Managing data is an integral part of the research process. How you manage your data depends on the type of data, how the data is collected, and how the data is used throughout the life of the project. Effective data management helps you organize your files and data for access and analysis. It helps ensure the quality of your research and supports the published results of your research.
The remaining pages in this section outline best practices throughout the research lifecycle. To get help with strategies for any part of the lifecycle, consult with us.
Research data management lifecycle. Though the process is generally linear from "Plan & Design" to "Publish & Reuse," you may find yourself jumping around this lifecycle throughout your project.
| Research lifecycle stage | Best practices and associated resources |
|---|---|
| Plan and design | |
| Collect and create | |
| Analyze and collaborate | |
| Evaluate and archive | |
| Share and disseminate |
Tutorials
Databases
- Introduction to SQL from Library Carpentry or Data Carpentry (approx 4h)
- Microsoft Learn, LinkedIn Learning resources
Data management
- Earth Science Information Partners (ESIP) data management training clearinghouse
- DataONE Data Management Skillbuilding Hub - community resources for data management education
- MANTRA: Research Data Management Training - free online course covering data management plans, organizing data, file formats & transformations, documentation, metadata, and citation, storage & security, data protection, rights & access, and sharing, preservation & licensing.
Open and reproducible science
- Mozilla Open Data Training for Instructors - Learn how to teach about open science
- Open Science: Sharing Your Research with the World (4 week MOOC) - Explore ways to apply Open Science principles to academic work - including your own. Learn how to share your research effectively and responsibly, building greater visibility and impact