ensuring better insights, improved compliance with FAIR principles, and greater efficiency in research processes.

How to 

Step 1

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- Identify and prioritise key requirements

Based on the outcomes of the PreUsing the pre-FAIR Assessment, identify the specific needs required to bridge the FAIR-related gaps. These may include metadata schemas, persistent identifiers, or data repositories that were found lacking in the assessment.

Step 2 – Assess feasibility and constraints

Assess assessment findings, identify and rank key issues based on urgency, impact, and feasibility. Prioritisation ensures that critical gaps, such as incomplete metadata, lack of persistent identifiers, or missing documentation, are addressed first.

Example: If metadata incompleteness is blocking data reuse, improving metadata standards should take precedence over less critical issues.

Step 2 - Define clear objectives

For each prioritised issue, define SMART objectives (Specific, Measurable, Achievable, Relevant, Time-bound). These objectives will guide implementation and measure progress.

Example: By [date], update metadata for 90% of datasets to comply with [standard], ensuring all required fields are completed.

Step 3 - Assess feasibility and identify constraints

Evaluate the current infrastructure, policies, and data governance environment identified in the Pre-FAIR Assessment. Determine . Identify constraints such as legal barriers, technical limitations, and organisational readiness that could hinder FAIR implementation, and define or resource availability. Develop mitigation strategies to address them.

Example: If data governance policies prevent external repository use, consider alternative institutional solutions.

Step

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4 - Select appropriate tools and methodologies

Using insights from the Pre-FAIR Assessment, select Choose tools, frameworks, and methodologies that directly best address the identified gaps identified. Resources such as http://FAIRsharing.org and existing FAIR Implementation Profiles (FIPs) should be leveraged to ensure alignment with best practices.

Examples:

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• Metadata improvement: Use controlled vocabularies and standards.

• Persistent identifiers: Implement DOIs or Handles for datasets.

Step 5 - Engage stakeholders and align objectives

Engage the same stakeholders involved in the Pre-FAIR Assessment to ensure continuity. Foster collaboration between Involve key stakeholders from the pre-FAIR assessment phase, including data stewards, domain experts, and IT teams to translate assessment findings into a practical and domain-specific solution plan.

Step 5 – Develop the FAIRification roadmap

Develop a detailed implementation roadmap that reflects the prioritised recommendations from the Pre-FAIR Assessment. Ensure alignment between technical and organisational priorities to create a feasible solution plan.

Tip: Regular check-ins help maintain engagement and prevent misalignment.

Step 6 - Develop a structured FAIRification roadmap

Create an implementation roadmap outlining key actions, responsibilities, timelines, and resources. Define key performance indicators that track the effectiveness of interventions (KPIs) to track progress and allow for iterative improvements.

Step 6 – Validate and refine the solution plan

Validate the proposed solution with stakeholders by comparing it to the insights gathered in the Pre-FAIR Assessment. Ensure that the solution effectively addresses identified gaps, and adjust where necessary based on stakeholder input.

Expertise requirements for this step 

Describes the expertise that may be necessary for this step. Should be based on the expertise described in the Metroline: Build the team stepadjustments.

Step 7 - Conduct risk assessment and refine the plan

Identify potential risks (e.g., delays, lack of resources) and define mitigation strategies. Review the solution plan with stakeholders and refine it based on feedback.

Example: Risk: Limited personnel availability. Mitigation: Cross-train team members to ensure continuity.

Expertise requirements for this step 

Designing a solution plan is typically a collaborative effort by a range of experts, as described in Metroline Step: Build the Team.

• FAIR experts.Provide guidance on best practices, standards, and methodologies.

• Domain experts. Define data semantics, quality standards, and use cases.

• Data stewards. Ensure data and metadata comply with FAIR principles.

• IT specialists. Support infrastructure needs, interoperability, and tool integration.

• Project managers. Oversee planning, stakeholder coordination, and implementation tracking.

Practical examples from the community 

This section should show the step applied in a real project. Links to demonstrator projects. 

Training

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• FAIRification Tools and Templates – ELIXIR-UK Fellowship

• FAIRification Workflow – FAIR Toolkit

• FAIR Implementation Profile

Suggestions

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