Optometry Digital Literacy Toolkit

Describe Research 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

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).

DataONE

The DataONE collaboration has a succinct information sheet about metadata for research data.

They also offer suggestions for best practice in these areas:

• Assigning descriptive file names
• Create a data dictionary
• Describe the research project
• Why data values should be kept separate from annotations
• Describing units of measurement
• The importance of documenting data processing workflows
• Why data typing should be consistent
• The need for consistent coding and how to establish this

Further Help

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