Data management plan for a funding proposal

A really good source of information for this whole area is the Digital Curation Centre and most of the information here is taken from their website.

Increasingly Funders are mandating that data must be made openly available as well as publications.  The Horizon 2020 funding call has an Open Research Data Pilot which will be monitored during the life of the program with a view to further developing EC policy on open research.

If you are asked for a plan when making a funding proposal, consider it as a preliminary outline plan for a comprehensive Data Management Plan which will be developed during the course of the research. 

What do Funders expect from the preliminary outline?

A funder will expect data plans to outline how the data will be created, managed, shared and preserved justifying any restrictions that need to be applied. Strict word counts may be applied so you need to be clear and concise. Funders typically expect a succinct summary submitted as part of the “case for support” or in an allocated section of the application form. Take care not to repeat information here or to provide details unrelated to data management.

  • Consult and collaborate widely: ask for advice from colleagues, research offices, library, local IT, legal, ethics, repositories.
  • Justify your decisions: generally the funder will not specify particular file formats, standards or methodologies that you are expected to use. However, you need to choose and demonstrate that the selections you have made are the appropriate ones, both for the project and for the future. You also will need to make a convincing case with regards to restrictions on data sharing.
  • Be prepared to implement: you need to convince the funder that you understand their requirements and have realistic plans in place to meet these. These plans should be clear and achievable. Clearly defined roles and responsibilities will help so be very clear about who will do what, how and when.

Content

Detail what data you will create and explain why you have opted for particular formats, standards and methodologies. Be aware that the choices you make here will make it easier or harder to share your data. Using standard or widely adopted formats will make your data interoperable and more easily shared. Open or non-proprietary data formats are preferable. If you are depositing your data into a subject/discipline or institutional archive, check what the preferred formats are.

You will need to state the data outputs you expect to generate. This means stating the volume, type, content, quality and format of the final dataset. Outline the metadata, documentation or other supporting material that must accompany the data for it to be understood properly. State the standards and methodologies that you will use to collect and manage this data.

Point out the relationship to other data available in other repositories; existing data sources that will be used, gaps between available data and your research project, the added value that your data will provide in relation to existing data.

Documentation and Metadata

This is really important as it allows your data to be understood and discovered by others. You must capture the contextual details about how and why the data was created. Metadata describes the data in detail (think of it like a description in a catalogue). There are various standards that can be used for this, check with the library or your colleagues for the one most appropriate for your discipline.

Make a strong case for any restrictions on sharing

You should justify any embargo periods or restrictions on sharing your data. Remember there is an expectation that publically funded research data will be openly available as soon as possible.

If using human subjects, you will be guided by formal ethical review and outline the steps you will take to protect the research participants. Show that you have weighed up the reasons to share or not share and in this context negotiated informed consent of the participants may be one way forward. You should also show that you are aware of relevant legislation such as the Data Protection Acts. Some guidance to the Acts is provided here.

Data Ownership

Show that you are aware of this issue. You must demonstrate that you have looked for advice on and addressed all copyright, license or other rights issues that might arise.

Anticipate how other users might avail of your data

If you can, anticipate the type of users who might avail of your data and address their needs when deciding how to make the data available. Remember your objective is to make it as easy as possible for them to access the data. The funders will welcome clarity around access so be clear about where, when and how your data will be made available. You may want to license your data using a Creative Commons License.  Where possible use an appropriate disciplinary database, data centre or institutional repository. You will find a list of such repositories at DataCite  or re3Data.org  and you can upload data to the Institutional Repository Arrow@dit.

Security

Describe how you plan to securely store the data. Security will need to be stronger for any sensitive data you collect than for licensed data.  If you are using an online server know where your data is housed and if this is legally permissible. The more important your data and the more it is used, the more regularly it needs to be backed up. If your project has multiple partners, specify the responsibilities for data management and curation within the research teams operating in all partner institutions.

 

Some useful resources:

UCD Library: Research Data Management Guide

DCC, Funders’ data plan requirements

Wellcome Trust. (n.d.). Guidance for Researchers: Developing a Data Management and Sharing Plan. Retrieved 8 August 2011, from http://www.wellcome.ac.uk/About-us/Policy/Spotlight-issues/Data-sharing/...

UKDA. (2011). Managing and Sharing Data: best practice for researchers

 

 

 

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