Research Data Management: About RDM

What is research data management (RDM)?

"Research data management concerns the organisation of data, from its entry to the research cycle through to the dissemination and archiving of valuable results" (Whyte and Tedds, 2011)

A Data Management Plan (DMP) will usually be created at the beginning of a research project which will cover what data will be created, how they will be organised and how they will be shared and preserved. It is increasingly a condition of research funders that a DMP is created. 

What are research data?

'Research data' are defined as: "records, files or other evidence, whether in print, digital, physical or other formats, that comprise a research project's observations, findings or outputs, including primary materials and analysed data collected from a third party" (Lyon & Pink, 2012).

Examples of research data are:

• Results of experimental work or simulations

• Statistics and measurements

• Computational models and software

• Observations e.g. data collected in the field

• Survey results, either in print or online

• Interview recordings and transcripts, and the coding applied to these

• Other audio or audio-visual material, e.g. musical or dance performances from which data are derived

• Images from cameras (including smart-phones) and scientific equipment

• Textual source materials and annotations

It does not include data collected for research administration purposes, such as returns to the Higher Education Statistics Agency (HESA) and the Research Excellence Framework (REF).

Why manage data?

There are many reasons why managing your research data is important:

• Research integrity - RDM is a way to assure research integrity and avoid reputational risk, for yourself and the institution
• Legislature/Regulatory compliance - RDM makes it easier to comply with Data Protection legislation and Freedom of Information requests
• Compliance with funders - Increasingly funders require data management plans at the grant application stage or shortly after a project has started
• Avoids the risk of data loss and ensures data is kept securely
• Easily find and access your data over the lifespan of the project
• Data is backed up, providing long-term preservation

• Public interest - If research is publicly funded then, in the same vein as open access to research articles, the data should be made openly available if possible
• Increased academic impact - Research has shown that sharing data increases the citation rate for research papers
• Increased research impact – sharing data means it can be used in new and innovative ways, eg by businesses, community groups, other researchers, to effect change
• Share data with other researchers to enable re-use or to reproduce your results
• Enable collaboration and potential further research
• Reduce duplication of effort

UK Data Archive: Collection of digital research data in the social sciences and humanities and help for creating and managing your data.

Data Documentation Initiative (DDI): An international standard for describing the data produced by surveys and other observational methods in the social, behavioral, economic, and health sciences.

MANTRA Research Data Management training: Free online course produced by the University of Edinburgh

The Digital Curation Centre (DCC):Centre of expertise in digital curation.The DCC provides expert advice and practical help in storing, managing, protecting and sharing digital research data.

Information on this guide has been informed by various sources including:

Whyte, A., Tedds, J. (2011). Making the Case for Research Data Management
University of Sheffield Why this affects you 
University of Oxford About RDM