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Research Data Management

This guide will help researchers with managing research data as well as preparing for data management plans required by funders.

What are Data?

Data are items of recorded information considered collectively for reference or analysis. According to UKRI Concordat on Open Research Data (2016): Data are "evidence that underpins the answer to the research question, and can be used to validate findings regardless of its form (print, digital, or physical)." The purpose of research data is to provide the information necessary to validate a research project's observations, findings, or outputs. 
Data can occur in a variety of formats that include, but are not limited to:
  • notebooks
  • survey responses
  • software and code
  • measurements from laboratory or field equipment 
  • images 
  • audio recordings
  • physical samples

Data can be defined in a variety of ways, depending on the discipline and the context. Specific funders may have their own definitions of data that should be consulted when making decisions about managing research data.  

What is Research Data Management (RDM)? 

Research data management describes the organization, storage, preservation, and sharing of data collected and used in a research project. It involves the everyday management of research data during the lifetime of a research project (for example, using consistent file naming conventions). It also involves decisions about how data will be preserved and shared after the project is completed (for example, depositing the data in a repository for long-term archiving and access).

Image of the Research Data Management Lifecycle

Why research data management is important:

  • Data, like journal articles and books, is a scholarly product
  • Data (especially digital data) is fragile and easily lost
  • There are growing research data requirements imposed by funders and publishers
  • Research data management saves time and resources in the long run
  • Good management helps to prevent errors and increases the quality of your analyses
  • Well-managed and accessible data allows others to validate and replicate findings
  • Research data management facilitates sharing of research data and, when shared, data can lead to valuable discoveries by others outside of the original research team
Attribution original source of diagram: The University of California, Santa Cruz, Data Management LibGuide, Research Data Management Lifecycle, diagram, viewed 7th May 2020 <http://guides.library.ucsc.edu/datamanagement>