In MRI research, data typically comes as a set of DICOM files which need to be first converted to a data format convenient for visualization and analysis, typically NIfTI. Another step further is to layout and organize the data according to BIDS (Brain Imaging Data Structure). One of the tools available to assist with such conversions is HeuDiConv (Heuristic DICOM Converter), which also has an option to place converted data and pre-generated templates under DataLad's control. This makes it immediately possible to distribute collected data across processing infrastructure, track provenance of derived data, and also updating datasets with more of freshly acquired data while relying on git's powerful merge mechanisms.
Whenever the data are ready for public sharing, it is a datalad publish away, while also allowing to to easily control and restrict the public release to only data files which do not carry any possibly subject identifying information (e.g., non-defaced high-resolution anatomicals).