During Your Project

The University maintains a number of systems and software to support researchers with collecting, managing and enabling safe access to data.

For information on hardware and software solutions offered to St George's researchers, please refer to the IT/AV Support pages.

It is advisable to store your data on an institutional network or shared drive, which you will be allocated by Computing Services. As your project develops, you might find you need more storage space. Email the IT/AV team to discuss your needs for more active data storage.

Good documentation improves the quality, interoperability and re-usability of your data. It also makes your research processes more efficient, particularly over time.

Research can be documented with study-level documentation, data-level documentation and catalogue metadata. The UK Data Service provides a valuable summary of each of these levels of documentation with examples of the kinds of information you should include in your own documentation.

If you’re writing source code as part of your research you should also document your code. The Software Sustainability Institute provides useful advice for making your source code readable. They also have a collection of guides to help you to develop sustainable software.

You should use community-agreed documentation standards, controlled vocabularies, protocols, or good practice where these exist. Documentation standards for some common data types include:

• CDISC, which maintains a range of data standards for clinical research
• INCF , which provides a suite of standards and best practice to support open and FAIR neuroscience 
• the OME Model , a specification for storing (meta)data on biological imaging
• the UK Data Service metadata guidelines will help researchers in the social, behavioural, economic and health sciences to document their data. 

FAIRsharing.org maintains a searchable list of documentation standards for a range of data types.

Contact the research data management service if you need help locating standards that best suit your research areas.

Researchers are responsible for managing their data according to community standards for quality assurance and quality control (QA/QC).

Generally, producing clear documentation and working to standard operating procedures (SOPs) and protocols will help you to create better quality data regardless of your field.

The UK Data Service provides good examples of QA/QC processes that could be applied to a range of data types.

The World Health Organization’s (WHO) Quality practices in basic biomedical research handbook offers good guidance for addressing quality in non-regulated, basic biomedical research.

There are a number of quality systems in place for regulated research, including Good Laboratory Practice (PDF) and Good Clinical Practice for pre-clinical and clinical studies respectively. Researchers conducting regulated research should be aware of their responsibilities regarding data quality and reliability. Visit the JRES governance pages for more information.