Research Data Management (RDM): Organise and Access

By establishing some simple, effective data practices early in your project you can make your data files easy to store, find and use.

This page includes information on data formats, file and folder naming and management, data security and documentation and metadata.

Your choice of file format will affect the usability and long term accessibility of your files and data. As technology changes, you should also plan for both hardware and software obsolescence.

File formats more likely to be accessible in the future have the following characteristics:

• Non-proprietary
• Open, documented standard
• Common usage by research community
• Standard representation (ASCII, Unicode)
• Unencrypted
• Uncompressed

Examples of preferred file format choices include:

• ODF, RTF or TXT, not Word (.doc or.docx)
• ASCII, not Excel (.xls or .xlsx)
• MPEG-4, not Quicktime
• TIFF, PNG or JPEG2000, not GIF or JPG
• XML or RDF, not RDBMS

If you are using proprietary software consider migrating your data into a format with the above characteristics, in addition to keeping a copy in the original software format.

• Further guidance can be found from the University's Modern Records Centre
• Cornell University has published a guide on common file formats

It is essential during your project that you have plans in place to ensure the safe storage of your data as well as a strategy for regular backups.

If you are storing your data in the University’s storage options, they are automatically included in the main IT Services backup processes - this can be an easy way to cover all your backup requirements. The University also has guidance on the selection and use of external cloud services for storing data - generally they are not recommended, particularly when personal data may be handled and servers cannot be guaranteed to be physically located in the UK (as required by some projects!).

Data security considerations include both physical practices such as ensuring a safe environment in which to work and digital security such as passwords and ensuring that access is limited to the appropriate people.

Physical security

When you are working on your project, you should always consider your surroundings.Think: are you able to work in a private environment when necessary? Is there anyone looking over your shoulder at sensitive information?

Similarly, you should consider where your devices and notes are stored. Can anyone else access them?

Lastly, while seating in shared work areas such as the Library can be limited at certain times of the year, it is never a good idea to leave your belongings unattended!

Digital security

While most devices are password-protected, the strength of your password depends on its uniqueness and length. Your password should be hard to guess, contain a variety of character types, and should not be reused across devices or accounts.

The University has guidelines and advice for improving your digital security.

If you believe that your account has been compromised, you should contact IT Services urgently - this can be done by phone: 02476 573737. Alerting the helpdesk quickly will help to minimise damage and remedy the situation. 

Some data centres apply physical access conditions to their datasets. The University of Warwick provides a SafePod, enabling local researchers to access many such datasets in the University of Warwick library. Examples of data providers which can be accessed using the SafePod include:

• The Office for National Statistics Secure Research Service
• The UK Data Service
• The SAIL Databank
• Linked datasets created by Administrative Data Research UK projects

As of November 2025, the Luxembourg Income Study has joined the SafePod Network, adding almost 1000 new datasets from:

• The Luxembourg Income Study Database
• The Luxembourg Wealth Study Database (LWS)
• The ERF-LIS Database.

A plan for the storage of research data is essential, both for the short and long term. The short term plan considers how to store data during research, whereas the long term plan identifies how and where to store data for archiving and future reuse after research activities end. For short term, IT Services offer a flexible data storage service with backup. Check Preserve & Share for advice on longer term preservation and access.

Starting a project with a strategy for the consistent naming of both files and folders and creating appropriate file and folder structures will save time, avoid loss of data, allow re-use of the data, and assist in accurate location of data in the future. Names should be objective, meaningful and standardised to allow for other users (or yourself in the future!) to make sense of them. Useful information in file names includes the date the file was created, subject of the file, and version number

• The University of Warwick has Top Tips for records management
• Jisc Digital Media has a guide on choosing file names
• UK Data Service advice for naming and structuring research data files
• UK Data Service recommended file formats
• Library of Congress recommended formats statement (digital and non-digital formats)

Below is an example of a possible file structure template which separates a project chronologically into experiments.

Using the University of Warwick's departmental shared folder for your research project (also known as the M: drive) permits collaborative working with other researchers within the institution. Files and folders can be selectively shared with others to ensure that appropriate limitations are in place.

Good documentation for your data is like creating a ‘user’s guide’ to the data and helps make data understandable, verifiable and reusable. Just making the data available does not make it useful, if you or others come back to your data at a later time later it is helpful to have time they will need information on when, why, how and by whom the data was created.

Research funders often require the open access publication of research data metadata to facilitate the location discovery and reuse of datasets. Documentation and metadata about a dataset is often mentioned together but can be very different things.

Documentation

Documentation for a data collection or dataset includes high-level information on the research context and design, the data collection methods used, plus summaries of findings based on the data.

Documentation deposited alongside data files should enable users, with no prior knowledge of the research project and data collected, to understand what the data mean and be able to use the data correctly in their own research projects.

Metadata

Metadata are intended for reading by machines, and help to explain the purpose, origin, time references, geographic location, creator, access conditions and terms of use of a data collection. This allows data collections to be discovered for re-use and/or citation.

Further information and examples of best practice in documenting data can be found at UK Data Service.