I’m wondering if there is an updated way of archiving workspaces instead of projects? I often have many workspaces in one project, and I would rather archive those workspaces to save disk space rather than archiving my projects. I saw this previous discussion (Exporting a Workspace instead of the full project?), where it looks like I could make a project specifically for archival, and then export the project I want to archive to the “archival project”, but that seems to be a bit complicated.
I prefer to work with multiple workspaces inside of one project instead of giving every single data collection its own project, but am I setting up my projects outside of the norm? Thank you for any help you can provide!
There are benefits to doing it either way. I would suggest making more projects instead of more workspaces primarily because the GUI slows down considerably after a couple thousand jobs in a project regardless of how many workspaces, but there does not seem to be this limitation if data are spread across projects. The drawback is that you have to create project folders, and you can’t share job info/templates/volumes etc as easily across projects.
I don’t know if there are norms, but there are certainly trade-offs.
Previously in our facility we did 1 dataset = 1 workspace, and projects corresponded to an individual structural target. That was nice because you can link jobs together, and share common resources, as CryoEM2 mentioned. The downside was that archiving became extremely difficult (when are you really done trying to get a structure of a target?), and routinely expanding our cloud file-system (FSX) became time-consuming and prohibitively expensive.
Now we do 1 dataset = 1 project so that we can easily archive the dataset and move all the generated files off the filesystem. It’s pretty fine. Using an import job to move resources between projects is slightly more annoying than linking jobs between workstations (especially for users who are unfamiliar with UNIX filesystems and the cryosparc project directory structure) but it’s worth it for our purposes.
I hope cryoSPARC’s improved data management tools arrive soon!