Research Data Management
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Data management plans 

A data management and sharing plan helps researchers consider, when research is being designed and planned, how data will be managed during the research process and shared afterwards with the wider community  

- UK Data Archive



Why are they important? 

  • data management plans are valuable documents that show that you have engaged with a variety of research related topics.
  • we advise that you allocate enough time to develop a robust data management plan or technical plan (formally known as a technical appendix) before your deadline for funding passes. 
  • even if you are not requested to submit one as part of your grant application, it is considered good practice to develop a plan, as they allow you to critically review your project and develop a suitable plan of action to overcome any issues.
  • remember that your plan will need reviewing throughout your project to help you manage your data most effectively. Taking the time to develop a good data management plan from the onset can save you time and money in the long term.

What do funders require?

The following five topics are the most commonly cited areas that funders require information on:

  • Data created
  • Metadata and documentation
  • Ethical and legal considerations
  • Access, re-use and sharing
  • Long term preservation

Data Management Planning Checklist

A data management checklist is a useful planning tool, which can assist you when considering what you need to put in place for good research data practice and management. Data management planning is an important part of the responsible conduct of research. You can use a data management checklist to:

  • Keep an audit of data management requirements that may change during the research process and update the checklist as required
  • Document your research data management requirements
  • Identify potential problems early in the research process

A sample checklist could include the following:

  1. What type of data will be produced?
  2. What standards will be used for metadata and documentation?
  3. What steps are required in order to protect confidentiality, privacy, security, intellectual property or other rights?
  4. Are there any funder requirements to share my data?
  5. How do I disseminate and share my data?
  6. How do I archive and preserve my data in the longer term?
  7. How do I store and backup my data?
  8. How much data will I be generating?
  9. Are there any tools or software needed to create/process/visualize the data?
  10. Will I need additional resources to manage data?

Examples from external resources

  • The University of Oxford provides a succinct checklist of what should typically be covered in a data management plan  
  • The Digital Curation Centre (DCC) checklist is a useful resource in identifying common questions from funding bodies

Additionally, the DCC hosts an excellent web based tool: DMP Online which provides you with a step by step guide on how to create a data management plan. 

It is important to remember that your funder may request different information cited within the DMP tool and therefore it is always advisable to check with them, what information they require in order to comply with any agreements. 

A summary of some funders' data requirements (AHRC, BBSRC, Cancer Research, ESRC, MRC, NERC, STFC and Wellcome Trust) is provided by the DCC and regularly updated.


Who can help me at Nottingham?

  • IT Support can advise on various aspects, while  local contacts within Schools or Departments may have subject specific knowledge. 

It is advisable to seek help as soon as possible; this will ensure that the correct provisions are put in place to assist you in creating your data management plan.

Other useful resources

Fallow deer AHRC grant (internal access only)

Columbia University examples of data management plans and templates for specific academic subjects

NERC Data Management Plan template and guidance notes.

Managing and Sharing Data - UK Data Archive

CAiRO Project: Managing Creative Arts Research Data

Research @ The University of Nottingham

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