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Data Management Planning

Light effectsWhy prepare a data management plan?

Many funders require new project proposals to include a data management plan describing the data that will be collected in the course of the research, how the data will be managed, what data will be retained for the long term and, where relevant, how they will be made available for re-use by other researchers.

Whether or not you are asked to prepare a data management plan for your research project, it is good practice to plan and document how you intend to manage the data you collect in the course of your research. There are many benefits to creating a data management plan at an early stage in your project:

  • It enables you to comply with your funder's requirement for a data management plan, where this is applicable;
  • It helps you to plan how the data you collect or generate will be managed both during the project and for the long term, and identifies at an early stage issues that need to be addressed, for example, the need to obtain consent (see Enabling Data Sharing), or requirements for additional storage capacity;
  • Where data are managed within a research group or in a partnership, it helps to document roles and responsibilities, so that data are managed efficiently and consistently to agreed standards;
  • In collaborative research activities it can help to establish Intellectual Property Rights and Data Ownership, and permitted uses of the data by others, so that confusions or disagreements over ownership and use of the data can be avoided;
  • It allows you to identify the costs of data management activities, which you may be able to recover through your grant.

A data management plan is a valuable tool, and if used well it can make your research more efficient and effective. 


Grant applications

If a data management plan is required as part of a grant application, this will be subject to review by the Research Data Manager prior to submission of the final application. You must ensure that a draft of your data management plan is made available to the Research Data Manager for review and comment as early as possible and no later than 5 working days before the proposed application submission date. Draft plans can be sent directly to the Research Data Manager or via the Research Development Manager who is supporting your application.

You can contact the Research Data Manager if you require advice and support in writing your data management plan.

General guidance

Writing a Data Management Plan for a Grant Application focuses on general principles, and provides information about University policies and services. Guidance for selected specific funders is provided below.

Funder guidance 

Guidance on preparing data management plans and addressing data management requirements for selected funders is provided below.

AHRC DMP Guidance

BBSRC DMP Guidance

EPSRC Data Management Guidance

ESRC DMP Guidance

GCRF Internal Application DMP Guidance

Horizon 2020 Data Management Guidance

NERC DMP Guidance


If you would like to get an idea of what a good data management plan looks like, the DCC provides a number of examples that you can refer to. You can also review applications made by University of Reading researchers in the Research and Enterprise Development Successful Proposal Library.

Planning tools

If you are applying for funding from one of the major funders, you should use the template specified by the funder. A number of UK funders' data management plan requirements are listed by the DCC.

You can use a tool called DMPonline to create a data management plan according to your funder's requirements. DMPonline includes funder-specific templates for all the UK Research Councils as well as other major funders, with tailored prompts and guidance to help you write your data management plan. Plans can be saved, shared with co-applicants, and exported in a variety of formats for incorporation into grant applications.

The Digital Curation Centre (DCC) provides a generic template in the Checklist for a Data Management Plan. This will give you a logical structure for a data management plan broken down into sections, with questions and prompts to help you address all relevant requirements.

To help you identify all the staff time and resources required for the collection, management, processing, preservation and sharing of data, and to ensure all research data management activities and resources are appropriately costed, you can use the Costing Tool developed by the UK Data Archive. Although the tool is primarily aimed at researchers in the social sciences, the activity-based approach can be easily applied in any discipline.


What does a data management plan involve?

Most data management plans will cover the following:


  • The context of data collection: i.e. the research project, and relevant policy frameworks, e.g. sponsors' policies, institutional policies, policies of partner organisations;
  • Data collection, storage and processing: the data to be collected, methods of collection and processing, solutions for storage, backup and organisation, and relevant formats and standards;
  • Documentation and metadata: information that will be created and linked to the data to identify them, document the methods by which they were created, and provide you and other people with whatever is necessary to understand and use the data;
  • Ethics and legal compliance: measures for the management of data in order to comply with any Research Data Ethics, such as those relating to data obtained from human subjects, any requirements specified under the Data Protection Act, other contractual undertakings, etc.;
  • Selection and preservation: what data will be preserved over the long term, where and for how long, and what costs are likely to be involved in data preservation;
  • Data sharing: whether and if so how the data will be shared and made available for discovery, who will be able to access the data, and under what conditions, with consideration of relevant issues, such as handling Intellectual Property Rights and Data Ownership, obtaining consent for sharing from human subjects, anonymisation of personal data, etc.;
  • Responsibilities and resources: how roles and responsibilities for different aspects of data management will be assigned and monitored, what resources will be required, in terms of staff and equipment, and what additional costs will be incurred, such as data storage costs, or charges for data archiving.  



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