The document discusses the importance of research data management (RDM) and the evolving role of libraries in supporting institutions with their data needs. It highlights the challenges of managing research data, including quality, preservation, and compliance with funding mandates, while emphasizing the necessity for libraries to enhance their skills in this area. The Digital Curation Centre plays a crucial role in providing support and resources for improving RDM capabilities across higher education institutions.

1. Supporting Libraries in
Leading the Way in
Research Data Management
Marieke Guy, Institutional Support Officer,
Digital Curation Centre, UKOLN, University of Bath, UK
Email: m.guy@ukoln.ac.uk
Twitter Id: mariekeguy
Web: http://www.dcc.ac.uk
Online Information, 20th -21st November 2012
UKOLN is supported by:
This work is licensed under a Creative Commons Licence
Attribution-ShareAlike 2.0
1

2. Who Am I?
• Have worked for UKOLN for over 12 years
• Worked on variety of projects:
Subject portals project, IMPACT, Good APIs,
JISC Observatory, cultural heritage work,
digital preservation work, …etc
• Remote worker, into amplified events
• Co-chair of IWMW for a number of years
• Now working for Digital Curation Curation
• Institutional Support Officer helping HEIs with their RDM
2

3. Today’s Talk
• Research data and why is it so important?
• How research data is managed
• What the DCC does
• The role libraries are currently playing
• The role libraries could be playing in the future
3

4. http://www.google.co.uk/imgres?q=illumina+bgi&hl=en&client=firefox-
a&hs=Jl2&rls=org.mozilla:en-GB:official&biw=1366&bih
Research Data
http://www.flickr.com/photos/think
mulejunk/352387473/
http://www.flickr.com/photos/usf
sregion5/4546851916
http://www.flickr.com/photos/wasp
http://www.flickr.com/photos/charleswelch/3 _barcode/4793484478/
4 597432481/

5. What is Research Data?
…whatever is produced in research or evidences its outputs
• Facts
• Statistics
• qualitative
• quantitative
• Not published
research output
“highest priority research data is that which • Discipline specific
5 underpins a research output”

6. A Data Present
“Data underpins our economy and
our society - data about how
much is being spent and where,
data about how schools, hospitals
and police are performing, data
about where things are and data
about the weather.”
Tim Berners Lee, director of W3C.
6

7. Big Data
• Volume
• Velocity
• Variety
“The 1000 Genomes Project generated more DNA
“The 1000 Genomes Project generated more DNA
sequence data in its first 6 months than GenBank
sequence data in its first 6 months than GenBank
7 had accumulated in its entire 21 year existence”
had accumulated in its entire 21 year existence”

8. A Data Future
“The ability to take data - to
be able to understand it, to
process it, to extract value
from it, to visualise it, to
communicate it -that’s going to
be a hugely important skill in
the next decades.”
Hal Varian, Google’s chief economist.
8
Hal Varian, Chief Economist, Google

9. Big Data…and Small Data
• DIY data
• Consumer data
• Crowd Sourced data
• What about Linked data/
Web of data/Open data?
• Databases
• Learning data
• Administrative data
• Long tail data
r os s project: “
JIS C MaRDI-G ast significant
e le ce
vo lume is th resent context, sin
ep
(is sue) in th al problem
”
hnic
it i s ‘ o nly’ a tec
9

10. Some Data Issues
• Scale and complexity – data
deluge – volume, pace
• Infrastructure and management
– Storage, costs & sustainability
• Quality of data
• Reputation – FOI, DPA, computer
misuse
• Openness agenda
• Preservation
• Working in partnerships
• Funding for researchers
10

11. Funding…the Biggest Carrot/Stick?
EPSRC expects all those institutions it funds:
•to develop a roadmap that aligns their policies and processes with
EPSRC’s expectations by 1st May 2012;
•to be fully compliant with these expectations by 1st May 2015.
•http://www.epsrc.ac.uk/about/standards/researchdata/Pages/expectat
ions.aspx
11

12. Data Policies of Funders
http://www.dcc.ac.uk/resources/policy-and-legal/overview-funders-data-policies
12

13. What is Research Data Management?
“the active management and
appraisal of data over the
lifecycle of scholarly and
scientific interest”
Data management is part of
good research practice
13

14. How is Research Data Managed?
Some areas to think about:
Leicester
University
Data
management
support for
researchers
Web site
• Storage & cloud • Curation
• Data repositories • Digital Preservation
• Metadata & citation • Migration
• File naming • Sharing/openness
• Appraisal, selection & • Security
deletion • Cost
14

15. RDM Activities
What kind of activities are involved?
– producing and sharing of data with research colleagues
in collaborative environments (internal and external)
– file naming
– applying metadata for context and discovery
– ensuring that sensitive data is not shared or accessible
– cleaning data for longer-term use
– selecting mechanisms for data capture and storage
– selecting and appraising data for short and longer-term
retention
– licensing data for reuse
– developing data management plans
•Data management is about making informed decisions
15

16. The Digital Curation Centre
• A consortium comprising units from the Universities of Bath
(UKOLN), Edinburgh (DCC Centre) and Glasgow (HATII)
• launched 1st March 2004 as a national centre for solving
challenges in digital curation that could not be tackled by
any single institution or discipline
• Funded by JISC with additional HEFCE funding from 2011
for the provision of support to national cloud services
• Targeted institutional development
• http://www.dcc.ac.uk/
16

17. Advocacy and Training
How to…
• Appraise and Select
Research Data
• Cite Datasets and Link to
Publications
• Develop a Data
Management and Sharing
Plan
• License Research Data
• Set a RDM service –
coming soon!
How to cite data
17

18. 18

19. DCC Tools for Engagement
Survey and interview
methodology for
investigating data holdings
and how they are managed
Capability model for establishing
consensus on capabilities and
gaps in current provision, rating
organisation, technology and
resources
Customised institutional
templates for data
management planning
19

20. Institutional Engagement Work
• Funded by the HEFCE through its Universities
Modernisation Fund (UMF)
• Intensive, tailored support to increase research data
management capability
• Originally 18 Higher Education Institutions (HEIs) between
Summer 2011 and Spring 2013
• Can help:
– win the support of senior management
– understand current data practices
– redesign data support services
– Help with policy development and training
20

21. What Part are Libraries Playing?
• RDM requires the input of all support services, but libraries
are taking the lead in the UK
• The library is leading on most of the DCC engagements
Other examples include:
–EDINA at University of
Library Information
Edinburgh
managementthe a
–Bodleian Library at is
University of Oxford
Research key skill in RDM, so
–Subject librarians at
Office it’s a major role for
University of Southampton
IT librarians
21

22. Why are Libraries Taking the Lead?
Because libraries:
•Often run publication repositories so are the stakeholder
called on when questions are raised about the
management of associated data
•Have directed the open sharing of publications so are
well placed to advice on how best to support data
requirements
•Have good relationships with researchers and good
connections with other service departments
•Have a highly relevant skill set
22

23. An Exciting Opportunity
“Researchers need help to
manage their data. This is a
really exciting opportunity for
libraries….”
Liz Lyon, VALA 2012
• Leadership
• Providing tools and support
• Advocacy and training
• Developing data informatics capacity & capability
23

24. Reskilling for Research
But librarians feel they lack appropriate skills…
Skills gap 2-5 years Now
Preserving research outputs 49% 10%
Data management & curation 48% 16%
Complying with funder mandates 40% 16%
Data manipulation tools 34% 7%
Data mining 33% 3%
Metadata 29% 10%
Preservation of project records 24% 3%
Sources of research funding 21% 8%
Metadata schema, disciplinary standards, practices 16% 2%
From RLUK, Re-skilling for Research, Jan 2012, p43
24 Other surveys include DataOne, Cologne Uni, DigCurV

25. Specialist Knowledge
“Very few librarians are likely to
have specialist scientific or
medical knowledge - if you train
as a research scientist or a medic,
you probably won’t become a
librarian.”
Mary Auckland: Reskilling for Research 2012,
RLUK.
25

26. Knowledge Needed…
• Librarians are overtaxed already, lack personal research
experience, have little understanding of complexity and
scale of issue
• Need knowledge and understanding of:
– Researchers’ practice and data holdings
– Research Councils and funding bodies’ requirements
– Disciplinary and/or institutional codes of practice and
policies
– Existing institutional policies and infrastructure
– Reputational risks associated with poor data
management – with respect to researchers’ reputations
as well as that of their institutions
– Data management and sharing benefits
– Research data management tools and technologies
26

27. And Needed Fast…
Implications of “Big Data”
and data science for
organisations in all sectors
McKinsey Global Institute
predicts a shortage of
190,000 data scientists by
2019
http://www.mckinsey.com/Insights/MGI/Research/Technology_and_Inno
27
vation/Big_data_The_next_frontier_for_innovation

28. Is Retooling Possible?
“Significant mismatches exist between research
data and library digital warehouses, as well as
the processes and procedures librarians typically
use to fill those warehouses. Repurposing
warehouses and staff for research data is
therefore neither straightforward nor simple; in
some cases, it may even prove impossible.”
Salo, D. (2010) Retooling Libraries for the Data Challenge,
Ariadne, Issue 64.
• Libraries are organised, research data isn’t
• Need technical systems such as sheer curation, better
sharing of data and improved funding models
28

29. Possible Approaches
• University of Helsinki Library – Knotworking “collaborative
performance between otherwise loosely connected actors
and activity systems”
• University Burnaby, British Columbia - providing research
data services since the 1970s – currently exploring funding
gaps
• Deutsche Nationalbibliothek - DP4lib project (Digital
Preservation for libraries) where the library is acting as a
service-broker for digital data curation
• Research libraries - Opportunities for Data Exchange (ODE)
project as an exemplar project, which gives shares
emerging best practice
• Data intelligence 4 librarians, Delft University of
Technology
29

30. Training Librarians: RDMRose
• JISC funded project to produce OER learning materials in
RDM tailored for Information professionals
• Led by Sheffield University iSchool
• Practitioner community based on the White Rose University
Consortium’s libraries at the Universities of Leeds,
Sheffield and York
• Deliverables include curriculum, module within taught
masters course in Sheffield, self study version
• Much of course concentrates on teaching librarians about
research and the research process
• RDMRose working with Stephen Pinfield on a web-based
survey of current library RDM activity
• http://www.sheffield.ac.uk/is/research/projects
30

31. Informatics Transform
• Library & institutional stakeholders
• Roles (7 listed): Responsibilities,
Requirements, Relationships
1. Director IS/CIO/University Librarian
2. Data librarians /data scientist /
liaison/subject/faculty librarians
3. Repository managers
4. IT/Computing Services
5. Research Support/Innovation Office
6. Doctoral Training Centres
7. PVC Research
Liz Lyon, Informatics Transform, Ariadne Issue 68, 2012
31

32. Partnership Approaches
• Research 360,
University of Bath:
• UKOLN-DCC
• Library
• IT services
• Research
Support Office
• Doctoral
Training
Centres
http://blogs.bath.ac.uk/research360/
32

33. Embedded Librarians
“Librarians may need to raise their
profile, become ‘researchers’
themselves; getting embedded in the
research community;
gaining credibility; and collaborating
as equals.”
Bent et al, 'Information literacy in a researcher's
learning life' in New Review of Information
Networking, 13 (2), 2007
33

34. So What Next?
• Address the lack of data informatics skills
• Mainstream data librarians & data scientists
• Embed new skills into LIS & iSchool curriculum
Lyon, ‘The Informatics Transform: re-engineering libraries for
the data decade’ in IJDC, 7(1), 2012
hts the
an ag ement highlig bracing
Re search data m n’s skillset. By em
licability of the libraria t, librarians
will
ap p u ppo r
p rovide RDM s d as .
the need to of institutional agen
remain at the heart
34

35. Resources to Look at…
• Riding the Wave report and many others emphasise the
relevance of research data to current academic working
• RLUK/Mary Auckland: Reskilling
for Research
• Sheila Corrall: Libraries,
Librarians and Data
• DigCurv
• Book: Managing Research Data
• HEIs research data support
pages
35

36. Thank You
• Thanks to DCC colleagues for contributing to slide material.
Any questions?
m.guy@ukoln.ac.uk
36