Skip to main content

Research Data Management Basics

Data management is an important part of the research life cycle. This guide covers best practices and resources.

Research Data Management Steps

Use this guide to learn best practices for managing research data. See recommendations on how to:

  • Write Data Management Plans to meet funder mandates and to help plan a project.
  • Document Data through the creation of codebooks, data dictionaries, lab notebooks, metadata, and related forms of documentation.
  • Organize & Name Files by following structured naming and organizing guidelines.
  • Store & Backup your work through recommended practices for proper and reliable storage, access, and security. 
  • Archive & Share results in research repositories. Your work will be indexed by services such as Google Scholar. When your work is free and easy to find, it is more likely to be read and cited by other researchers.
  • Access Data Management Tools, handbooks, and guides for more in-depth instructions.
  • Access Research Policies & Support to find out where you can get data management help, research support, and information about research policies at George Mason.

Open Science Framework

The Open Science Framework (OSF) has features that enable efficient, organized research projects. You can manage and share research through the OSF platform.

There's no need to create a new account. Sign in using your George Mason username and password.

OSF for Institutions (osf.io/institutions/gmu/) 

This service is supported on campus by Research Development, Integrity and Assurance (RDIA), The Office of Research Computing (ORC), and University Libraries. Users should abide by all requirements of Mason's Data Stewardship Policy including not using this service to store or transfer highly sensitive data or any controlled unclassified information. For assistance please contact Wendy Mann, Director of Mason's Digital Scholarship Center.

Questions? Contact datahelp@gmu.edu

Related Guides

Data Citation: Follow data citation rules and examples described on this guide. Citing data sources is just as important as citing other sources used in research.

Data Services' handouts on using syntax to manage data.

Acknowledgements

A big thank you to Jen Doty from Emory University Libraries, Sherry Lake from UVa Libraries, and Katherine McNeill from MIT Libraries, for permission to re-use their content.