Talk on

1. Data Management Planning
University of Northampton, 27th February 2013
Marieke Guy
DCC, University of Bath
m.guy@ukoln.ac.uk
Funded by:
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2. What is a data management plan?
A brief plan written at the start of your project to define:
• how your data will be created?
• how it will be documented?
• who will access it?
• where it will be stored?
• who will back it up?
• whether (and how) it will be shared & preserved?
DMPs are often submitted as part of grant applications,
but are useful whenever you are creating data.

3. Why develop a DMP?
• to meet funder requirements
• help you manage your data
• to make informed decisions so you don’t have to
figure out things as you go
• to anticipate and avoid problems e.g. data loss
• to make your life easier!

4. What should a DMP cover?
1. Provide a description of the data
1. Explain how the data will be collected & documented
2. Outline the plans for data sharing
3. Justify any restrictions on sharing (ethics, IP)
4. State the long-term preservation plan

5. Provide a description of the data
Why is this important?
A good description of the data to be collected will help
reviewers
understand the characteristics of the data, their relationship to
existing data, and any disclosure risks that may apply.
•e.g. The proposed research will include data from
approximately 500 subjects being screened for three bacterial
sexually transmitted diseases (STDs) at an inner city STD clinic.
The final dataset will include self-reported demographic and
behavioural data from interviews with the subjects and
laboratory data from urine specimens provided.

6. Data collection & documentation
Why is this important?
Creating data in formats preferred for archiving helps to ensure
that they will be usable in the future. Good descriptive metadata
are essential for effective data use.
•e.g. Quantitative survey data files generated will be processed
as SPSS system files with DDI XML documentation. The
codebook will contain information on study design, sampling
methodology, fieldwork, variable-level detail, and all
information necessary for a secondary analyst to use the data
accurately and effectively.

7. Outline the plans for data sharing
Why is this important?
Sharing data helps to advance science and to maximize the
research investment. Your funder probably expects you to share
data wherever possible.
•e.g. We will make the data and associated documentation
available to users under a data-sharing agreement that provides
for: (1) a commitment to using the data only for research
purposes and not to identify any individual participant; (2) a
commitment to securing the data using appropriate computer
technology; and (3) a commitment to destroying or returning
the data after analyses are completed.

8. Justify any restrictions on sharing
Why is this important?
As funders expect data to be shared, any restrictions need to be
valid. Protection of human subjects is a fundamental tenet of
research and an important ethical obligation for everyone.
•e.g. Because the STDs being studied are reportable diseases,
we will be collecting identifying information. Even though the
final dataset will be stripped of identifiers prior to release for
sharing, we believe that there remains the possibility of
deductive disclosure of subjects with unusual characteristics.
Thus, we will make the data and associated documentation
available to users only under a data-sharing agreement.

9. State the long-term preservation plan
Why is this important?
Digital data need to be actively managed over time to ensure that
they will always be available and usable. Depositing data
resources
with a trusted digital archive can ensure that they are curated and
handled according to good practices in digital preservation.
•e.g. The investigators will work with staff at the UKDA to
determine what to archive and how long the deposited data
should be retained. Future long-term use of the data will be
ensured by placing a copy of the data into the repository.

10. A useful framework to get you started
•Think about why
the questions are
being asked – why
is it useful to
consider that?
•Look at examples to
help you understand
what to write
•www.icpsr.umich.edu/icpsrweb/content/datamanagement/dmp/framework.html

11. Help from the DCC
•https://dmponline.dcc.ac.uk
•www.dcc.ac.uk/resources/how-guides/develop-data-plan

12. ...a web-based tool to help researchers write Data
Management Plans according to different funder
requirements
We’re currently enhancing it with practical examples,
boilerplate text and tailored support
https://dmponline.dcc.ac.uk

13. How DMP Online works
Create a plan
based on
relevant
funder /
institutional
templates...
...and then
answer the
questions
using the
guidance
provided

14. Tips for writing DMPs
• Seek advice - consult and collaborate
• Consider good practice for your field
• Base plans on available skills & support
• Make sure implementation is feasible

15. Advice on what funders look for
Audio clip from presentation by Peter Dukes of the MRC

16. Sources of guidance
• ICPSR framework for a data management plan
www.icpsr.umich.edu/icpsrweb/content/datamanagement/dmp/
framework.html
• How to develop a data management and sharing plan
www.dcc.ac.uk/resources/how-guides/develop-data-plan
• UKDA’s manage and share your data guide
• http://data-archive.ac.uk/media/2894/managingsharing.pdf

17. •To Summarise: Data Management
and Sharing Plans
Funders typically want a short statement covering:
• What data will be created? (format, types, volume)
• How will the data be collected and documented?
• What are the plans for data sharing and access?
• Justify any restrictions on sharing (ethics, IP)
• What is the strategy for long-term preservation?

18. Thanks - any questions?
For DCC guidance, tools and case studies see:
www.dcc.ac.uk/resources
Follow us on twitter @digitalcuration and #ukdcc
Thanks to Research360 for contribution to slides