© 2019 RNS Data Analysis & Surgical Outcomes Unit

RESEARCH DATA MANAGEMENT

What is Data Management?

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

One such purpose is “outcomes research”. Clinicians should have:

  • a clear and concise project protocol

  • specific project timeline plans (including milestones)

  • a research data management plan, and

  • an ethics application where relevant

Optimal management of data for research projects ensures that the data collected is relevant and sustainable. This means it will be appropriate for use now and in the future. For data to be useful for both current and future researchers it needs to be well planned and well described.  

Why manage data?

Data management is good research design made practical. Good data management is the back bone of good research methodology. 

  • Better data management = lower errors in research

  • Lower errors means more meaningful research, i.e. more robust conclusions and hence more useful research results

  • Good data management = good research design turned into practical systems

The research data life cycle

The research data life cycle separates the research process into stages, and in each stage different research data management practices must be implemented.

The University of Sydney Library has further information, guidelines, training and other resources available on their website to help with each of the stages of the research data life cycle:

https://library.sydney.edu.au/research/data-management/index.html

Plan & Fund

Collect & Analyse

Preserve & Store

Publish & Share

Discover & Re-use