Data Management

Data Management and Bio-Statistical Support

The following information and resources are provided as a guide to managing research data. It is intended for staff and students working, learning and conducting research in the SLHD.

What is Data Management (DM)?

Data management is the practice of planning, collecting, organising, storing, checking, maintaining, using and sharing your data so it is  ‘fit for purpose’.

This means you as a researcher need to be very clear about the purpose of your research. You should have:

  • a clear and concise project protocol
  • project timeline plan (including milestones and so on)
  • a research data management plan and
  • an ethics application where relevant

Optimal management of your data and research project ensures that you and others can use it now and in the distant future. If your data set is to be useful, both to you and to other future researchers, it needs to be well planned and well described.  

Research Data Management

Why manage data?

Best Practice:

Data management is about good research design made practical. Following good data management practices will mean you also follow best practice for research methodology. Good data management practices particularly address issues of reducing non-sampling error. This is not as well known or understood as sampling error.

  • So the better the data management = lower error in your research

  • Lower error means  the more meaningful your research, the more robust your conclusions and hence the more useful the  research results

  • Good DM = Good research design turned into practical systems


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Page Last Updated: 02 October, 2019