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Research Data Management: Getting Started

This is a guide to best practices for managing your research data

What is data?

Every discipline has data. Research data that should be properly managed include both quantitative and qualitative data.

Types of data include: 

  • Laboratory experiment data
  • Observational data
  • Raw data generated from instruments
  • Interviews
  • Transcripts
  • Statistics
  • Figures
  • Code
  • Computer simulation
  • Textual Analysis
  • Physical artifacts


This guide overviews stages of data management:

Additionally, this guide includes federal funding requirements for data sharing.

Why should I manage my data?

Increase your research impact
Sharing your data can increase your research's discover ability and relevance. There is also a citation advantage for researchers who make their data openly available.

Save time
Planning for data management will save you time and headaches in the future.

Meet grant requirements
Many funding agencies now require that researches properly manage and share the data collected for a funded research project.

Preserve your data
Depositing your data in a data repository protects your research time and preserves your research contribution for you and others to use.

Maintain Integrity
Managing your data throughout its life cycle will ensure that you and others can understand use the data in the future.

Data Sharing and Management Snafu

Don't let your data overwhelm you!

CC BY 2.5 Denmark license
Illustration by Jørgen Stamp.

Data can feel overwhelming, but with a strong data management plan you will be organized and confident in the management of your data.

Follow this guide and learn how to organize, document, store and backup your data, and how to draft a data management plan.