Research Data Management Services
ZIH offers services for research data management around the research data life cycle. Hereafter, we have listed our offers briefly, links refer to the websites of the individual services.
For more information and support on these topics, please contact the Service Center Research Data.
Store and manage data
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The home directory can be used as a central place to store data in form of folders and files. It includes an automated backup.
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Several people (e.g. a workgroup) can store their files in a group drive. The access rights to files and (sub)folders, can be defined individually. Snapshots allow access to older file versions. Daily backups are available, too.
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In a backup, data in use is regularly saved so that it can be restored in the event of loss or error (e.g. accidental deletion, malware infestation or hardware errors).
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Files and lists can be conveniently stored in Sharepoint and provided with automatic workflows. A wiki function is also available.
Share data
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Files can be stored in the Cloudstore and shared with others (including non-TUD members). Please be aware that there is not backup available.
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The focus of Sharepoint is on the storage and (shared) editing of documents, but any other files can also be stored. Sharepoint allows to arbitrarily define access rights for groups and persons.
Processing and analyzing data
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Various software packages for data processing, analysis or visualization are available on our high performance computers. Examples are Matlab, Paraview, Big Data frameworks like Hadoop or Tensorflow for Deep Learning. Consulting regarding Big Data and Artificial Intelligence is provided by ScaDs.AI.
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The Research Cloud offers an easy way to quickly get resources for processing data in form of (individual) virtual machines. Enterprise clouds can be used if there are high availability requirements.
Archiving and publishing data
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Data can be intermediately archived in the intermediate archive for the duration of a project run time.
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OpARA (Open Access Repository and Archive) enables the long-term archiving of research data (e.g. for 10 years as required by the DFG and TUD) and, if desired, its publication with a DOI (e.g. for referencing the data in a paper).