Data life cycle: Storage
What is data storage?
Data storage is the phase in the project where data is converted moved and saved into a safe storage solution. Storing your data in a safe location, helps you manage different risks, like data breaches, loosing your data, and data corruption.
Most of the safe storage solutions have back-up systems that use a synked version of your files and store them automatically in a different location, this is in case one server fails, you can accees your data in the back-up location.
What storage solutions do I have as an ERIM member?
At EUR we have several storage solutions, depending on the type of data you are pocessing.
Storage Solution | Personal/Sensitive Data | Collaborating Outside EUR |
---|---|---|
EUR Yoda | ✅ | ✅ |
EUR Document Vault | ✅ most secure | ✅ |
EUR SURF Research Drive | ✅ | ✅ |
EUR SharePoint/Teams | ✅ | ☑️ with guest access |
EUR OneDrive | ✅ | ❌ |
EUR SURFdrive | ☑️ only personal data | ☑️ only among Dutch universities |
EUR Dropbox | ❌ | ✅ |
More information on each of these solutions can be found in the EUR tooling page. For any questions related to which tood to use, please consult the ERIM Research Data Steward via data@erim.eur.nl.
If you need to transfer data to a reseach colleague or anyone in your collaboration, please use SURFfilesender to send research data, this will ensure the safety of your data.
What should be considered for data storage?
The following considerations are important for data storage:
- When using EUR supported tools for data storage, only to a limited extent backups are made automatically. These backups are implemented to prevent data loss in case of disaster or hardware failure on the server side. Note that these backups usually do not suffice as backups for erroneously deleted or modified files.
- We therefore advice you to always arrange regular backups of your data yourself (on EUR supported tools).
- It is also good practice to separate raw data (saved as read-only) from processed data in different folders, to prevent accidental data loss.