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What is research data management?

Research data management

Research data

Research data is all of the information that has been created and/or collected to use in research, irrespective of format. The primary purpose of research data is to provide the information necessary to support or validate a research project's observations, findings, or outputs. Research data may include:

  • spreadsheets
  • documents
  • questionnaires
  • transcripts
  • surveys
  • photographs
  • audio or video recordings
  • simulations
  • software/code

Research data are the evidence that underpins the answer to the research question, and can be used to validate findings regardless of its form (eg, print, digital, or physical). These might be quantitative information or qualitative statements collected by researchers in the course of their work by experimentation, observation, modelling, interview or other methods, or information derived from existing evidence. Data may be raw or primary (eg, direct from measurement or collection) or derived from primary data for subsequent analysis or interpretation (eg, cleaned-up or as an extract from a larger data set), or derived from existing sources where the rights may be held by others. Data may be defined as ‘relational’ or ‘functional’ components of research, thus signalling that their identification and value lies in whether and how researchers use them as evidence for claims.

Concordat on Open Research Data (July 2016)

Research data management

Research data management is the term used to describe the management and curation of research data both throughout the research project and beyond. It usually includes the following elements:

  1. Advanced planning prior to the start of a research project.
  2. Implementation of good data management practices during the project.
  3. A long-term strategy for data preservation and sharing at the end of the project.

Why is research data management important?

There are many benefits to managing your data. Research data are fundamental for research and underpin published results, with good quality data producing good quality research. Therefore it is extremely important that the data are managed effectively.

Good data management:

  • helps to protect against data loss or corruption
  • ensures that the data remain accurate and reliable
  • increases transparency of the research process
  • enables validation of published results
  • facilitates data sharing and re-use
  • increases your research productivity and efficiency
  • ensures compliance with ethical codes, data protection laws, funder and institutional requirements