Research Data Management Basics

An important part of any researcher's job is dealing with data. Use this guide to learn practical information and best practices for managing your project data. This guide addresses the following common tasks:

• Writing data management plans to meet funder mandates and to help plan a project.
  • Use the DMPTool to help you build your data management plan.
• Documenting data through the creation of code books, data dictionaries, lab notebooks, metadata, and related forms of documentation.
• Organizing & naming files by following structured naming and organizing guidelines.
• Storing & backing up your work through recommended practices for proper and reliable storage, access, and security. 
• Archiving & sharing 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.
• Using data management tools, handbooks, and guides for more in-depth or discipline-specific guidance.
  • Try the Open Science Framework for managing your research project components and for collaborating with research partners.
• Accessing research policies & support at George Mason University.

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.

Access DiSC's handouts and guides on specific data management techniques.

• Data Syntax and Organization
• SPSS: Managing Data
• SPSS: Data Mangement Syntax
• Stata for Theses
• Working with Data