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Research Data Management: Reusing Existing Data

Bringing together University resources and services to facilitate researchers in the production of high quality data.

At a Glance

Reusing existing data can be cost effective & time saving but may require significant effort to get to know the data.

Help@UCD: ISSDA Reusing Research Data

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Help@UCD: ISSDA Data Sources

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Reusing Data Pros & Cons

Advantages

  • Datasets may impossible to create within the scope of your research project
  • I can be cost effective & time saving to use data which has already been collected
  • Ethical issues about data collection have already been dealt with
  • You can spend bulk of time analysing data
  • There is a huge breadth of data available, even in an Irish context

 

Disadvantages

The main disadvantage to reusing existing data is that the data were not collected to answer your specific research questions.

  • Particular information may not have been collected
  • The data may refer to a different geographic region than you are interested in studying
  • The data may refer to a different time period than you are interested in studying
  • Variables may have been defined or categorised differently than you would have liked
  • You were not directly involved in the data collection process
  • There may have bee a low response rate
  • Anonymisation may be quite extensive, so variables you are interested in may not be available

Reusing Existing Research Data

It is essential to:

  • Check out the documentation for collection procedures, data cleaning procedures and other technical information.
  • Spend time getting to know and understanding the data.
  • Be practical about whether data are suitable (good enough) for your research.

 

Documentation helps you to understand the meaning of the data & to evaluate suitability for your research question. It can help you understand exactly what information was collected, from whom, where & when, as well as what was done to the resulting data before it was archived.

Documentation can include:

  • Study description (metadata)
  • User guide
  • Codebook or data dictionary
  • Survey questions
  • Official reports