Presentation given at the VADS4R training event in Glasgow on 16th June. VADS4R is a project training PhD students and early career researchers in the visual and performing arts about research data management.

1. Data Management Planning
and DMPonline
Sarah Jones
DCC, University of Glasgow
sarah.jones@glasgow.ac.uk
Twitter: @sjDCC
•VADS4R, Glasgow School of Art, 16th
June 2014
Funded by:

2. What is the DCC?
A Jisc-funded service to support universities
with research data management
•Run training courses
•Provide guidance on good practice
•Develop tools such as DMPonline
•Offer tailored support to universities
•…
www.dcc.ac.uk

3. “the active management and
appraisal of data over the
lifecycle of scholarly and
scientific interest”
Data management is part of
good research practice
What is research data management?

4. 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’re creating data.

5. Why develop a DMP?
• to 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!

6. Which UK funders require a DMP?
•www.dcc.ac.uk/resources/policy-and-legal/ overview-funders-data-policies

7. DCC Checklist for a DMP
• 13 questions on what’s asked across the board
• Prompts / pointers to help researchers get started
• Guidance on how to answer
www.dcc.ac.uk/sites/default/files/documents/resource/DMP_Checklis

8. Common themes in DMPs
1. Description of data to be collected / created
(i.e. content, type, format, volume...)
2. Standards / methodologies for data collection & management
3. Ethics and Intellectual Property
(highlight any restrictions on data sharing e.g. embargoes, confidentiality)
4. Plans for data sharing and access
(i.e. how, when, to whom)
5. Strategy for long-term preservation

9. •1. Describing data to be collected
• What type of data will you produce?
• What file format(s) will your data be in?
• How much data will be produced?
• How will you create your data?

10. Some formats are better for the long-term
It’s preferable to opt for formats that are:
• Uncompressed
• Non-proprietary
• Open, documented
• Standard representation (ASCII, Unicode)
Data centres may have preferred formats for deposit e.g.
Type Recommended Non-preferred
Tabular data CSV, TSV, SPSS portable Excel
Text Plain text, HTML, RTF
PDF/A only if layout matters
Word
Media Container: MP4, Ogg
Codec: Theora, Dirac, FLAC
Quicktime
H264
Images TIFF, JPEG2000, PNG GIF, JPG
Structured data XML, RDF RDBMS
Further examples: http://www.data-archive.ac.uk/create-manage/format/formats-table

11. Tools for researchers
www.dcc.ac.uk/resources/external/tools-services/
managing-active-research-data

12. •2. Standards and methodologies
• What metadata and documentation will you record?
• What standards are used in your field?
• How will your data be organised?
• Where will it be stored and backed-up?

13. Documentation and standards
Metadata: basic info e.g. title, author, dates, access rights...
Documentation: methods, code, data dictionary, context...
Use standards wherever possible for interoperability
www.dcc.ac.uk/resources/me

14. •3. Ethical and IPR implications
• Are you seeking consent from participants?
• Who owns your data or has rights in it?
• Are you re-using other people’s data?

15. Seek consent for data sharing & preservation
•If you don’t ask, data centres won’t be able to accept
your data – regardless of any conditions on the original
grant or your desire for it to be shared.

16. •4. Data sharing and reuse
• Are you allowed to share your data?
• Who will you share with and how?
• Do you need to impose conditions on reuse?
• How will you license the data for clarity?

17. •CREATIVE COMMONS LIMITATIONS
• NC Non-Commercial
• What counts as commercial?
• SA Share Alike
• Reduces interoperability
• ND No Derivatives
• Severely restricts use
www.dcc.ac.uk/resources/
how-guides/license-research-data
License your data for reuse
Outlines pros and cons of each
approach and gives practical advice on
how to implement your licence

18. •5. Preservation
• Which data do you need to keep?
• Will you deposit your data in a repository?
• Do you need to prepare it for deposit?

19. Lists of repositories to choose from
http://databib.org
http://service.re3data.org/search

20. Managing and sharing data:
a best practice guide
• How to write a DMP
• Formatting your data
• Documentation
• Data sharing
• Ethics and consent
• Copyright
• …
http://data-archive.ac.uk/media/2894/managingsharing.pdf

21. 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

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

23. Help from the DCC
•https://dmponline.dcc.ac.uk
•www.dcc.ac.uk/resources/how-guides/develop-data-plan
A web-based tool to help researchers
write data management plans

24. DMPonline demo
https://dmponline.dcc.ac.uk

25. Thanks – any questions?
DCC guidance, tools and case studies:
www.dcc.ac.uk/resources
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