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Research Data Management

This guide will assist researchers in planning for the various stages of managing their research data, implementing best practices for managing research data, and in preparing data management plans required with funding proposals.

What is Research Data Management?

Research data management (RDM) is a phrase that describes the process of organizing, storing, preserving and sharing the data collected and used in research. It encompasses the day-to-day management of research data collected or created during a research project as well as how that data will be preserved and shared after the project is completed.

Why is Research Data Management Important?

Many institutions, funding agencies, and journals have requirements regarding research data management.

Additionally, good research data management will: 

  • ensure the integrity of the data.
  • save time in the collection, description, analysis, and reuse of the data.
  • make the data findable and usable to all parties involved in the project.
  • help those outside the project understand the data.
  • aid in the verification of results and reproducibility of the research. 
  • facilitate the sharing of the data within and across disciplines, accelerating other's research. 
  • ease the process of archiving and preserving data over the long term. 
  • encourage data citation to increase the impact of the research and improve author citation counts.


image of the research life cycle

Image source: The University of California, Santa Cruz, Data Management LibGuide, Research Data Management Lifecycle, diagram, viewed 21 February 2020 <>  

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