Data Archiving
What
Data archiving is the long-term, secure preservation of research data. At this stage, the data is no longer being ‘actively’ used.
Why
Archiving enables future verification and safeguards the integrity of research. By storing raw data in a stable and accessible manner, researchers and institutions can revisit it if questions arise about methods, results, or conclusions.
Archiving is not directly part of the FAIR principles, which focus on sharing and reusing data. Nonetheless, good archiving practices - such as organized file structures and clear documentation - provide a strong foundation for later FAIRification.
Who
The lead researcher is primarily responsibility for ensuring data is archived, while the research team shares responsibility for preparing and organizing the files.
When
Archive your data at the end of your project, when no further changes are expected to be made. This can be when data collection and analysis are complete, or when results are published or submitted.
Retention requirements vary by institution, funder, and discipline. A common guideline is to preserve raw data for at least 10 years after project completion or publication, though some fields require longer retention for legal, ethical, or scientific reasons.
Where
Archive your data in the Vault area of YODA to create a read-only, long-term snapshot that cannot be overwritten or deleted, ensuring data integrity.
How
Select the data to preserve long-term, as archiving all research materials and data (especially large datasets not directly related to the project) can be practically and financially challenging.
To improve future reusability, store data in recommended formats that are non-proprietary, unencrypted, and uncompressed.