This year’s theme of “Open in Action” is all about taking concrete steps to open up research and scholarship and encouraging others to do the same.
In the spirit of Open Access Week, here’s a quick look at the importance of Data Management Plans.
Every research proposal needs to have a data management plan (DMP) either as part of a funding application or as part of the University’s policy requirements. This document contains all the information related to the management of the research data of your project.
Why do you need a data management plan?
Your data management and sharing plan involves making decisions at the outset of your research to decide:
• Which software to use
• How to organise, store and manage your data
• What to include in the consent agreements you negotiate
These decisions will all affect the future use of your data. Most funders expect a short statement to be submitted with your grant proposal, outlining your plans for data management and data sharing.
What’s in a data management plan?
Generally, a DMP covers 5 themes:
• What data will be created?
• How will the data be documented and described?
• How you will manage ethics and your intellectual property rights (IPR)?
• What are the plans for data sharing and access?
• What is the strategy for long-term preservation and sustainability?
The specific questions asked in each of these sections depends on the funding body to which you are applying. However, they are all designed to cover every step of your project – this is why they are such a useful tool.
Templates and examples
The best place to start when writing a DMP is the DMPonline tool from the Digital Curation Centre (DCC), which:
• Has templates for most of the UK, EU and US funders, plus a generic template suitable for any project
• Provides expert guidance from the DCC for each section of each template along with guidance from the funder where available
• Exports in a variety of formats, including PDF and Microsoft Word
For more information, see:
• How to develop a data management plan (Digital Curation Centre) — includes a checklist and examples
• Your funder’s website
If you can’t find an example for your research, further advice and assistance is available by email: email@example.com.
Science and Engineering South held a one day conference, The Data Dialogue: When Research Crosses Borders, on September 29th at the University of Oxford. The event was well-attended by a good mix of researchers and research data practitioners. In his opening address Simon Hodson, representing CODATA, addressed the topic of Open Data and the Data Revolution: Challenges and opportunities for Global Research. Among the issues addressed were the principles of legal interoperability and coordinating data standards within the science community.
This was followed by a presentation by Rowan Wilson who works within Oxford’s Academic IT Research Support unit. Rowan described the range of issues and questions that are most commonly presented by researchers at Oxford, many of which were closely identified with by other practitioners in the audience. The day unfolded with a series of presentations by researchers detailing their personal experience in data collection relating to their own field of study, and the particular challenges and inspirations that this work delivered by this research.
– Prof Mary Bosworth on collecting data from those being detained in UK detention centres
– Dr Troy Sternberg offered a fascinating insight into his data collection work in Mongolia and China; the effect of regional ideologies was highlighted in terms of how the data was presented and delivered to its audience.
– Dr Julie Viebach on the profound personal experience involved in collecting data from the survivors of genocide in Rwanda
– Dr Heather Hamill addressed the issue of establishing trust between subject and interviewer in relation to her work with communities in sub-Saharan Africa.
– Gareth Knight from the London School of Hygiene and Tropical Medicine talked about the particular challenges associated with medical research data collection.
The programme was concluded by a panel discussion focused on answering questions posed by audience members. Some of the most discussed topics were those around security measures and cloud computing, ownership of data, and the huge benefits that can be gained from data sharing. Perhaps a fair summary of the discussion is that a ‘one size fits all’ solution is not always possible, but that making data open should not be a binary choice between either ‘open’ or ‘closed’: there are many solutions available which allow for sharing and it is always best to consider and discuss these. The EC slogan ‘As open as possible, as closed as necessary’ was mentioned in this context.
The one key idea I took away from the day (and perhaps one it would be wise to promote as widely as possible) were the words of Simon Hodson: “The first person you share your data with is your future self”.
The Cambridge Office of Scholarly Communication has conducted research over the past 18 months to look at the challenges associated with financially supporting RDM training.
Amongst their conclusions was that “research data cannot be effectively shared if it has not been properly managed during the research lifecycle”.
Read the full post here and contact firstname.lastname@example.org for further information on managing your research data or creating a data management plan.
Do you want to learn more about libraries of the future?
A curated resource reading packet with 10 websites, 11 downloadable reports and tool-kits, 18 articles, and a YouTube video playlist – all focused on key ideas and trends for libraries of the future – is available here.
The Open Science Framework (OSF) for data and project management is a science-focused tool that can manage their all kinds of research data during a project and also deal with other types of data created during a project, e.g. steering group minutes, presentations, interview permissions.
Some of the advantages are:
– Very quick start up time– it’s possible to get a project up and running in a couple of minutes.
– Possible to upload and categorise all kinds of data and files. For example, ‘methods’, ‘hypotheses’ and ‘communication’.
– Ability to store versions of data – revisions to each file can be stored.
– Different files can have different levels of permission.
– Ability to create public versions of parts of projects, with citations.