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Research Data Management - Research Guide

Data Management

Data Collection

You may collect and retain data throughout your research project.

It is important that you design your data on the understanding/assumption that it will be shared:

  • When creating data, describe it as you go - make sure you document sources, methods and reagents so that others will understand. 
  • Always document terminology and acronyms at the time of data collection, so that the meaning is clear.

File Management

When naming files, try to include:

  • name of creator
  • short description
  • version
  • anything else that will be important in recognising the file

This seems like a lot of information, but it can be achieved with initial or codes. For example: 20201016_RDM_ CF_PPT_v2NewFormat.ppt

If this becomes complex, use a readme.txt file to record the system.

Some other recommendations:

  • Create unique file names
  • Use a version scheme: V1, v2, v3...
  • Incorporate descriptions to indicate why the version is different
  • Be descriptive but concise
  • Include a date in ISO8601 format YYYYMMDD
  • Use leading number for dates so that you can sort chronologically
  • Use underscores instead of spaces
  • Avoid special characters
  • Remember that some operating systems are case sensitive

Data Storage

You will need to ensure that your research data is stored securely for the life of the project and for any required retention period. Research funding bodies may mandate where research data must be stored including institutional, national or international repositories.

When deciding on data storage and access, always consider how sensitive the data is. Care should be taken when storing all sensitive or confidential data, especially if it relates to research with human subjects.

Store your data in more than one place and in more than one medium. Storing your data in multiple places and mediums ensures that data files can be restored, if they are corrupted, damaged or go missing.

Store the data in a format that is machine readable, avoiding proprietary formats if you can.

If your data can be shared, consider storing your data in a data repository or archive.