FAIR Data Storage
Storage for Science not only provides storage ressources for large scale research data (in form of file storage via CIFS or NFS, object storage via S3 and tape), but also supports the documentation of the data with structured metadata to make it findable, accessible, interoperable and reusable (FAIR).
Data Management over the Data Lifecycle
The system supports the whole data life cycle from planning storage ressources for projects over handling hot data to publication and archival of finalized data.
Data is organized in form of datasets that can contain a set of connected files. The datasets can be moved between the different storage layers, shared with other project partners and described with documenting metadata. Links between datasets allow to document dependencies and provenance.
An interface to the data repository DaRUS allows to publish the data while keeping the describing metadata.
Roles and Responsibilities
Researchers are able to create, share and work with datasets. Metadata can be added either over the graphical web interface or by putting structured JSON files into the file system. The documentation can therefore be automated in and integrated into computational research workflows.
Research data managers choose and configure metadata schemata and create automated basic quality checks that ensure the formal quality of data and data documentation.
Project administrators handle role and rights management and administer the storage ressources.