Data Management Best Practices

RDM Frameworks

Data management coexists with broader frameworks that shape how and why we manage, document, and share data. This table synthesizes three frameworks: FAIR, SEER, and Open Science—and offers key elements, concrete and actionable steps for applying them in day‑to‑day RDM work.

How to apply FAIR in RDM work

Planning: state your repository, identifier, formats, and metadata approach in the DMP; plan for open formats.
During cleaning/finalization: prepare searchable metadata (title, description, coverage, creators) and document provenance steps.
Release and archiving: publish data (or a request pathway) and always publish metadata; include clear licensing and citation information.

How to apply SEER in RDM work

Before data collection: preregister study plans; prepare to make data and methods open where feasible.
During implementation: document study details; track components to support interpretation and generalization.
After analysis: share findings, methods, and—when allowed—de‑identified data to support scaling and reuse.

How to apply Open Science in RDM work

Plan for openness: design your workflow to enable open data, analysis, and materials where allowed.
Maintain documentation: create metadata, codebooks, and provenance notes so others can interpret and validate your outputs.
Enable access: provide a repository location or request pathway; preregister when appropriate; pursue open access for outputs when feasible.

Data Management Rubric

By applying the RDM rubric, researchers can clearly see the gap between their current practices and their desired or required standards for research data management. This diagnostic function is powerful: it highlights strengths, pinpoints areas for growth, and sets a concrete roadmap for improvement. At the same time, data service providers can align the rubric with guides that spotlight available tools and institutional supports. Together, this creates a practical bridge—not just identifying where a research group stands, but showing exactly how they can advance toward best practices in RDM.