Management of scientific data, including consistent organization, annotation and storage of data, is a challenging task. Accessing and managing data from multiple workplaces while keeping it in sync, backed up, and easily accessible from within or outside the lab is even more demanding.
To minimize the time and effort scientists have to spend on these tasks, we here present the GIN (G-Node Infrastructure) services [1], a free data management system designed for comprehensive and reproducible management of neuroscientific data.
GIN keeps track of changes to the contents and structure of files and folders, and provides secure remote access to the data. More specifically, once a directory has been put under GIN control, the contents will be synced to a dedicated GIN server. With proper authorization, data can be accessed and changed from remote clients, making it easy to work from multiple workplaces while keeping all data and code at hand and in sync.
Data can be managed from web and file browsers as well as through a command line interface, which enables integrating data management and access into the data acquisition and analysis procedures.
The system handles any kinds of directory structures and file types, and tracks all changes, using Git [2] and Git-annex [3] tracking mechanisms. This supports reproducible data workflows and in particular keeps previous versions accessible when datasets are updated. The service furthermore makes it straightforward to share any data within a lab or with off-site collaborators and to work on it in parallel.
Supported by BMBF (Grant 01GQ1302) and the Bernstein Center Munich
[1] https://gin.g-node.org
[2] https://git-scm.com
[3] https://git-annex.branchable.com
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