An overview of Research Data Management: the research process from developing ideas to preservation of data; funder perspectives, the impact on the wider service, Data Asset Frameworks, preservation and access, and cost implications.

1. Dr Birgit Plietzsch, Research Computing Team Leader
RDM within Research Computing support
SALCTG, 18 June 2013

2. RDM: The destination
“The next generation of scientific discovery will be data-driven
discovery. ... We need to make sure we capture value from
this mass of data – both for economic growth and for social
advances, such as better health. ... This requires a
transformation in data management.”
(Speech by the Chancellor of the Exchequer, Rt Hon George Osborne MP, to the Royal Society
(9 November 2012))
“As a first step towards this
intelligent openness, data
that underpin a journal
article should be made
concurrently available in an
accessible database. We are
now on the brink of an
achievable aim: for all
science literature to be
online, for all of the data to
be online and for the two to
be interoperable.”
(The Royal Society. Science as an Open
Enterprise: The Royal Society Science Policy
Centre Report 02/12 (June 2012), p. 7)

3. • National / international effort:
– Economic benefits
– Subject-specific, not institutional
• RDM affects the entire University:
– Training and advice:
• Creation
• Access & Sharing
• Metadata
• Appraisal and selection
– Storage and technical maintenance
– Cataloguing
– Physical space:
• ICT infrastructure
• Paper records
– Strategies, policies and procedures:
• University-level
• HR
• Service-level
– Cost recovery
• Finance Advice and Support team
• Requirement for processes:
– RDM planning:
• Project
• Service providers
• Long-term access:
– Digital preservation
RDM: The journey
Research Computing Service interfaces
with RDM
• Training & advice: data creation, long-
term storage, technical standards
• Storage and technical maintenance
• Service-level strategy & procedures
• Cost recovery
• RDM planning (at project and service
level)
• Technical solutions for RDM and digital
preservation

4. Research Computing Service
2003 Arts Computing Advisor
2008 Developer for Arts and Humanities projects
2011 Research Computing Service
2013 University approval for 2 new posts:
- Research Computing Advisor
- Applications Developer (Research Computing)
Vision
To provide innovative and advanced digital technologies and research
computing services of nationally and internationally recognised quality and
standards, which will facilitate research excellence at the University of St
Andrews.
(Research Computing Strategy, http://www.st-andrews.ac.uk/itsupport/academic/research/about/strategy/ )

5. Research projects
(pre-)
application
stage
• Development of ideas
Technical requirements gathering (software, hardware, technical development and data requirements)
• Planning the Research Computing Service
• Cost recovery
Project
stage
• Confirmation of requirements
• Technical development work
• Storage and backup
• Enabling access & sharing
• Training
Post-
project
stage
• Hosting of research outcomes
 enabling access & sharing
 enabling use & re-use
• Technical maintenance
• [long-term preservation]
University / service view

6. Research projects
Funder perspective
•“This is an exceptionally well written proposal, setting out its general goals with clarity.
The applicant gives confidence at every level, presenting few issues for thought or
clarification. The digital outcomes are well defined, and supported by relevant
resources and management. This is likely to produce a very successful resource, with
usefulness to scholars and the general public alike.”
Quality of applications
•“The IT people will be very important in this project, and I don't know them, but
certainly the on-line databases provided by St Andrews which I have used are reliable
both technically and intellectually. It seems safe to assume, therefore, that this side of
things will also be successful.”
Technical support / skill
available to the project
team
•“It is good to see the technical work being carried out in the context of an institutional
commitment to the digital humanities, as evidenced by the University's Arts Research
and Teaching Server and the support of the university's Research Computing Team.”
Institutional
commitment /
sustainability of project
outcomes

7. Research Computing Service
Generic needs
School 1
• Project 1a
• Project 1b
School 2
• Project 2a
• Project 2b
School 3
• Project 3a
• Project 3b
Shared
solution
Repository-type solutions
Image database
(http://imagedatabase.st-andrews.ac.uk/)
Digital Archive
Digital Collections Repository
(http://arts.st-andrews.ac.uk/digitalhumanities/)
reduction of resource required for
development and technical
maintenance
speed of service
subject & project-specific
description needs

8. Impact of RDM on the service
• Formalisation of procedures
– RDM planning (DMPonline?)
– Service review (Data Asset Framework, CARDIO)
• Increase in scale and volume of activities
• Increased co-operation with other parts of the
University
• Technically accommodate better use and re-use of data
• Long-term storage requirement
– Digital preservation starts at the point of data creation!
• Cost recovery

9. Data Asset Framework
(DAF)
• Framework for auditing of departmental data
collections, awareness, policies and practice for data
curation and preservation
– Online tool: http://www.data-audit.eu/tool2/
• Get an idea of current RDM practices within academic
Schools
• Interviews using open questions:
– Managing Data
– Access and Sharing
– Preservation and Archiving
– Existing RDM support provision
– RDM policy

10. DAF Action Points
(Science Schools)
• Provide training in RDM
• Produce a comprehensive list of services offered centrally
• Improve the responsiveness and flexibility of central services
to better meet the needs of researchers
• Undertake extensive outreach and advocacy work to build
awareness of and trust in central services

11. DAF Action Points
(Arts Schools)
• Confirmation of existing central research computing support
service provision:
– Applications for funding / RDM planning
– Technical development work
– Training
• Long-term storage / digital preservation
• Requests for support of unfunded research

12. Collaborative Assessment of
Research Data Infrastructure and
Objectives (CARDIO)
• Benchmarking tool for data management strategy
development, typically applied at the department
or research group level
– Online tool: http://cardio.dcc.ac.uk/
• Involvement:
– Data creators (DAF)
– Information managers
– Service providers
• Monitor service provision
– Alignment with institutional goals and academic
requirements

13. Use and re-use of data
• Technology can accommodate some of this
• Development of flexible solutions
– APIs
• Programming code is data!
– Open Source / Open Standard solutions
• Economics
• Active developer community
• Long-term commitment
• Visualisation / Analysis tools

14. Long-term access
• Need for digital preservation:
– What?
– How?
– How long for?
• Technical and procedural components
– Digital archiving project

15. Open Archival Information
System (OAIS)
ISO 14721:2003
Functional Overview

16. OAIS procedural overview

17. Cost of RDM
• For example:
– Hardware
– Software
– Storage & backup
• Rule of thumb: 1TB = £30k over 25 years
– Staff:
• Hardware implementation and maintenance
• Technical development
• preparation of the data for access and curation (incl. the addition
of metadata)
• Data collection
• Data analysis
• Sharing

18. Cost of RDM: Funder perspective
• RCUK Common Principles on Data Policy
(http://www.rcuk.ac.uk/research/Pages/DataPolicy.aspx):
– Principle 7: “It is appropriate to use public funds to support the management
and sharing of publicly-funded research data. To maximise the research
benefit which can be gained from limited budgets, the mechanisms for these
activities should be both efficient and cost-effective in the use of public
funds.”
• Efficient use of such money
• Funders are looking for research benefits where money is spent.
– Principle 2: “Institutional and project specific data management policies and
plans should be in accordance with relevant standards and community best
practice. Data with acknowledged long-term value should be preserved and
remain accessible and usable for future research.”
• Not all data should remain accessible or be preserved.
• Retention of data is the decision of the researcher. If data is kept, it should be kept in
accordance with funder policies.

19. Cost of RDM: Funder perspective
• DMP: principles under which the data is going to be made
available
• Institutional plan, policy or operational document:
institutional infrastructure that is provided for making data
available
• Justification of Resources of applications for funding:
– What exactly it is that they expect funders to pay?
• the cost of collecting data
• the cost of curating data
• the cost of analysing data
• the cost of preservation and sharing
• Further detail:
http://research-computing.wp.st-andrews.ac.uk/2013/05/01/funding-rdm/

20. Further resources
• DCC web site: http://www.dcc.ac.uk
• JISC MRD
– Some projects to look at via:
http://www.jisc.ac.uk/whatwedo/programmes/mrd.aspx
• Books
– Graham Pryor (ed.) Managing Research Data (2012)
– Adrian Brown. Practical Digital Preservation (2013)

21. Summary
• RDM requires co-operation across institutions
• Research Computing:
– Contribute towards RDM planning
– Provide and maintain technical solutions
– Contribute towards costings / institutional cost
recovery
– Contribute towards RDM training
• RDM is bigger than that!

22. Any questions ?
Dr Birgit Plietzsch, Research Computing Team Leader
bp10@st-andrews.ac.uk
01334 462315
@birgitplietzsch
blog: http://research-computing.wp.st-andrews.ac.uk/