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Research Data Management: Organising data

Organising files and data

Why is it important to organise files and data?

Finding data that you or your collaborators have created can be challenging as your data and files increase over time.  

Organising your data effectively can help you identify, locate and use your research data files efficiently and effectively. 

Organising your files in a logical and consistent way will save time by helping you and others find the correct files, prevent errors and enable reproducibility.
 
Top tips
  • Use any existing conventions, for example, in your research group, department or faculty  
  • Agree on a consistent convention for naming files and folders.
  • Create a logical folder and sub-folder structure and file data accordingly
  • Name your folders so that they are meaningful to yourself and others
  • Create separate folders for current/ongoing and completed work
  • Don't keep everything. Consider what you need to retain and for how long
  • Review your files at regular intervals

File naming

Why are filenames important?

  • Good practice dictates that all information (files, datasets, documents, or records) should be identifiable and traceable.

How should I format a filename?

  • A filename is the chief identifier for a research data file. Using agreed and consistent conventions to file names can help prevent confusion, particularly when multiple people are working with the data.  
  • The filename should include as much descriptive information as possible to assist identification.

Key elements to include in your file name include:

  • File name, or full file path 
  • Name/role of file author(s) or originator(s)
  • Date of creation, edit or event which is the subject of the document/file
  • Version number if applicable

Version control

Why is version control important?

Version control involves a process of naming and distinguishing between a series of draft documents which lead to a final (or approved) version.

It is important for:

  • Documents that undergo a lot of revisions
  • Collaborative documents that are being changed by a number of different users
  • Tracing and auditing the development of a document
  • Avoiding conflicting document versions

Top tips

  • Follow naming conventions (see file naming)
  • Include version numbers in the file name
  • Identify on the document (e.g. header/footer), the author, filename, page number and date of creation/revision
  • Give read-only status to definitive versions to allow changes to be controlled

Describing data

What is metadata?

• You can describe your work by assigning metadata.
• Metadata is "data about data". It is used to summarise basic information about data and describe or contextualise the data. 

Why is metadata important?

It is important to clearly describe your data to ensure it can be:

  • Searched for and found
  • Understood by any user now and in the future
  • Properly interpreted

Research funders require researchers to create and make metadata openly available.

The key question to ask yourself is

“what information would I need to understand and use this data in twenty years?”

Further information

Metadata examples and links to descriptive standards can be found on the University of Leicester metadata and documentation page

Documentation

What is meant by documentation?

Documentation may sit alongside metadata. This refers to all the information necessary to interpret, understand and use a given dataset, a set of files or a single document.

How should research data be documented?

Research data need to be documented at various levels:

  • Project level: e.g. what the study set out to do, contribution to new knowledge, questions/hypotheses, methodologies, sampling, instruments and measures etc.
  • File or database level: e.g. how all the files that make up the dataset relate to each other, format, superseding or superseded etc.
  • Variable or item level: A full label explaining the meaning of a variable in terms of how it was operationalised is recommended.

Further information

For more information about on documenting your data see the UK Data Archive.

DMU Policy

Policy on Managing Research Data at DMU

"De Montfort University is committed to research excellence and integrity and seeks to promote high standards of research data management throughout the research data lifecycle." 

DMU RDM Training

 

Click to go yo the DMU Research Data Management Course