This indicator assesses the presence and adoption of data management documentation standards, best practices and guidelines provided by the organisation. It evaluates how systematically documentation requirements are defined, communicated and implemented across research activities.
Level 1 – No documentation standards present or recommended
- Absence of guidance: No formal or informal documentation standards, templates or institutional guidelines exist.
- Individual practice: Documentation is left to the discretion of individual researchers or groups, often varying widely in quality and format.
- Inconsistency: Information about data, methods and analyses is recorded sporadically or incompletely, making verification or reuse difficult.
- Lack of awareness: There is little or no understanding within the organisation of the importance of systematic documentation for research integrity or FAIR data management.
Impact: Documentation practices are ad hoc and inconsistent, leading to loss of information, limited reproducibility and minimal institutional oversight of research data quality.
Level 2 – Reference to generic best practices
- Generic guidance: Documentation standards or guidelines exist but remain broad and unspecialised. They refer to general RDM principles (e.g., FAIR) and use non-domain-specific terminology without concrete examples relevant to particular research contexts or disciplines.
- Reactive development: Guidance is often provided in response to external requirements rather than proactively maintained (e.g., from a research council as a condition for funding).
- Inconsistent delivery: The quality and content may vary depending on who provides the training or support.
- Unclear responsibility: Guidance may be developed or delivered by individuals without broad RDM knowledge or general data managers lacking domain-specific expertise.
Impact: Awareness of documentation good practice begins to emerge, but materials remain generic and inconsistently applied, limiting their usefulness and integration into daily research workflows.
Level 3 – Guidelines / standards provided and documented for researchers / relevant groups / relevant RDM processes
- Domain-specific guidance: Documentation standards are tailored to particular subjects or domains, using relevant domain-specific terminology and practical examples (e.g., example of writing data dictionaries for health research).
- Proactive and targeted: Guidance is developed in advance and made available at project start, communicated to the relevant audiences such as departments or research groups.
- Defined responsibility: Specific individuals or teams are assigned to maintain and disseminate documentation within their domain or department (e.g., institute or group level data managers).
- Limited revision: Documentation exists as a fixed reference and is not yet routinely updated in response to user feedback or changing needs.
Impact: Documentation practices become consistent and reliable across the organisation, improving clarity, reproducibility and alignment with domain-specific RDM processes.
Level 4: Guidelines / standards adopted by researchers / relevant groups / relevant RDM processes
- Broad adoption: Documentation has wide awareness and best practices are applied. The material is written with clearly defined target audiences in mind (e.g., collaborators, departments, external bodies, industry partners).
- Communication: The existence of the documentation is proactively communicated to the appropriate audiences (e.g., targeted emails to researchers and other relevant parties).
- Awareness: Target audiences understand both the purpose and relevance of the documentation as well as the challenges, processes and expectations that it is relevant to.
- Live documents: Documentation is regularly reviewed and updated in response to user feedback, evolving practices and emerging requirements.
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