FAIR assessment of a dataset
We help researchers and research groups review the FAIR readiness of datasets before publication, during repository deposit or after publication.
The service focuses on whether a dataset is sufficiently findable, accessible, interoperable and reusable through metadata, documentation, identifiers, licences, file organisation and links to related research outputs.
Submit a consultation request
What this service supports
Findability
We check whether the dataset has sufficient metadata, title, authors, keywords, identifiers and links to related publications or projects.
Accessibility
We review access conditions, licence information, repository deposit status and whether users can understand how to access the data.
Interoperability
We assess whether metadata, formats, vocabularies, units, methods and related standards support integration with repositories, catalogues and EOSC-related services.
Reusability
We check whether the dataset has documentation, README, provenance, method description, file structure, licence and citation information needed for reuse.
How the process works
1. Request
You submit a consultation request and briefly describe the dataset that should be assessed.
2. Initial review
The Competence Center reviews the available dataset description, metadata, README, files and publication context.
3. FAIR criteria checked
The dataset is reviewed against practical FAIR criteria: findability, accessibility, interoperability and reusability.
4. Gaps identified
The Center identifies missing metadata, documentation, identifiers, licence information, access conditions or reuse instructions.
5. Recommendations provided
The research group receives practical recommendations for improving the dataset before publication, repository deposit or further reuse.
What users should prepare
To make the FAIR assessment useful, users are encouraged to prepare:
- dataset title and short description;
- current metadata or repository draft;
- file list or folder structure;
- README file, if available;
- licence or access conditions;
- related publication, project, DOI or repository link;
- information about methods, software, instruments or workflow;
- information about data formats, units, variables or parameters;
- links to related software, models or documentation;
- specific questions about FAIR readiness or repository publication.
Expected outcomes
Depending on the request, the outcome may include:
- FAIR readiness comments;
- identification of missing metadata fields;
- recommendations for improving README and documentation;
- recommendations on file structure and manifest preparation;
- comments on licence and access conditions;
- recommendations on identifiers and links to related resources;
- recommendations for improving metadata interoperability;
- suggestions for controlled terms or domain-specific metadata;
- recommendations for DataverseUA publication;
- recommendations for OpenAIRE or EOSC compatibility;
- a practical list of next steps for the research group.