Research

Writing a data management plan

A data management plan is a document or statement describing how research data will be handled both during a project and after the project has ended. They are sometimes known by a different name depending on the emphasis that an organisation wishes to give them; the following are some common variations:

  • Data Management and Sharing Plan
  • Outline Data Management and Data Sharing Plan
  • Access and Data Management Plan
  • Statement on Data Sharing
  • Data Access Plan
  • Technical Plan
  • DMP

Writing a data management plan for the first time can be challenging. To help you, there are templates you can fill out, various forms of guidance to read, and you can contact the Library Research Data Service for advice.

It is worth taking the time to consider issues thoroughly and to find answers to any questions you identify as this will save you time and effort later. The data management issues relevant to your area of research are unlikely to change rapidly, so you will be able to re-use and adapt aspects of your data management plan for future research projects.

Your plan should be concise and appropriate to the nature of your research, with more detailed plans for larger projects. You should justify the decisions you make and be prepared to implement your plan. You can also update your plan once your project has started to reflect changes in your research, or to fix aspects that do not work as well as expected.

Using a data management plan template

To help you write a data management plan that is appropriate for your needs, there are a range of templates and tools available. These can help you to structure the content of your data management plan and focus on the topics relevant to your funder or institutional policy requirements.

Funder templates

Most Research Councils and some other funders provide templates and guidance for writing data management plans. These templates have been designed to meet the specific requirements of the funder in question.

We recommend that you use any templates or guidance provided by your research funder when applying for funding. This will ensure that you've covered all of the criteria that your plan will be reviewed against.

When using these templates, ensure you are using the correct version: they are updated periodically, and some funders provide different templates depending on the programme or the stage of the application process.

Other templates

If your funder does not provide a template for you to use, there are other templates available that are more generic.

If you are a PhD or Masters student, we recommend using the University of Bath postgraduate data management plan template, which has been specifically designed to help you plan how to manage your data during your project.

Otherwise, we recommend using the checklist for a data management plan (external website), produced by the Digital Curation Centre, as a starting point.

Using a data management planning tool

A couple of tools exist to help you complete a data management plan template.

DMPonline is a web-based tool that breaks templates down into small sections; alongside each one it presents relevant guidance and suggestions for what to include. The tool was developed by the Digital Curation Centre and we have loaded it with additional guidance specific to the University of Bath. It contains templates for all of the major UK funding bodies, as well as some international funders. It also contains generic templates including the University of Bath postgraduate data management plan template and one based on the Digital Curation Centre checklist.

If you are collaborating on a project, DMPonline allow you to specify which other users of the tool can see your plan; they do not have to be based at the same institution. You can choose whether they can edit your plan or only view it.

When you have finished writing your data management plan, you can export it from DMPonline in different file formats, including PDF, CSV, text, HTML, JSON and XML. You can select which information you want to include in your export and alter the formatting to meet your funder requirements.

DMPTool is similar to DMPonline, but includes templates and guidance based around the requirements of major US funding bodies. Data management plans created using DMPTool can be shared with collaborators and then exported in either PDF or RTF formats.

Information to include in a data management plan

Because of the diversity of research, there is no single correct answer to what a data management plan should cover. However, a good data management plan should typically address the following topics:

What data will you create or re-use?

  • If you're re-using existing data, what licences or terms of use will you have to comply with?
  • How will new data build on and relate to existing data? Why were existing data unsuitable for re-use in your new project?
  • What types of new data will you create and in what format? Did you chose these formats because they are standards in your discipline, are linked to the software or equipment you will use, or are open file formats?
  • Can you estimate the size of the data you'll create? Will it be less than 500GB, around 1TB, or substantially more than 1TB? How many boxes might non-digital data fill?
  • What methods will you use to capture your data and how will these ensure that your data are high quality? Will you use standard protocols, include replicates or controls, or automate data capture?

How will you document and describe your data?

  • What contextual information is needed for you or someone else to understand your data? Do you need to record methodologies, equipment settings or abbreviations used?
  • How will you capture contextual information? Will this be in a 'readme' text file to accompany the data, or will you embed metadata directly in file properties or headers?
  • Are there any standards that you will use? The Digital Curation Centre maintains a list of metadata standards for different disciplines.

How will you protect your data and those associated with your research?

  • Where will you store your data and how will you ensure that they are backed up? Will you use University-managed data storage or will you need to set up your own back-up procedures?
  • How will you secure your data? What methods will you use to restrict access to your sensitive data? Will you encrypt hardware when working off campus?
  • How will you protect your research participants? Will you obtain informed consent for data retention and sharing? How will you anonymise data to safeguard the privacy of your participants?

Which data will you retain and preserve after your project ends?

  • Which subsets of your data will you keep at the end of your project? Will you retain anonymised versions but destroy personal data and identification keys? Will you retain all of the raw data or is a processed version more suitable to preserve? Do you need to keep all intermediary files or would you only need to refer back to input files or a final version?
  • How will you prepare your data for long-term preservation? Are you able to convert your data to open file formats? What contextual information do you need to retain so that your data remain understandable and usable?
  • Where will you archive your data to ensure that they are preserved and sustained for several years after your project ends? Will you submit your data to a specialist data repository/centre and if so, have you consulted them about your requirements?
  • How big will your final dataset be and will there be any costs associated with archiving them, such as data deposit charges?

What are your plans for data sharing?

  • Can you demonstrate that you'll plan ahead to maximise data sharing? For example, will you only share a subset of the data where informed consent was granted for data sharing?
  • Are there any reasons why you would not be able to share some of your data? Would they be covered by the Data Protection Act, licence restrictions or contractual confidentiality clauses? Are there ethical reasons why data should not be released?
  • When will you share your data? Will data be made available upon first publication of findings or within a limited period after the end of the project? Do you need to delay publication to allow for commercialisation or patent applications? Will you embargo your data to allow for a limited period of exclusive use?
  • How will you disseminate your research? Will you include a data access statement in published articles? Does your chosen method of data preservation provide a persistent URL such as a Digital Object Identifier? What licences will you assign to your data?

Example data management plans

If you've not written a data management plan before, it can be helpful to look at what a good example should look like.

When using an example plan, consider how the issues raised would apply to your project to ensure that the plans you make are appropriate for the data you will be collecting or creating.

Further guidance on writing data management plans

You may find the following external resources useful when writing a data management plan.