NIST Research Data Framework, Version 2.0
RDaF organizes research-data concerns across planning, lifecycle, infrastructure, standards, governance, workforce, and community perspectives.
What the authority record establishes
RDaF organizes research-data concerns across planning, lifecycle, infrastructure, standards, governance, workforce, and community perspectives.
Voluntary framework
The exact official title, issuing body, jurisdiction, version or application record, and linked source define the scope of this page. Readers should not transfer the authority's status to a commercial product or infer transaction-, patient-, system-, site-, or organization-specific applicability from this summary.
Why it matters to this market
It gives R&D buyers a broader research-data operating model for stewardship, interoperability, access, preservation, reuse, and governance beyond notebook authoring or file storage.
Affected operating stages
- Plan
- Generate
- Process
- Analyze
- Share
- Preserve
- Reuse
Capabilities to examine
ELN Experiment Authoring And Collaboration
Ask how the system or service identifies the controlling source and version, applies customer-specific interpretation, handles exceptions, preserves human judgment, and retains evidence for ELN experiment authoring and collaboration.
Raw Scientific-File Capture And SDMS Archive
Ask how the system or service identifies the controlling source and version, applies customer-specific interpretation, handles exceptions, preserves human judgment, and retains evidence for raw scientific-file capture and SDMS archive.
Scientific Data Models Ontology And Semantic Context
Ask how the system or service identifies the controlling source and version, applies customer-specific interpretation, handles exceptions, preserves human judgment, and retains evidence for scientific data models ontology and semantic context.
Scientific Search Analytics And Data Reuse
Ask how the system or service identifies the controlling source and version, applies customer-specific interpretation, handles exceptions, preserves human judgment, and retains evidence for scientific search analytics and data reuse.
Electronic Signatures Audit Trails And Record History
Ask how the system or service identifies the controlling source and version, applies customer-specific interpretation, handles exceptions, preserves human judgment, and retains evidence for electronic signatures audit trails and record history.
Role Identity Access And Segregation-Of-Duties Controls
Ask how the system or service identifies the controlling source and version, applies customer-specific interpretation, handles exceptions, preserves human judgment, and retains evidence for role identity access and segregation-of-duties controls.
API Integration And Enterprise Interoperability
Ask how the system or service identifies the controlling source and version, applies customer-specific interpretation, handles exceptions, preserves human judgment, and retains evidence for API integration and enterprise interoperability.
Deployment Administration Change Control And Validation Support
Ask how the system or service identifies the controlling source and version, applies customer-specific interpretation, handles exceptions, preserves human judgment, and retains evidence for deployment administration change control and validation support.
Affected buyer audiences
- research leaders
- data stewards
- scientists
- technology
- libraries and archives
Implementation questions
- Which entities, products, populations, transactions, systems, sites, or jurisdictions are actually within scope?
- What is binding, what is guidance, and what is a technical or consensus standard?
- Which publication, adoption, effective, application, transition, and enforcement dates differ?
- Who owns legal, clinical, quality, regulatory, policy, or operational interpretation?
- How will a source revision affect open work and historical decisions?
Interpretation boundary
The framework does not prescribe a product architecture, certify a platform, or establish scientific validity or data fitness.