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Research Data Management: Working on a Research Project


It is important that you store your research data in a safe and secure location, which is regularly ‘backed up’, during the course of a project.

You should not store master copies of your data in removable mediums such as your laptop hard drive, USB sticks or external hard drives. These are prone to damage, corruption and data loss. Additionally, if your data is confidential, removable mediums carrying copies of your data should be encrypted.

When planning for and conducting research, there are a number of storage and security issues which researchers need to consider. The University has clear policies and guidelines on protecting your information and data – please familiarise yourself with these.


With a little planning, you can make your data easy to find and reuse. When planning how to organise your data, you should think about certain key questions:

  • If I want to find a particular piece of data in the future, will I know where to look?
  • If I want to re-analyse a piece of data, what will I need to know?
  • If I did not generate this data, what do I need to know to understand it?

Think about what makes sense for your research. If you are conducting experimental work, for example, you might want to organise the results into folders by the date you did the experiment, or by a key experimental condition.

However you choose to arrange your files, make sure you create an index file (e.g. a text file that describes the data and how it can be used). This only takes a few minutes, but can save you answering multiple questions at a later date. 


Metadata is ’data about data’. It is information that enables users to find a dataset. This is the cornerstone of effective ‘open data’. All researchers are responsible for providing and publishing sufficient metadata and explanatory notes about their research data to ensure it is discoverable, understandable and re-useable. Metadata can also be used to justify decisions on restricting accessibility of research data and outline the conditions which must be satisfied for access to be granted.

Take a pragmatic approach to describing your data. It might be useful to imagine which information you would require if you were accessing another researcher’s data. Put yourself in the shoes of a secondary user – have you provided enough information for them to legitimately analyse your published findings and potentially re-produce your analysis?

Providing detailed and meaningful dataset titles, descriptions, keywords and other information enables data centres to create rich resource-discovery metadata for archived data collections that are searchable by all users.