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Data Management Guide

An overview for researchers on how to collect, manage, organize, and preserve data at all stages of the research process.

Why Manage Research Data?

Research Data Management describes all of the ways researchers collect, analyze, store, and use data during a project. It includes writing and following lab procedures, keeping backups of hard copies and digital items, and thinking ahead about how these data may be re-used or re-purposed.

So why manage your data? 

  • Increase your impact. Making data freely available to other researchers can boost the reach and relevance of your results. 
  • Save time and money. Having a data management plan means you've already thought about how your data will be shared and preserved long-term—so you don't have to convert, clean, or reorganize your datasets at the end of a project.
  • Safeguard your work. Placing your data in an repository means you are no longer responsible for making sure it stays complete, uncorrupted, and accessible.
  • Aid future research. Careful management and documentation of your data will make it possible for you and other researchers to understand, replicate, and re-use it.
  • Promote new discoveries. Your data may have uses beyond the scope of your original research proposal. Sharing data turns your research results into part of an ever-growing dataset for other researchers. 
  • Comply with funding requirements. Obeying public access mandates is part of the grant reporting process, and can affect whether you receive additional funds. 

Introduction to Data Management

Data Sharing and Management Snafu