Stuart Macdonald gave a presentation on research data management at the University of Edinburgh. He discussed the work of EDINA and the Data Library in providing data services and developing tools like Edinburgh DataShare. The university implemented a research data management policy and projects like Data Audit Framework and MANTRA to help researchers with data management best practices and culture change. The goal is to help researchers comply with funder requirements and enable secondary use of research data.

1. Research Data Management at Edinburgh:
Effecting Culture Change
Stuart Macdonald
Associate Data Librarian
EDINA & Data Library
University of Edinburgh
Stuart.Macdonald@ed.ac.uk
RECOLECTA Online Seminar on Research Data Management and Curation, 24 November 2011

2. Overview
IASSIST Latin Engagement Strategic Action Group
Research Data Management at University of Edinburgh
Research Data MANTRA

3. International Association for Social Science
Information Services and Technology –
IASSIST
An international organisation of
professionals working with IT and
data services to support research and
teaching in the social sciences. Its
320 members work in a variety of
settings, including data archives,
statistical agencies, research centers,
libraries, academic departments,
government departments, and non-
profit organisations.

4. IASSIST Latin Engagement
Strategic Action Group
Co-Chairs:
Luis Martínez-Uribe
Instituto Juan March, Madrid
Stuart Macdonald
EDINA & Data Library, University of Edinburgh
Mission :
To propose a set of activities that IASSIST could undertake to
further engage with data professionals from Ibero-american
institutions

5. Benefits
Identify data infrastructures and resources from Spanish
& Portuguese speaking countries to further the
establishment of collaborative data networks.
Reach out to Spanish/Portuguese speaking academic and
support communities that could benefit from the existing
network of expertise, guidance and knowledge that is the
IASSIST community

6. IASSIST Latin Members
• Two members from Spain in 1993 and 2001
• One member from Mexico 2009
• Representation in 2011 from Spain and Portugal
Phase I: Spain
Desk research (navigating institutional websites, annual
reports, mailing lists)
Combination of online survey questionnaire & telephone
interviews (with script)
3 areas of interest: traditional data library role; research
data management & curation; IASSIST
Responses from library & support services from national
& regional universities, Data Centres

7. Findings: traditional data library
• Only one 'traditional' data library
• Libraries provide training courses and
support for subscription data services
• Minimal data cataloguing!
Findings: research data management
• Growing area of interest in repository community
• Some institutions have started to deposit data in IRs -
others are conducting scoping & requirement gathering
exercises
• New skills needed – unclear about whose responsibility

8. IASSIST
Half of respondents knew of IASSIST
Perceived benefits that IASSIST can offer:
• Information about data support / data libraries
• Basic skills to handle social science data
• Links to free social science data resources
• Data analysis and visualisation tools
• Tools to manage and share research data
• A peer to peer support network
• Access to IASSIST online facilities
• Help to raise awareness and share knowledge about
RDM issues (remove duplication of effort)

9. In addition to conducting
similar scoping exercises in
Portugal & Latin-America
The Latin Engagement
Action Group have come up
with a number of outreach
activities aimed at supporting
data professionals from
Spanish and Portuguese
speaking educational institutions, namely:
Participation in Research Data Management Webinars for
Spanish/Portuguese data specialists
Preparation of a Latin-American session in next IASSIST annual conference
in collaboration with outreach committee
Spanish and Portuguese translation of the main pages of the IASSIST site

10. Research Data Management at
University of Edinburgh

11. EDINA & Data Library (EDL)
• EDINA and University Data Library (EDL) together are a
division within Information Services of the University of
Edinburgh.
• EDINA is a JISC-funded National Data Centre providing
national online resources for education and research.
• The Data Library assists Edinburgh University users in
the discovery, access, use and management of
research datasets.

12. EDINA National Data Centre
• Mission statement: “..to enhance the productivity of research,
learning and teaching in UK higher and further education..”
• Networked access to a range of online resources for UK
FE and HE
• Services free at the point of use for use by staff and
students in learning, teaching and research through
institutional subscription
• Focus is on service but also undertake R&D (projects
services)
• delivers about 20 online services
• has about 10 major projects (including services in
development)
• employs about 75 staff (Edinburgh & St Helens)

13. What is a Data Library?
A data library refers to both the
content and the services that
foster use of collections of
numeric, audio-visual, textual
or geospatial data sets for
secondary use in research.
Focus on re-use of data
re-

14. Data Library services and projects
• Data Library &
consultancy
• Edinburgh DataShare
• JISC-funded projects
– DISC-UK DataShare
(2007-2009)
– Data Audit Framework
Implementation (2008)
– Research Data MANTRA
(2010-2011)

15. Data Library & Consultancy
• finding…
• accessing …
• using …
• teaching …
• managing
Building relationships with researchers via postgraduate
teaching activities, research support projects, IS Skills
workshops, Research Data Management training and
through traditional reference interviews.

16. Edinburgh DataShare was built as an output of
the JISC-funded DISC-UK DataShare project (2007-2009)

17. Edinburgh DataShare
An online institutional repository of multi-disciplinary
research datasets produced at the University of
Edinburgh, hosted by the Data Library
Researchers producing research data associated with a
publication, or which has potential use for other
researchers, can upload their dataset for sharing and
safekeeping. A persistent identifier and suggested citation
will be provided.
DataShare is a customised DSpace
instance with a selection
of standards-compliant metadata
fields useful for discovery of
datasets, through Google and
other search engines via OAI-PMH.

18. A decision making and
planning tool for
institutions with digital
repositories in existence or
in development that are
considering adding research
data to their digital collections
Downloadable as PDF

19. Edinburgh Data Audit Framework (DAF) Implementation
(May – Dec 2008)
A JISC-funded pilot project
produced 6 case studies from
research units across the University
in identifying research data assets
and assessing their management,
using DAF methodology developed
by the Digital Curation Centre.
4 main outcomes:
• Develop online RDM guidance
• Develop university research
data management policy
• Develop services & support for
RDM (in partnership IS)
• Develop RDM training

20. Research Data
Management Web
Guidance
Online suite of web pages
for IS website developed in
2009 (will be revamped
early 2012)
Downloadable PDF
handbook

21. Championed by Vice-Principal
& Chief Information Officer
Professor Jeff Haywood the
policy for management of
research data was approved
by the University Court on 16
May, 2011.
Along with University of
Oxford, the first RDM policies
in the UK
“The University adopts the following
policy on Research Data Management.
It is acknowledged that this is an
aspirational policy, and that
implementation will take some years.”
* Quote from University of Edinburgh website
21

22. University Research Data Management Policy
In spring 2010, a review commenced at the
University of Edinburgh to address the issue of
managing the rapidly expanding volume and
complexity of data produced by researchers.
The Review was overseen by the IT & Library
Committee and had twin tracks to look at
Research Data Storage, and Data Management,
Curation and Preservation.
The Review looked at current practice in the
University and assessed current practice in peer
universities and internationally
Review Committee responsible for drafting policy
to support the University’s mission for ‘the
creation, dissemination and curation of knowledge’

23. The 10 Policy Principles
1. Research data will be managed to the highest standards throughout
the research data lifecycle as part of the University’s commitment to
research excellence.
2. Responsibility for research data management through a sound
research data management plan during any research project or
programme lies primarily with Principal Investigators (PIs).
3. All new research proposals must include research data management
plans or protocols that explicitly address data capture, management,
integrity, confidentiality, retention, sharing and publication.
4. The University will provide training, support, advice and where
appropriate guidelines and templates for the research data
management and research data management plans.
5. The University will provide mechanisms and services for storage,
backup, registration, deposit and retention of research data assets in
support of current and future access, during and after completion of
research projects.

24. 6. Any data which is retained elsewhere, for example in an
international data service or domain repository should be
registered with the University.
7. Research data management plans must ensure that research data
are available for access and re-use where appropriate and under
re-
appropriate safeguards.
8. The legitimate interests of the subjects of research data must be
protected.
9. Research data of future historical interest, and all research data
that represent records of the University, including data that
substantiate research findings, will be offered and assessed for
deposit and retention in an appropriate national or international
data service or domain repository, or a University repository.
10. Exclusive rights to reuse or publish research data should not be
handed over to commercial publishers or agents without retaining
the rights to make the data openly available for re-use, unless this
is a condition of funding.

25. Next Steps
IS Implementation group established
Led by Director, Library and Collections
Research Data Management Policy
Implementation Project
Working group was set up to define a
research data storage strategy
Vice Principal has promised a half terabyte
per researcher, storage

26. Research Data
MANTRA
Partnership between:
Edinburgh University
Data Library
Institute for Academic
Development
Funded by JISC
Managing Research Data
programme (Sept. 2010 –
Aug. 2011)

27. Why manage Data Deluge – exponential growth in
the volume of digital research artifacts
research data? created within academia
Data management is one of the
essential areas of responsible
conduct of research.
By managing your data you will:
• Meet funding body grant
requirements.
• Ensure research integrity and
replication.
• Ensure research data and records
are accurate, complete, authentic
and reliable.
• Increase your research efficiency.
• Enhance data security and minimise
the risk of data loss.
• Prevent duplication of effort by
enabling others to use your data.

28. Project overview
Grounded in three disciplinary
contexts: social science, clinical
psychology and geoscience
Aim was to develop online
interactive open learning
resources for PhD students and
early career researchers that will:
• Raise awareness of the key issues
related to research data
management & contribute to
culture change
• Provide guidelines for good
practice

29. Selling RDM as a Transferrable Skill
(voluntary participation)
The FRUIT principles:
Fun
Feedback
Relevant
Real
Useful
Interesting
Timely

30. Online learning module
Eight units with activities, scenarios and
videos:
• Research data explained
• Data management plans
• Organising data
• File formats and transformation
• Documentation and metadata
• Storage and security
• Data protection, rights and access
• Preservation, sharing and licensing
Four data handling practicals:
SPSS, NVivo, R, ArcGIS
Video stories from researchers in variety
of settings
Xerte Online Toolkits – University of
Nottingham

31. Online learning module
• Delivered online – self-paced, available ‘anytime, anyplace’
• Emphasis on practical experience and active engagement via
online activities
• One hour per unit
• Read and work through scenarios & activities (incl. videos etc)
• CC licence to allow manipulation of content for re-use with
attribution
• Portable content in open standard formats (e.g. SCORM)

32. MANTRA dissemination
Image courtesy of the periodic table printmaking project –
http://azuregrackle.com/periodictable/table/58.html
• Deposit learning materials with an open licence in JorumOpen and Xpert
• Learning materials to be embedded in three participating postgraduate
programmes and made available through IAD programme for use by all
postgraduate students and early career researchers: This academic
year
• Public Website launch: http://datalib.edina.ac.uk/MANTRA
• Download/re-brand/re-purpose materials from JorumOpen in standards
compliants formats (forthcoming)
• Software modules – data handling practicals (MS Word)

33. Lessons learned
Time – underestimated!
Authoring content – not an easy task...
• Re-using existing materials vs writing from scratch
• Copyright – images, videos (where possible open
or CC-licensed materials)
• Consistency in style, terminology, tempo
Setting up Xerte Online Toolkits (XOT) on the server
• Security issues
• Issues with the software

34. Lessons learned
Working with a default XOT template
• Limitations of the template
Use ‘reward’ to engage volunteers for user
testing
Issues with data handling practicals:
• Tension between data handling and
data analysis in terms of actual content
• Ensuring clear explanation of
software specific jargon/technical
terminology/process-specific
language
• Retaining consistency across four
data handling practicals in terms of
look and feel, flow, content, audience

35. Links
IASSIST: http://www.iassistdata.org/
Data Library services: http://www.ed.ac.uk/is/data-library
EDINA: http://edina.ac.uk/
Research data management guidance pages:
http://www.ed.ac.uk/is/research-data-management
Edinburgh University data policy:
http://www.ed.ac.uk/is/research-data-policy
Policy-making for Research Data in Repositories - A Guide:
http://www.disc-uk.org/docs/guide.pdf
Edinburgh Data Audit Framework (DAF) Implementation:
http://ie-repository.jisc.ac.uk/283/
Research data MANTRA course: http://datalib.edina.ac.uk/mantra

36. THANK YOU!
stuart.macdonald@ed.ac.uk
Acknowledgements
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