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Research Data Management Toolkit RDM Toolkit

  • Research data lifecycle
  • RDM for Researchers
  • Skills and training
  • Research Data Management Toolkit
  • Plan and design

The RDM lifecycle

  • Plan and design
  • Collect and capture
  • Collaborate and analyse
  • Manage, store and preserve
  • Share and publish
  • Discover, reuse and cite

The RDM lifecycle

  • Plan and design
  • Collect and capture
  • Collaborate and analyse
  • Manage, store and preserve
  • Share and publish
  • Discover, reuse and cite

Plan and design

Research data management planning underpins any project. It helps you ensure that data is shared at the right time, with the right people, and after seeking appropriate permissions. It also helps you organise, store and preserve data in a FAIR (Findable, Accessible, Interoperable, and Reusable) way.

You should consider research data at project start, before beginning any practical work. Many research funders now require research data management planning at the grant application stage. As you begin planning, also consider relevant policies, services, and requirements in your organisation. These might not always align with the practices highlighted in this toolkit or in the literature but can override them. For example, your organisation may have certain processes or systems in place that you have to use. A good data management plan reflects the organisational context and leverages it to minimise costs.

This toolkit will help you design your approach to research data management by discussing the main issues in the field and by signposting relevant resources. You should also seek support from research data management specialists within your organisation, who can provide you with tailored advice. You can find links to the research data management pages of many UK higher education institutions in the website footer and in the RDM for researchers page.

Data citation and metrics

Data should be cited just like academic publications. There is evidence showing how this practice yields additional citations, plus it acknowledges researchers’ efforts and allows increased transparency.

Data management planning

Data management plans describe how data is managed and documented throughout a research project. They also discuss deposit for long-term preservation.

Policy compliance

When carrying out research, you should ensure you comply with relevant funders’ policies. However, you should not forget your organisation might have policies, too.

FAIR principles in research data management

FAIR principles ensure that research outputs are findable, accessible, interoperable and reusable. In practice, they enable higher visibility and reuse potential for data.

Costing

Performing research data management is an investment of both time and money. Therefore, costing it appropriately in a research data management plan is essential.

Research data in arts, humanities and social sciences

Research data management applies to all disciplines, including arts, humanities and social science. Particularly, in the past few years, digital humanities and social sciences have risen significantly.

Research data management?

Some general information and high-level sources on RDM if you are just beginning to learn the topic.

RDM Checklist

A downloadable checklist to ensure you are managing your project data appropriately.

Useful links
  • Research Data Management?
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  • Staying up to date with RDM
  • RDM skills and training
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