About data management

Good practice in managing your data brings various benefits for you, your fellow researchers, and the wider public. It can help make the actual research process more efficient, minimising the time spent searching for information that is being accumulated and thus helping maximise the time available for the meat of the research work. A little planning at the beginning of a project can make things much easier later on, saving work and reducing stress. It is also a key requirement by most research funders and related stakeholders. Good data management can also help make more of the fruits of a research project available to a wider audience, increasing impact and allowing researchers to get full credit for the work done.

Key benefits include:

• Research data can be shown to be accurate, authentic, reliable and complete - allowing researchers to find what they need, when they need it
• Data security is enhanced, thus minimising the risk of data loss or unintended disclosure
• Research results can often be replicated without difficulty
• Good documentation and metadata allow research data to remain comprehensible over time
• When researchers leave a research group, procedures around handover of data are clear
• Sharing, reuse and reproducibility of data is made possible
• Collaboration is facilitated
• Duplication of effort is kept to a minimum
• Researchers have a greater opportunity to boost their visibility and reputation among peers
• Funding and regulatory body requirements are met

'Data' is a very broad term, covering a wide range of type of information used in research. The nature of research data can vary widely depending on discipline, type of project, and the stage of the research process. For example, it might be:

• Textual, numerical, or consisting of images or audio-visual resources
• Qualitative or quantitative
• Structured (for example in a spreadsheet or database) or unstructured
• In a preliminary or final form
• In a digital or print format - or in some case, may include physical artefacts

The  Digital Curation Centre (DCC) offers this definition:

Representations of observations, objects, or other entities used as evidence of phenomena for the purposes of research or scholarship.

Different definitions may apply in different contexts. For example, the University of Oxford Research Data Management Policy defines the data it is concerned with as:  

The recorded information (regardless of the form or the media in which it may exist) necessary to support or validate a research project’s observations, findings or outputs, or which is required for legal or regulatory compliance.