Data management planning

This indicator assesses how far the organisation has developed, maintained and embedded its guidance, training, consultancy and data management plan tools. It evaluates the extent to which these services strengthen researchers’ ability to manage, share and preserve their data in line with recognised best practices and with institutional or funder requirements.

Level 1 – Nothing offered

• Generic advice or less offered: If information about data management requirements exists, it is minimal and high level.
• Missing documentation: No guidelines, tools or best practice advice are available to researchers.

Impact: Researchers receive little or no support, leading to inconsistent and often ad hoc data management practices across the organisation.

Level 2 – Best practice and guidelines available

• Basic guidance: Guidelines draw on recognised best practices but are not yet supported by structured training or consultancy.
• Generic resources: General RDM tips, recommendations or FAQs are available and maintained.

Impact: Researchers can access foundational information that improves awareness of RDM. However, the lack of dedicated personnel and sustained support limits the consistent adoption of best practices.

Level 3 – Consultancy and training available, more standardized guidelines; DMP writing may be required from some researchers

• Dedicated staff: Specialised staff with expertise in data management planning and RDM are available to support researchers.
• Defined RDM services: Consultancy, training, DMP tools and templates and more standardised guidelines are increasingly offered and maintained.
• Growing consistency: DMPs are used in some projects but not yet required or implemented across the entire organisation.

Impact: Researchers benefit from targeted guidance and structured support, resulting in more consistent data management practices. Full institutional integration of RDM planning and tools is still developing.

Level 4 – DMP tool available and machine actionability facilitate further integration; DMP writing may be required for all projects

• Maintenance and quality assurance: Procedures ensure that all resources and services are updated, maintained and aligned with evolving best practices.
• Institution-wide adoption: DMP writing is required for all research projects. DMPs are widely used and regularly reviewed and updated.
• Integrated RDM services: A coherent portfolio of RDM services is in place, including consultancy, training, DMP tools and templates and clear requirements supported by checklists and maintenance procedures.
• Machine-actionable DMPs: Machine-actionable DMP tools and workflows are implemented, widely used and routinely updated.

Impact: Researchers have access to comprehensive, coherent and machine-actionable RDM services. Use of these resources is widespread, institutional expectations are clearly communicated and adherence to funder requirements is consistently achieved.

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