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Research Data Management: Introduction

Research Data Management (RDM) Library guide

Introduction to Research Data management workshop

This is a recording of the Introduction to Research Data Management workshop which is delivered as part of the Doctoral College's Researcher Development Programme and the RKE Development Framework offered by Organisational Development

Outline

In this session the terms 'research data', 'open data' and 'research data management' are defined. The rest of the session is divided into three parts:

  • The benefits of good Research Data Management - why it is needed
  • Data Management Plans (DMPs) - what you need to do to get started
  • Online resources and tools available to you - where to go for support

Everything covered in this workshop is available to read or is linked to from this guide.

What is research data?

Research data means information in any format (digital or physical) that is collected or generated during research with a view to its use as a basis for research findings.

It is the evidence that would be necessary to validate research conclusions, or which may be of interest to future researchers seeking answers to new questions.

It includes:

  • Primary data collected or generated by you (the researcher or research team) for the research project.
  • Secondary data, which are existing datasets created for a different purpose and mostly owned by third parties.

What is Research Data Management?

Research Data Management (RDM) is concerned with how the data generated or collected during research is handled throughout the research life-cycle and preserved for future re-use.

The research data life-cycle model is used to illustrate how data management applies to each stage in the research process.

 

Van Den Eynden, V., 2013. Data lifecycle and data management planning. Colchester: UK Data Service. Available from: https://dam.ukdataservice.ac.uk/media/187718/dmplanningdm24apr2013.pdf [Accessed 25th October 2024].

FAIR and Open Data

This video highlights poor data practices which limit the potential uses of the data for new research. For example:
  • The data was not stored anywhere accessible. It was (eventually) found in an unlabelled box on a USB drive.
  • No back-ups were made.
  • It's in a proprietary format which can't be read without a specific programme, which is now no longer available.
  • The field names didn't make sense of the data, and there was no documentation to explain them.
  • No contact details were recorded for the co-author.
The FAIR research data management practices described in this guide would have avoided these issues, and increased the value of the data for everyone.

The FAIR principles of data management ensure that data is Findable, Accessible, Interoperable and Re-useable. Together, they aim to maximise the utility and value of research data, and they are applicable throughout the research life-cycle. All research data produced by researchers at BU should align with FAIR principles. If you are interested in finding out more about FAIR, the principles are explained in greater detail by the GO FAIR Initiative.

Open Data is data which has been made publicly available with few or no restrictions. BU is committed to the UKRI 'Common principles on data policy' to make publicly funded research data 'openly available with as few restrictions as possible in a timely and responsible manner'. However, FAIR data does not necessarily mean the data has to be open. Degrees of 'FAIR-ness' are recognised (Wilkinson et al. 2016). For example, highly sensitive and personally identifiable data may need access restrictions imposed. The common principles also recognise legal, ethical and commercial constraints. To maximise the benefits, BU operates on the principle "as open as possible, as closed as necessary" (Horizon 2020).   

Benefits of FAIR and Open Data

Benefits to researchers include:

  • Data becomes available for researchers to make new discoveries by either combining datasets or asking new questions. Good data practice avoids the difficulties highlighted in the video!
  • Increase citations! Data deposited in a research data repository is citable, and could potentially increase the profile of your work. Data citations would also demonstrate research impact.
  • It has the potential to make research easier and help to avoid disasters (such as data loss or data protection breach) by keeping data organised, secure and understandable.
  • Helps to tackle the 'reproduceability crisis' through effective documentation. The data can also help with validating research findings.
  • Research funding. Funders increasingly require, as a condition of funding, researchers to demonstrate good data practice and to make data openly available at the end of the project. Familiarising yourself with the information in this guide could help improve your chances of success when bidding.

BU Research Data Policy

BU's Research Data Policy has recently been revised and approved (December 2024) and will soon be available via the Staff Intranet > Policies and Procedures.