Data Management Planning (DMP)

A Research data management plan (DMP) is evidence of your commitment to value the research data generated by you/your project; and ensure that you, as researcher and your institution are better positioned to meet the requirements of our research funders.  See Bidding.

Why develop a research data management plan (DMP)?

• You can find and understand your data when you need to use it
• There is continuity if project staff leave or new researchers join
• You can avoid unnecessary duplication e.g. re-collecting or re-working data
• The data underlying publications are maintained, allowing for validation of results
• Data sharing leads to more collaboration and advances research
• Your research is more visible and has greater impact
• Publishers and research funders may require that you share your data so it is worth investing time to plan for effective data management. Several funders ask for data plans as part of grant proposals.
• Other researchers can cite your data so you gain credit

Did you know that the University of Leeds Research Data Management Policy states....?

• A data management plan that explicitly addresses the capture, management, integrity, confidentiality, preservation, sharing and publication of research data must be created for each proposed research project or funding application.
• Sufficient metadata shall also be created and stored to aid discovery and re-use.
• Data management plans should take account of and ensure compliance with relevant legislative frameworks which may limit public access to the data (for example, in the areas of data protection, intellectual property and human rights).

Please see the FAQs supporting the University of Leeds Research Data Management Policy.  This resource has been developed to help understand the policy requirements whilst also being a standalone resource for information and guidance on research data management.

A typical Research data management plan (DMP) provides information on:

1. The research project and research context including what data will be created by the research project and how? 
2. Data Types, Formats, Standards and Capture Methods
3. Ethics and intellectual property - including what actions are appropriate given the nature of the data and any restrictions that may need to be applied.
4. Access, Data Sharing and Re-use including an outline plan for the sharing and preservation of the research project outputs/data
5. Short-term storage and data management
6. Deposit and long-term storage
7. Resourcing
8. Training and Support                                                         

This DCC structure gives you the generic headings/sections that inform a data management plan.  The information in the extended tabs below will help you consider what content to include as part of these headings/sections:

1. Details on the Research project funded including research aims, methodology, contact details etc

2. Research funder grant requirements eg How long you required to preserve your research data for beyond the life of the research?

For certain areas of research it may be difficult due to time and cost constraints to undertake primary research or analysis. Being able to obtain information from secondary sources may support your finding of data; Data that has already been published provides a useful source of secondary data ie from books, journals and periodicals - see the list below. 

Remember your research funder may ask you to outline the steps you have taken to satisfy yourself that the research data to be generated has not in fact been funded and published on previously.    

& a peer review/funder perspective?

• What secondary sources of data have been considered and evaluated? 
• Is the project creating new data? and why existing  data resources could not be re-used? 
• If existing data are used, have issues such as copyright or IPR of such data been considered and possible copyright clearance obtained to be able to share data or data derived thereof?

1. The approximate size of your research data / number of data files that represent your research
2. How your data is organised, described and annotated?
3. See What is research data? and File formats

For example:

To help you keep track of your data files, it is important to adopt a file naming and versioning convention.

• Advice on file naming and tracking changes from University of Oregon
• General advice on file naming from the University of Edinburgh Records Management Section (mainly aimed at files generated from Windows based software)

• In line with the research and methodology proposed in the application is the information on the data to be produced adequate and realistic? 
• Is there evidence that the plan covers all data that is planned to be generated from the research?
• Is sufficient information given on how data will be collected and in which formats (eg Open Document Format, tab-delimited, Excel etc)?
• How will data be documented, analysed and stored?
• Have any data collection or quality assurance procedures been stated? This could include methods for data validation or standards applied during data collection and data entry, codes of research practice adhered to, transcription templates used, etc.
• Is there a clear need that from the research being proposed quality assurance procedures should be outlined?

Ethics in research relates to how issues such as:

These are issues that are applied to all areas of your research.  Hence the principles of good research practice encourages those involved in research to consider the wider consequences of their research and engage with practical, ethical and intellectual challenges inherent in high quality research. 

The university provides information and guidance on good practice in ethics and ethical review.

Data Protection

The eight principles of the Data Protection Act states that personal information should be:

For more detailed information, guidance, advice and answering any queries you may have on Data Protection please go to: Data Protection.

Copyright and IPR issues?

Intellectual property rights, very broadly, are rights granted to creators and owners of works that are the result of human intellectual creativity. The main intellectual property rights are: copyright, patents, trade marks, design rights, protection from passing off, and the protection of confidential information (JISC Legal).

It is important to clarify intellectual property rights at the beginning of the research process, otherwise there may be unexpected restrictions on how data may be used and reused by yourself and others. Research funders may expect IPR ownership to be addressed in your data management plan.

What is Freedom of Information?

JISC, the UK expert on information and digital technologies for education and research advise the following:

Information, guidance and support from the University of Leeds is available at:

• Freedom of Information (FOI)
• Freedom of Information Quick Links

The Information Commissioners Office (ICO) is the UK independent authority set up to uphold information rights in the public interest, promoting openness by public bodies and data privacy for individuals.

FOI and Data Examples

Many funders of research require the studies they support to be made freely available - this is referred to as open access.  Where possible, the cost of publishing under open access arrangements should be included in project costs. The University of Leeds Researcher@Librarywebsite contains useful information on open access publishing including links to information on the open access policies of many funders and publishers.

What do I need to take into account when planning to share research files and data with collaborators?

• What data will be shared and with whom? How will other researchers be able to access the data?
• What are the further intended and/or foreseeable research uses for the completed dataset(s)?
• How you will make the resource accessible to the potential audience(s) identified?
• Where will you make the data available?
• Will a data sharing agreement be required?
• What is the timescale for public release of the data?
• State any expected difficulties in data sharing, along with causes and possible measures to overcome these difficulties.
• How will data sharing provide opportunities for coordination or collaboration?
• Whether any enhanced security controls need to exist.
• Have all obstacles to sharing data been considered? Have strategies been considered for dealing with these issues? For example by discussing data sharing and re-use with interviewees and gaining specific consent from participantsto share research data and
  o anonymising data to remove personal and disclosive information
  o regulating access to data

1. Identification of the person responsible for the immediate day-to-day management, storage and backup of your research data arising from your research
2. Who will be responsible for your research once your research has concluded?

If you have any questions about research data backup and storage you should contact your Faculty IT Manager.

The Research Support service web pages have advice on the University approach to storage and backup of research data.

The IT Help desk web page holds information on file storage.

Always store your crucial data in more than one place.

• Is the data back-up procedure described fit for purpose? eg considering back-up  procedures for all institutions.
• Are methods of version control described? (ie making sure that if the information in one file is altered, the related information in other files is also adopted, as well as keeping a track on a number of versions and their locations)
• Is the data back-up procedure described fit for purpose? eg considering back-up procedures for all institutions/collaborations

1. What happens to your data longer term?
2. Do you deposit to a data centre or similar?
3. For how long will you embargo your research data before it is published for others to see and use?
   

Why is preservation important for my research?

Regular backups of data are not enough to ensure long term accessibility and reusability. For example, file formats may become obsolete, storage media may become damaged or your data may not be understandable if it lacks appropriate description and documentation to enable reuse.

Long term preservation guidance from the University of Edinburgh.  If you deposit your data with a data centre or repository, check their policies on data retention and preservation.  Your research funder may have a requirement that your data is retained for a specific period of time.

All research data should be offered and assessed for deposit in an appropriate University, national or international data service or domain repository, unless specified otherwise in the data management plan.  See the University of Leeds Research Data Management Policy FAQs for further information.

If there is a recognised data centre or 'digital repository' for your subject discipline, this should be your first port of call for long term data deposit. Your funder may stipulate which repository should be used to house your data. Be aware of any collaborative agreements you have signed with research partners and whether these contain requirements for data deposit.

Is there a Leeds data repository?

The University of Leeds is scoping a research data management repository service as part of the RoaDMaP project (Leeds Research Data Management Pilot). The project will make recommendations for a service in 2013.

In the meantime, the holding advice is to apply good research data management principles to your data and ensure it is securely stored ready for eventual deposit in the local data repository.
 
If you are unsure about where to deposit your data, email roadmap@leeds.ac.uk  for advice.

What is data citation and why is data citation relevant for my research data?

The exact format data citation should take is currently under debate though common practice is emerging as more datasets are made available online. If you use data from an online data repository, there may be a recommended citation format; any journal you publish with may have a dataset citation house style. A Digital Curation Centre guide collates current practice on citing datasets.

There is some evidence publications with associated datasets are more highly cited.

What is a Unique Identifier?

For robust citation, datasets should have a unique identifier which persists over time. Several identification systems are in use. A well known example is the digital object identifier (DOI) which is commonly used to identify journal articles but which can also be used to identify datasets. More information on persistent identifiers from DataCite and the Australian National Data Service.

Further information on citing data and getting cited is available from: 

• Are the plans for preparing and documenting data for sharing and archiving with the selected repository appropriate? 
• Is there evidence that data will be well documented during research to provide high-quality contextual information and/or structured metadata for secondary users? eg documenting the method of data collection, origin, circumstances, processing and analysis of data.
  

1. Have all relevant of data management requirement costs been built into your research bids?
2. Who will be responsible for your data, once you have left your present research group?

Further support in the area of costing your data management plan is available from:

1. The UK Data Archive

• Planning
• Costing Tool

2. UK Data Service

3. JISC Keeping Research Data Safe

• Have data management responsibilities been allocated to named individuals? 
• Is there evidence that data management will be followed throughout the course of the  project? 
• Has consideration been given to the variety of data management tasks that may be required for the research? 
• For collaborative research, are data management responsibilities allocated at each partner organisation (if needed for the research) or has the coordination of data management responsibilities across partners been considered?
  

Internally

SDDU offers a range of courses relevant to research data management, including External training providers

Online

• Generic research data management training resources
• Discipline specific research data management training resources
• The University is currently reviewing its support for research data management as part of the RoaDMaP project.