Use case: Remote pyaims processing with remote datasets #8
Description
Name: remote_process_remote_dataset
Author: Joël C.
Summary: The dataset lies on the remote storage platform. The aims utilities lie on the remote computing plateform. The non-developer user implements pyaims-based processing step on the remote computing platform. The result is stored on the remote storage platform
Description:
Participants: advanced users to get for example deep learning projects running that use as a first step pyaims processing
**Datasets:**datasets of the size of UK biobank (~ 500,000 subjects)
Data flow:
Input data is on the storage platform. Client side of the project is setup on the computing platform. Processing can be performed in GPUs on the computing platform
Security:
Linking the use of each dataset with the authorization to be provided by the external dataset provider. Separate the access to the csv file and the access to the data, generally linked to different kinds of authorization
Workgroup(s): pipeline, security