A presentation by Professor Stephen Pinfield, professor of information services management, University of Sheffield.

1. Research Data Management
and University Libraries
Andrew M. Cox, Mary Anne Kennan, Liz Lyon,
Stephen Pinfield and Laura Sbaffi
Jisc-CNI Leaders’ Conference, Oxford, 2 July 2018

2. Reporting Research
• Previous research:
– Previous research: On the role of academic libraries and RDM, in
the UK, Ireland, Australia and New Zealand, e.g.
• Kennan, Corrall, & Afzal (2014)
• Cox & Pinfield (2014)
– Project 1: International RDM and libraries survey (Australia,
Canada, Germany, Ireland, Netherlands, New Zealand, UK): Sept-
Dec 2014
• Cox, A. M., et al. (2017)
– Project 2: Second survey, extended to USA: Jan-Mar 2018
• Ongoing analysis and writing up
• This presentation:
– Early sight of highlights from the 2018 data
– Provisional comparison with 2014 findings
– Initial insights into developing maturity of RDM/RDS
2

3. ‘Maturity’
• ‘Maturity’:
– “…as knowledge about, and services in, a particular
area reach a full or complete level of development,
they are ‘mature’”
• Concept applied in e.g.:
– Software engineering
– Data governance
– Digital preservation
– Data-intensive research
• Maturity models in e.g.:
– RDM (ANDS, 2011)
– Research projects’ data
management (Crowston & Qin, 2011)
But ‘maturity’ concept
problematic:
• May wrongly imply a
single development path
with a single end point
• May imply certain points
on the path are ‘under-
developed’ or ‘immature’
3

4. Developing Support and Services:
Maturity Model
Maturity
Time
RDM training/data literacy
Advisory services (awareness of
data archives, publication, citation,
storage, DMP tools, rights/IP)
Services & Support
Advisory (non-italic) and Technical (italic)
Policy, Insight &
Capability
RDM policy
RDM governance boards
Skills
Roles
Structures
Web resource/guides
Data repository
Technical support (selection,
catalogue, curation,
preservation, metadata)
Data analysis/visualization
RDM shared services
Audits & surveys
Cultural acceptance
Embedded practices
Level 3
Extensive
Level 0
None
Level 1
Basic
Level 2
Developing
Compliance
Capacity-building
Stewardship
Re-engineering
(Cox, Kennan, Lyon & Pinfield, 2017)
4

5. Research Questions
1. What is the character of RDS development
internationally?
a. What types of services are being offered?
b. What types of service are future priority?
c. What are the drivers and barriers to developing RDS?
2. Are there distinct national paths or are patterns or
directions of travel similar?
3. What has changed (become more “mature”) between
2014 and 2018?
a. Have institutions converged on one model of service?
b. Where and why have more advanced types of services
developed?
4. Can we refine our definition of RDM “maturity”?
5

6. Summary of Findings
1. The sector has moved forward in developing policy and
offering services
2. Advisory services are the main type of service
3. The key driver remains funder mandates, but this still
lacks teeth
4. Hence lack of resources and lack of academic staff
engagement remain the main obstacles
5. Libraries have played a key role in leading the
development of RDS
6. Yet there is still perceived to be a significant skills gap
7. The perception of the agenda has not greatly shifted,
with future priorities correlating strongly to 2014
priorities
6

7. Responses
Response
No. of
institutions
invited
Response
rate
2014
response
Australia 34 39 87% 34
Canada 24 74 32% 17
Germany 23 c250 10% 8
Ireland 11 12 92% 7
Netherlands 6 16 38% 12
New Zealand 8 8 100% 7
UK 80 169 47% 85
USA 23 86 27% n/a
Total 209 170
7

8. Formal RDM Policy
8
• 56% have a
policy (38% in
2014)
• 14% are
planning a
policy (46%)
• Canada and NZ
no policies cf
Australia and
UK
• Policy making often early stage in the institutional
RDM programme – but some HEIs have services
without policy
79%
0%
52%
36%
50%
0%
75%
48%
9%
29%
35%
27%
17%
13%
5%
9%
12%
42%
9%
18%
17%
75%
9%
17%
0%
29%
4%
18% 17% 13% 8%
26%
0% 0% 0% 0% 0% 0% 4% 0%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Australia Canada Germany Ireland Netherlands New
Zealand
United
Kingdom
United
States of
America
Have a policy now Planned in next year Planning but more than year
Not planned Don’t know

9. Library Involvement
Policy development
• Library leading or participating
throughout
• In Australia normally RO
leading and library
participating; opposite in the
UK
9
55%
73% 77% 73% 80%
43%
70%
91%
45% 14%
23%
18%
20%
57%
23%
9%
0%
9%
0%
9%
0% 0%
4%
0%0% 5% 0% 0% 0% 0% 3% 0%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Library involvement in developing RDS
Led Participated Did not participate Don't know
Service development
• Library normally described
as leading
39%
50%
68%
38%
80%
40%
58%
47%
52% 25%
32%
38%
20%
60%
33%
37%
6%
13%
0%
13%
0% 0%
7%
11%
3%
13%
0%
13%
0% 0% 3% 5%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Library involvement in policy making
lead participated did not do not know

10. Services Currently Provided
Ranking of services (providing any service – Basic, Well-developed,
Extensive): Advisory rather than technical services predominate
10
1 Promote awareness of reusable data sources, such as data archives 83%
2
Offer advice on copyright and/or intellectual and/or licensing property rights relating
to data and data management 81%
2
Data management training and/or data literacy instruction (e.g. to research students,
early career researchers etc.) 81%
4 Maintaining a web resource/guide of local advice and useful resources for RDM 79%
5 Data Management Planning (DMP) advisory service 76%
5 Offer data citation advisory services 76%
7 Offer data publication advisory services 75%
8 Provide support for search and retrieval of external data sources 73%
9 Offer data storage advisory services 68%
10 Run a data repository/archive/store 67%
…
24 Offer an advisory service on data mining 23%
25
Analyse and visualise datasets using Python scripts, SPSS, R and MS Excel
software 21%
26 Rescue legacy data or perform data triage or forensic data recovery 16%

11. Service Development
• Provision of all services has risen 2014-18
11
1.=no service
2.=basic
service
3.=well
developed
or extensive
service
1.00
1.20
1.40
1.60
1.80
2.00
2.20
2.40
2.60
2018 2014

12. Priorities for Future Development
ANY library
service
now Rank
Top priority
for future
Top
priority
rank
Data Management Planning (DMP) advisory service 76% 5 61% 2
Data management training and/or data literacy instruction (e.g. to research
students, early career researchers etc.) 81% 2
66%
1
Maintaining a web resource/guide of local advice and useful resources for RDM 79% 4 51% 4
Promote awareness of reusable data sources, such as data archives 83% 1 30%
Provide support for search and retrieval of external data sources 73% 8 23%
Offer data citation advisory services 76% 5 29%
Offer data publication advisory services 75% 7 41% 6
Offer data storage advisory services 68% 9 35% 9
Offer an advisory service on data analysis 24% 23 7%
Offer an advisory service on data mining 23% 24 6%
Offer an advisory service on data visualisation 28% 20 8%
Offer advice on copyright and/or intellectual and/or licensing property rights
relating to data and data management 81% 2
41%
6
Provide advisory services on the curation of active data 63% 30% 10
Provide advisory services on the technical aspects of long term data preservation 61% 30% 10
Run a data repository/archive/store 67% 10 56% 3
Offer a service creating or transforming metadata for data or datasets 46% 24%
Provide a data catalogue including your institution’s research data 44% 43% 5
Select, accession and/or deselect and deaccession data/data sets for deposit in a
repository 39%
24%
Prepare data/data sets for deposit in a repository 52% 29%
Carry out the curation of active data 29% 16%
Carry out long term preservation of research data 43% 38% 8
Clean data and carry out data quality checks 26% 9%
Analyse and visualise datasets using Python scripts, SPSS, R and MS Excel software 21% 8%
Support reproducibility, transparency in workflows and research integrity 34% 25%
Rescue legacy data or perform data triage or forensic data recovery 16% 4%
Embed librarians in the laboratory or research project 27% 13%
12

13. Priorities for the Future
• Priorities very similar 2018 cf 2014
• If anything, technical priorities slightly lower
13
1.20
1.40
1.60
1.80
2.00
2.20
2.40
2.60
2.80
2018 2014
1.=no service
2.=basic
service
3.=well
developed
or extensive
service

14. Organisational Structure
A single
individual is
responsible
A team with a
specific focus on
research data is
responsible
A team with a
general remit
for research
support is
responsible
It is spread
across
multiple
teams
Australia 18% 18% 31% 26%
Canada 11% 29% 11% 14%
Germany 15% 42% 15% 12%
Ireland 40% 13% 20% 13%
Netherlands 20% 80% 0% 0%
New Zealand 20% 10% 20% 10%
United Kingdom 25% 17% 22% 10%
United States of America 31% 26% 11% 26%
23% 23% 19% 15%
14
• Sense of how RDM is organised is diverse

15. Additional Skills Required
AUS CAN GER IRE NETH NZ UK USA Rank
Data curation skills 21 16 16 10 3 8 57 21 152 1
Technical and ICT skills (e.g. data
storage, infrastructure, architecture etc.)
21 13 14 6 1 7 45 16 123 5
Subject and or disciplinary knowledge 11 6 14 6 1 4 27 14 83 8
Knowledge of a variety of research
methods (e.g. data analysis, data
visualisation)
22 15 12 10 2 5 51 20 137 2
Knowledge of the research lifecycle 11 7 12 7 0 5 37 8 87 7
Data description and documentation 17 15 14 10 2 7 50 18 133 3
Legal, policy and advisory skills (e.g.
intellectual property, ethics, licencing
etc.)
19 14 16 9 3 7 44 16 128 4
Understanding of research integrity,
reproducibility and transparency
principles
15 12 11 7 1 8 45 16 115 6
Total response rate for the survey as a
whole (could have dropped answering at
this point)
34 24 23 11 6 8 80 23 209
15

16. Drivers
AUS CAN GER IRE NETH NZ UK USA TOT
Funders policy 17 14 4 8 1 4 39 8 95 57%
Publishers policy 3 4 1 0 0 1 6 4 19
institutional policy/strategy 7 1 0 1 0 0 4 2 15
Integrity 7 1 1 1 1 0 12 4 27
FAIR 4 0 1 0 0 0 1 0 6
Open science (incl data
publication)
6 1 0 1 1 0 12 1 22
Needs of researchers 7 5 7 3 1 2 9 7 41 25%
Impact of research 3 2 1 1 1 1 6 4 19
Library role - having the
skills/needing to stay relevant
7 6 8 5 5 3 25 9 68 41%
16
Classified free text responses but large numbers of responses, providing
confidence of validity of the results

17. Drivers
• “Research integrity is a major driver from the Dean of Research now both to
ensure good scholarship and minimise the university's exposure to risk from
poor practice. Open scholarship links closely with the university's mission
and is gaining prominence as a good in itself. The REF requirements for
REF 2027 [sic] and the expectation that data will be included is focusing
academic staff on RDM as are existing funded projects and their
requirements.” (UK)
• “Libraries need to stop navel gazing and look outwards. The Library's RDM
agenda and activities must be better aligned with:
– the research strategies and priorities of the University as a whole
– corporate information management policies and practices including
recordkeeping, data governance and business intelligence
– enterprise IT and architecture approaches.” (AUS)
• “Academic libraries have the expertise to lead and support RDM on
campuses and we are already involved in the data discussions at the early
stages of research. We also have a need to access data resulting from
research so there is a wonderful "full circle" reuse/recyle/upcycle system in
place when we are involved.” (CAN)
17

18. Challenges
Most frequently mentioned challenges were resources, library skills,
academic engagement, collaborations with other central services and
infrastructure:
• Perceived shortfall in library skills combined with resource shortages
both in financial and staffing terms seems to be the main barrier
• Presumably this in turn links to less than whole-hearted institutional
commitment
• Working with other central services and immaturity of infrastructure
were other issues
• Lack of engagement from researchers was also a major factor
• Other factors fairly commonly mentioned were on collaboration
between support services and infrastructure
• One of the newly added challenges was competition with publishers
18

19. Challenges
• “Faculty apathy for sharing; culture of research antithetical to
sharing in some disciplines; IP/Security; Indigenous ownership of
data makes agreements for openness/sharing complex;
administrative burden of well managed data; costs of maintaining
data over time; cross institution and international partnerships
increases complexity of sharing; Budget (ongoing financial support),
staff (subject librarians, data librarians, graduate student peers,
technical support), infrastructure (local repositories, systems
support).” (AUS)
• “A major challenge is doing this as well as everything else. Also,
RDM is much more complex than most other things we do.” (UK)
• “The chicken and egg scenario of RDM remains. You need to have a
service in place to promote effective RDM practices, but it is hard to
fund and develop a service without evidence of demand for that
service, or to decide how to scope it. We are still in advance of
academic demand for RDM” (UK)
19

20. Issues
“The role of publishers, positive and
negative, in this arena. They are marketing
heavily to university faculty and
administration and cutting out libraries from
the discussion.”
20

21. Summary of Findings
1. The sector has moved forward in developing policy and
offering services
2. Advisory services are the main type of service
3. The key driver remains funder mandates, but this still
lacks teeth
4. Hence lack of resources and lack of academic staff
engagement remain the main obstacles
5. Libraries have played a key role in leading the
development of RDS
6. Yet there is still perceived to be a significant skills gap
7. The perception of the agenda has not greatly shifted,
with future priorities correlating strongly to 2014
priorities
21

22. Developing Support and Services:
Maturity Model
Maturity
Time
RDM training/data literacy
Advisory services (awareness of
data archives, publication, citation,
storage, DMP tools, rights/IP)
Services & Support
Advisory (non-italic) and Technical (italic)
Policy, Insight &
Capability
RDM policy
RDM governance boards
Skills
Roles
Structures
Web resource/guides
Data repository
Technical support (selection,
catalogue, curation,
preservation, metadata)
Data analysis/visualization
RDM shared services
Audits & surveys
Cultural acceptance
Embedded practices
Level 3
Extensive
Level 0
None
Level 1
Basic
Level 2
Developing
Compliance
Capacity-building
Stewardship
Re-engineering
(Cox, Kennan, Lyon & Pinfield, 2017)
22

23. References
ANDS. (2011). Research data management framework: Capability maturity guide.
Melbourne: Australian National Data Service. Retrieved from
http://ands.org.au/guides/dmframework/dmf-capability-maturity-guide.html
Cox, A. M., Kennan, M. A., Lyon, L., & Pinfield, S. (2017). Developments in research data
management in academic libraries: Towards an understanding of research data service
maturity. Journal of the Association for Information Science and Technology, 68(9), 2182–
2200. http://doi.org/10.1002/asi.23781
Cox, A. M., & Pinfield, S. (2014). Research data management and libraries: Current
activities and future priorities. Journal of Librarianship and Information Science, 46(4),
299–316. http://doi.org/10.1177/0961000613492542
Crowston, K., & Qin, J. (2011). A capability maturity model for scientific data
management: Evidence from the literature. Proceedings of the American Society for
Information Science and Technology, 48(1), 1–9.
https://doi.org/10.1002/meet.2011.14504801036
Kennan, M. A., Corrall, S., & Afzal, W. (2014). “Making space” in practice and education:
research support services in academic libraries. Library Management, 35(8/9), 666–683.
http://doi.org/10.1108/LM-03-2014-0037
23