This model provides a high-level view of data—from conception through preservation and sharing—to illustrate how data management activities relate to project workflows, and to assist with understanding the expectations of proper data management. In applying this model to research activities, researchers can ensure that data products will be well-described, preserved, accessible, and fit for re-use.
The tabs to the left will walk you through the foundational aspects necessary for adopting data management practices, but below are some quick tips. The best practice when starting to practice data management is to have a plan of action and create a habit. If these recommendations seem like too much, try to adopt one new good habit every month.
Writing a High Quality Data Management Plan
Read your funder requirements carefully and address everything they ask you to. Then follow your plan.
Have a consistent system and make sure everyone knows it. Don't use spaces or special characters in file names.
Creating and Using Spreadsheets or CSV Files
Columns are for variables, rows are for records. Label your columns and use consistent terms between records. Don't use color or leave cells blank.
Have roles and responsibilities clearly defined up front. Make sure you save new versions of files when changes are made.
Document Your Data Using Codebooks, ReadMe Files, and Data Dictionaries
Give at least enough information that future you, a new lab member, or another researcher could make sense of your data.
Share! And share your documentation so the data is useful. Repositories are the most effective way to share. Find an appropriate repository here or ask us!
Storing and Backing up Data
Follow the 3-2-1 Rule: 3 copies of your data stored on 2 different types of media with 1 copy in an offsite location. (0 of these copies should be on a flash drive) Want to know more? Watch one of these videos from Explaining Computers or University of Wisconsin Milwaukee.
Archiving Data for Preservation
Use sustainable file formats whenever possible and migrate your data to new media every 3-5 years.
Grateful acknowledgement to the University of Pennsylvania Penn Libraries for their permission to use and modify their template: Data Management Resources