Slides from an Open University workshop delivered February 2017.

1. Planning for
Research Data Management
7th February 2017
Wendy Mears,
Research Support Librarian
library-research-support@open.ac.uk

2. Overview of session
• What is Research Data Management?
• Why bother?
• Data Management Planning: step-by-step
• Questions
with a little help from my friends...

3. What is Research Data
Management?
“Research data management
concerns the organisation of
data, from its entry to the
research cycle through to the
dissemination and archiving
of valuable results. It aims to
ensure reliable verification of
results, and permits new and
innovative research built on
existing information."
Digital Curation Centre (2011)
Making the Case for Research Data Management
http://www.dcc.ac.uk/sites/default/files/documents/publications/
Making%20the%20case.pdf
http://www.data-archive.ac.uk/create-
manage/life-cycle

4. Why bother?

5. Or even worse...

6. Good data management...
• Helps you work more
efficiently and effectively
– Save time and reduce
frustration
– Highlight patterns or
connections that might
otherwise be missed
• Enable data re-use and
sharing
• Allow you to meet funders’
and institutional requirements

7. Benefits of data sharing...

8. OU Principles of
Research Data Management
“Research data must be managed to the highest
standards throughout their life-cycle in order to
support excellence in research practice.
In keeping with OU principles of open-ness, it is
expected that research data will be open and
accessible to other researchers, as soon as
appropriate and verifiable, subject to the application
of appropriate safeguards relating to the sensitivity of
the data and legal requirements.”
OU Principles of Research Data Management, April 2013
http://intranet.open.ac.uk/research-school/strategy-info-
governance/docs/CoPamendedJuly2013mergedwithappendix-forintranet.pdf

9. Data Management Planning
• Make informed decisions to anticipate
and avoid problems
• Avoid duplication, data loss and
security breaches
• Develop procedures early on for
consistency
• Ensure data are accurate, complete,
reliable and secure
• Save time and effort – make your life
easier!
Data Management Plans are useful whenever
you are creating data to:

10. Data Management Planning
DMPOnline
https://dmponline.dcc.ac.uk
A web-based tool to help you
write DMPs according to
different requirements. DCC,
funder and OU guidance.

11. The rest of the session...

12. “Write a paragraph on the aim
and purpose of your research.”
1. Introduction and Context

13. 1. Introduction and Context

14. “Describe the data aspects of your
research, how you will capture/generate
them, the file formats you are using and
why. Mention how metadata will be created
to describe the data, and your reasons for
choosing particular data standards and
approaches.”
2. Data types, formats,
standards and capture methods

15. 2. Data types, formats,
standards and capture methods

16. 2. Data types, formats,
standards and capture methods
Metadata tips:
• Use disciplinary standards
• Create a data file
• Use file properties
• Use functions in data
analysis software, e.g.
NVIVO, R, SPSS, Electronic
Lab Notebooks

17. 2. Data types, formats,
standards and capture methods

18. “Detail any ethical and privacy issues,
including the consent of participants.
Explain the copyright/IPR and whether
there are any data licensing issues – either
for data you are reusing, or your data which
you will make available to others.”
3. Ethics and Intellectual Property

19. 3. Ethics and Intellectual
Property

20. 3. Ethics and Intellectual
Property

21. 3. Ethics and Intellectual
Property
Sharing sensitive data:
• Gain consent
• Anonymise
• Restrict access
• Lock down (with
justification)

22. 3. Ethics and Intellectual
Property
Intellectual Property:
• Secondary data use
• Understanding open
licences
• Who owns IP of
your data?

23. 3. Ethics and Intellectual
Property

24. “Note who would be interested in your data,
and describe how you will make them
available (with any restrictions). Detail any
reasons not to share, as well as embargo
periods or if you want time to exploit your
data for publishing.”
4. Access, Data Sharing
and Re-use

25. 4. Access, Data Sharing and
Re-use

26. 4. Access, Data Sharing and
Re-use

27. 4. Access, Data Sharing and
Re-use
Licensing your data

28. ORDO
Online data sharing services
• Figshare
• Zenodo
• CKAN DataHub
• Mendeley Data
Directories
• re3data
Funders’ repository services
• UK Data Service ReShare
• NERC data centres
4. Access, Data Sharing and
Re-use

29. 4. Access, Data Sharing and
Re-use

30. “Give a rough idea of data volume. Say
where and on what media you will store
data, and how they will be backed-up.
Mention security measures to protect data
which are sensitive or valuable.”
5. Short-term storage and data
management

31. 5. Short-term Storage and
Data Management
• Follow the 3-2-1 rule:
• 3 copies
• At least 2 formats
• 1 offsite

32. • Shared areas or SharePoint
• Zendto
• Be wary of Dropbox & similar
• ORDO
IT support for research:
http://intranet6.open.ac.uk/library/main/supporting-ou-
research/research-data-management/creating-your-data
5. Short-term Storage and
Data Management

33. 5. Short-term Storage and
Data Management

34. • Thinking ahead will help when you need to share/archive
your data
• Define processes at project start
• Think about:
–File naming and versioning
–File directory structure
–Metadata
–File formats
–Quality assurance
–Data security
5. Short-term Storage and
Data Management

35. 5. Short-term Storage and
Data Management

36. “Consider what data are worth selecting for
long-term access and preservation and how
you will need to prepare those data for
archiving. Say where you intend to deposit
the data.”
6. Deposit and long-term
preservation

37. 6. Deposit and long-term
preservation
Deciding what to keep:
• Raw data
• Derived data
• Data underpinning publications
• Code
• Methods
What are research data in your context?
What would others need to understand your research?

38. 6. Deposit and long-term
preservation
To allow long-term access to data:
• Don't use obscure formats
• Don't use obscure media
• Don't rely on technology being
available
• Provide sufficient documentation

39. For preservation, file formats should be…
• Unencrypted
• Uncompressed
• Non-proprietary/patent-encumbered
• Open, documented standard
• Standard representation (ASCII, Unicode)
Type Recommended Avoid for data sharing
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
6. Deposit and long-term
preservation

40. • Metadata is additional information that is required to
make sense of your files – it’s data about data.
Guidance on disciplinary metadata standards: http://www.dcc.ac.uk/resources/metadata-
standards
6. Deposit and long-term
preservation

41. 6. Deposit and long-term
preservation

42. Library Services
How we can help
• Data Management Plan checking
• Support with setting up new projects
• Advice on preparation of data for sharing
• ORDO
• Online guidance
• Enquiries
Email: library-research-support@open.ac.uk

43. Useful links
• The OU Research Data Management intranet site:
http://intranet6.open.ac.uk/library/main/supporting-ou-research/research-
data-management
• VRE: http://www.open.ac.uk/students/research/activities/lists/organising-
your-research
• Digital Curation Centre: http://www.dcc.ac.uk/
• DMPOnline: https://dmponline.dcc.ac.uk/
• UK Data Archive: http://www.data-archive.ac.uk/
• MANTRA: http://datalib.edina.ac.uk/mantra/
• The Orb: http://open.ac.uk/blogs/the_orb

44. Reflection
and
Questions

45. Image credits
Other cartoons from the Research Data Alliance 4th Plenary, Amsterdam 2014:
https://rd-alliance.org/plenary-meetings/fourth-plenary/plenary-cartoons.html (CC-BY)
BASF (2007) Crop Design – the fine art of gene
discovery,
https://www.flickr.com/photos/basf/48372670
13 (CC BY-NC-ND 2.0)
Jay Oliver (2005) UGA research in Tifton, GA.
June 2005,
https://www.flickr.com/photos/ugacommunicati
ons/6254516052 (CC BY-NC 2.0)
Teddy-rised (2008) Making every litter count,
https://www.flickr.com/photos/teddy-
rised/2947952302 (CC BY-NC-ND 2.0)
Stan Leary (2009) University of Georgia
Griffin Campus:Research,
https://www.flickr.com/photos/ugacommu
nications/6254368548 (CC BY-NC 2.0)
Morten Oddvik (2011) Papers,
https://www.flickr.com/photos/mortsan/543041854
5 (CC BY 2.0)
Lars Rosengreen (2012) Using a GoPro camera to
collect data on pollinators,
https://www.flickr.com/photos/46369606@N04
/7543827396/ (CC BY-NC-ND 2.0)
Casldlyrose (2009) Be Prepared
https://www.flickr.com/photos/calsidyrose/35524
73207 (CC-BY 2.0)
Caleb Roenigk (2012) Writing? Yeah.
https://www.flickr.com/photos/crdot/685553826
8/ (CC-BY 2.0)
Jamie Henderson (2010) Day 22
https://www.flickr.com/photos/xelcise/42967348
26 (CC-BY-NC-ND 2.0)
PHDComics.com (2007)
http://www.phdcomics.com/comics/archiv
e.php?comicid=814 (CC-BY 2.0)
Sybren Stuvel (2008) Frustration
https://www.flickr.com/photos/sybrenstuvel (CC-
BY-NC-ND 2.0)
Brian Yap (2012) Blowing Questions
https://www.flickr.com/photos/sybrenstuvel (CC-
BY-NC 2.0)