Have a Plan

First, if you haven't done this already, you should create a data management plan.

Backups

  • Install Google's Backup and Sync (but disable the Sync).
    • This will backup your Desktop and Documents by default, you can add additional folders and external drives (like thumb drives).
  • Install Google's File Stream (this won't take up space on your computer).
    • Note: you can select folders in your "GoogleDrive" to keep "Available Offline". Very handy both to improve speed and to allow access when traveling.

Places to Store Your Data

  • Google Drive (via Google's File Stream)
    • Good for long term storage, sharable, unlimited storage!
    • Slow, don't expect your Python script to process your data very fast if it is in your Google Drive.
  • MCDB's file server (or your department's file server if you aren't in MCDB).
    • Accessible via SMB and SSH. Lots of storage.
    • Ask your PI to send Erik an email requesting access for you.
  • Research Computing's storage.
    • This requires an account and some money. Only accessible via SSH.
  • An external hard drive.
    • Fast and effective storage for lots of data (up to 14TB on a single disk at the moment).
    • Portable, don't forget to backup!
    • Handy place for your data while processing with your Python script, etc.
    • An inexpensive way to do this is to buy an external hard drive docking station and a couple BIG hard drives.

Ways to Collaborate and Share Data/Files

  • Share a Google Drive Folder
    • Ask your Mentor or Colleague to share a folder with you. Then, in the Google Drive web interface, drag that folder to your "My Drive". You can then collaborate on your projects together via this folder in your Google Drive File Stream (that you setup per the suggestion above).
  • Use a Google Team Drive.
  • Globus Connect
    • Very fast data transfers, good for sending terabytes of data.
    • Contact Erik for details.

Publish Your Data

There are many places to publish your data, two possibilities to consider:

Be sure to consider data publication when making your Data Management Plan!