synapse-upload-workflow

To upload files to Synapse data collections, this workflow automates transferring datasets from local directories or cloud storage like S3, GCS, and SFTP directly into specified Synapse data collections. It handles multi-path uploads and maps files to collection specifications.

Yes, uploading large medical imaging datasets to Synapse is fully supported. The workflow automatically maps DICOM files and JSON labels to specifications, groups them into data units, and integrates patient metadata from Excel files for enhanced data organization.

Yes, the Synapse upload workflow validates metadata against schemas before registering files. It ensures data integrity by checking prerequisites, exploring source directories, and organizing files according to data collection specifications prior to registration as data units.

The best way to organize files for Synapse data collections is using an automated workflow that intelligently maps source files to specifications, groups them into data units, and prepares metadata, ensuring proper validation and registration without manual intervention.

Yes, you can automate multi-path uploads from cloud storage buckets using this Synapse SDK workflow. It validates prerequisites, explores source directories across S3, GCS, or SFTP, and registers uploaded files as data units within Synapse data collections.

When uploading large datasets to Synapse, the workflow requires validated prerequisites and properly structured metadata schemas. Files must be correctly mapped to data collection specifications, and source directories must be accessible from local or cloud storage paths.