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Core principles of Research Data Management

This page provides an overview of the core principles of Research Data Management.
Two mechanical hard drives sit on a table
© University of Hull

Research data management (RDM) will be helpful for you to consider, no matter the stage of your research project. Generally speaking, however, the earlier you reflect on data management and how you will manage this, the easier it will be to manage your project.

Good data management practices are essential in research, to make sure that research data are of high quality, are well organised, documented, preserved and accessible and their validity controlled at all times. Well-managed data are easily shared and can thus be used for new research or to duplicate and validate existing research.

RDM needs to be planned early in a project (or beforehand), so that practices can be implemented throughout the research cycle.

UKDA Research Data Lifecycle

This text and graphic has been adapted from the UK Data Service’s training materials for ‘Preparing and Managing Data’. The UK Data Service is funded by the Economic and Social Research Council (ESRC) to meet the data needs of researchers, students and teachers from all sectors.

What counts as ‘data’?

RDM is not just for scientists! Research ‘data’ (or ‘material’) comes in many forms. For instance:

  • Diaries
  • Audio recordings and transcripts
  • Lab/field notebooks
  • Search histories
  • Photographs and videos
  • Source code
  • Bibliographies
  • Survey responses
  • Specimens and samples
  • Quotations
  • Test results
  • Models

Why not reflect on your most recent (or upcoming) research project and consider what data you may produce

Creating a Data Management Plan (DMP)

Planning ahead for the collection, security, preservation and dissemination of your research data is key to successful data management. You are likely to find that your university and/or faculty provides guidance on creating a DMP. It may be a required aspect of your ethics processes.

If you intend to collect from human participants, your Data Management Plan should outline your strategy for complying with data protection regulations and standards. If your data is anonymised effectively it can be made public as a research output from your project, with your participants’ consent.

Many research funders specify that a DMP must be submitted with any grant application. They may provide a template, and/or set specific terms and conditions for the preservation and distribution of your data. Check your target funder’s data management policy before you start preparing a DMP.

© University of Hull
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