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Optometry Digital Literacy Toolkit

A toolkit to assist Optometry students with developing personal digital literacy capacity

Describing the Data

Part of good data management practice is the use of consistent, logical and documented descriptions of the data. This enables easier analysis and re-use.

Documenting these features will make things easier whether the research is being done solo or, especially, in a team:

  • Is there documentation about how the data was collected and/or created?
  • Is there documentation explaining the terms used to label and describe the data, including definitions, codes and abbreviations?
  • Is there adequate metadata to provide context and clarity around the data?

Metadata (data about data) is important to your project during the research and afterwards. The metadata you record about your data should include details like dates, creation methods, any processing that has been applied to the data, source details, descriptions of the content, technical aspects like file formats, and access considerations (i.e.: restrictions on access).

 

Why Bother with Metadata?

Well-described data is one thing, but without the data that description is not very useful. During the research project the data must be stored somewhere, and some methods of data storage are safer and more effective than others.

This guide's Store Research Data section outlines what to take into account with data storage decisions and practices.

 

Go to Store Research Data

Go back to Data Management Plan

Further Help

Further Help

The Optometry Digital Literacy Toolkit was developed by Deakin University Library.
Please get in touch if you have any questions or feedback.