Knowing how to manage, share, and protect your research data is crucial to your academic and professional success.
Follow us during Love Your Data Week, Feb. 8-12. We will guide you through five activities to help get your data organized, secure, and ready for write-up, sharing and reuse.
GOOD PRACTICE
Follow the 3-2-1 Rule:
Keep 3 copies of any important file (1 primary, 2 backup copies)
Store files on at least 2 different media types (e.g., 1 copy on a hard drive and a second on tape or in the cloud)
Keep at least 1 copy offsite (i.e., not at your house or on campus)
Things to Avoid:
Storing the only copy of your data on your laptop or flash drive
Storing critical data on an unencrypted laptop or flash drive
Saving copies of your files haphazardly across 3 or 4 places
Sharing the password to your laptop or cloud storage account
TODAY’S ACTIVITY
Data snapshots or data locks are great for demonstrating the provenance of your data from collection through analysis and write up. They also save you time in case you make a mistake in cleaning or coding your data. Taking periodic snapshots of your data, especially before the next phase begins (collection or processing or analysis) can keep you from losing crucial data and time if you need to make corrections. These snapshots then get archived somewhere safe (not where you store active files) just in case you need them. If something should go wrong, copy the files you need back to your active storage location, keeping the original snapshot in your archival location. For a 5-year longitudinal study, you might take snapshots every quarter. If you will be collecting all the data for your study in a 2-week period, you will want to take snapshots more often, possibly every day. How much data can you afford to lose? Oh, and (almost) always keep the raw data! The only time when you might not is if it’s easier and less expensive to recreate the data than keep it around.
Instructions: Draw a quick workflow diagram of the data lifecycle for your project. Think about when major data transformations happen in your workflow. Taking a snapshot of your data just before and after the transformation can save you from heartache and confusion if something goes wrong.