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Staffing Research Data Services at
University of Edinburgh
Robin Rice
Data Librarian and Head, Research Data Support
Information Services
Goettingen, 28 May, 2019
 About UoE and Information Services
 Maturity model, RDM services
 Research Data Mgm’t Policy
 Data service components
 RDM funding model
 Staffing profile and costs
 Data skills and competencies
2
Overview
About University of Edinburgh
• Founded 1583
• 39,576 students
• 14,346 postgraduate students
• 6,816 academic staff
• Research income: £253.9 million
(2015-16)
• Mission: the creation, dissemination
and curation of knowledge
• 20 schools in 3 colleges:
– Arts, Humanities & Social Sciences
– Medicine & Veterinary Medicine
– Science & Engineering
3
© www.nealesmith.com
About UoE Information Services
• Library & University
Collections
• IT Infrastructure
• Applications
• Learning, Teaching &
Web
• User Services
• Information Security
• EDINA
• Digital Curation
Centre
4
Argyle House © CoStar
A maturity model for RDM services
Cox, A. et al. “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 - September 2017 p. 2191.
DOI: 10.1002/asi
University’s RDM Policy (May, 2011)
https://www.ed.ac.uk/is/
research-data-policy/
Policy by Nick Youngson CC BY-SA 3.0 Alpha Stock
Images
• Commitment to
research integrity,
DMPs, open data
• Articulates clear
responsibilities of the
researcher and of the
institution
6
UoE Research Data Service = Tools and support
for working across the data lifecycle
7
https://www.ed.ac.uk/is/research
-data-service
Tools and Support Description
DMPOnline Online tool to create a data
management plan, based on
University and funders’ templates
Support and DMP Review Answer enquiries and review plans,
provide advice; in-depth or quick
turaround
Sample DMPs Library of successful plans to show
researchers in different disciplines
Before your research project begins
8
Tools and Support Description
Discover and re-use data Data portal and data librarian consultancy;
help with accessing / purchase of datasets or
data subscriptions
Active data storage (DataStore) Central, backed up storage for all researchers
- individual and shared spaces
Sensitive data
(Data Safe Haven)
New, secure facility for working with sensitive
data on remote server. We are pursuing ISO
27001 security certification
Code versioning (Subversion,
Gitlab)
Private or public software code storage and
management. Documents all code and allows
rollback to prior versions
Collaboration and data sync’ing
(DataSync)
Open source tool to allow external partners
to access your research data
Electronic Lab Notebook
(RSpace)
Data management for laboratory based
research; interoperable with local systems
Research in progress
9
Tools and Support Description
Open Access data repository
(DataShare)
Allows researchers to share
data publicly and preserve for
long-term
Long-term retention
(DataVault)
Deposit datasets for a specified
retention period (for example,
10 years), immutable copy
Data asset register through the
University CRIS (Pure for
datasets)
Record a description of your
dataset along with your
publications and research
projects
Approaching completion
10
Tools and Support Description
General RDM support Answer enquiries by email, phone or
appointment; track through helpdesk system
Online training (MANTRA
and RDMS MOOC)
Learn online at your own pace or with a cohort
of peers through our open educational
resources
Scheduled and bespoke
training
Sign up for a scheduled workshop or request a
special training session for your research group
Research Data Service
website
All the tools and support in one place,
increasingly self-serve
Blog and promotional
materials
New developments on our Research Data Blog.
Service video and brochure
Dealing with Data annual
event & workshop series
Annual conference of researchers talking about
their data challenges and solutions
Research Data Workshop
series in various settings
Compact, catered networking events for
researchers to engage with the service & each
other about challenging topics
Training and support throughout your project
Funding model
• Before 2012 – teams in IS contribute to a patchy RDM programme with
existing core funds and external projects
• From 2012, capital and recurrent funds are secured from the university to
cover the human and physical infrastructure needed to support the
services. A service owner provides oversight across teams.
• Capital funding provides initial purchase of key infrastructure.
• Replacement costs (e.g. storage discs) are paid by charges for some
services, to be recovered from research funders through costs in grants.
• From 2016, new services developed through Digital Research Services
programme, in which projects compete for university investment (e.g.
Data Safe Haven, DataVault).
Staffing profile – across library and IT teams
• Senior staff: data librarian and two team leaders –
librarian or equivalent background, Masters and PhD
• 1 p/t Research Data Support Officer – trainer background
• 3 (2.5 FTE) Research Data Support Assistants (research
backgrounds, subject Masters and PhD)
• IT infrastructure manager and 2 IT systems engineers
• 1.5 software engineers
Staff funded by dedicated RDM allocation
• Senior staff: data librarian and two team leaders –
librarian or equivalent background, Masters and PhD
• 1 p/t Research Data Support Officer – trainer background
• 3 (2.5 FTE) Research Data Support Assistants (research
backgrounds, subject Masters and PhD)
• IT infrastructure manager and 2 IT systems engineers
• 1.5 software engineers
Valued skills and priorities in RDM services
(A. Cox, et al)
Cox, A. et al. “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 - September 2017 p. 2191. DOI: 10.1002/asi
• “Personal Attributes” - most highly rated category overall (70%
respondents ranked Very important +)
• “Library Skills” - lowest rated category (40%)
• Top 5 items: “Developing relationships with researchers, faculty,
etc.”; “Oral communication and presentation skills”; “Teamwork
and interpersonal skills”; “Written communication skills”; and
“One-on-one consultation or instruction.”
• Bottom 5 items: “PhD or doctoral degree”; “Professional
memberships”; “Cataloging”; “Graduate degree in a [subject
discipline]”; & “Collection dev’t.”
Soft skills highly rated in a study of librarians doing
data-related work
Federer, Lisa. (2018). Defining data librarianship: A survey of competencies, skills, and training.
Journal of the Medical Library Association. 106. 10.5195/JMLA.2018.306.
Vielen Dank!
R.Rice@ed.ac.uk
@sparrowbarley
https://www.ed.ac.uk/is/research-data-service

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Staffing Research Data Services at University of Edinburgh

  • 1. Staffing Research Data Services at University of Edinburgh Robin Rice Data Librarian and Head, Research Data Support Information Services Goettingen, 28 May, 2019
  • 2.  About UoE and Information Services  Maturity model, RDM services  Research Data Mgm’t Policy  Data service components  RDM funding model  Staffing profile and costs  Data skills and competencies 2 Overview
  • 3. About University of Edinburgh • Founded 1583 • 39,576 students • 14,346 postgraduate students • 6,816 academic staff • Research income: £253.9 million (2015-16) • Mission: the creation, dissemination and curation of knowledge • 20 schools in 3 colleges: – Arts, Humanities & Social Sciences – Medicine & Veterinary Medicine – Science & Engineering 3 © www.nealesmith.com
  • 4. About UoE Information Services • Library & University Collections • IT Infrastructure • Applications • Learning, Teaching & Web • User Services • Information Security • EDINA • Digital Curation Centre 4 Argyle House © CoStar
  • 5. A maturity model for RDM services Cox, A. et al. “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 - September 2017 p. 2191. DOI: 10.1002/asi
  • 6. University’s RDM Policy (May, 2011) https://www.ed.ac.uk/is/ research-data-policy/ Policy by Nick Youngson CC BY-SA 3.0 Alpha Stock Images • Commitment to research integrity, DMPs, open data • Articulates clear responsibilities of the researcher and of the institution 6
  • 7. UoE Research Data Service = Tools and support for working across the data lifecycle 7 https://www.ed.ac.uk/is/research -data-service
  • 8. Tools and Support Description DMPOnline Online tool to create a data management plan, based on University and funders’ templates Support and DMP Review Answer enquiries and review plans, provide advice; in-depth or quick turaround Sample DMPs Library of successful plans to show researchers in different disciplines Before your research project begins 8
  • 9. Tools and Support Description Discover and re-use data Data portal and data librarian consultancy; help with accessing / purchase of datasets or data subscriptions Active data storage (DataStore) Central, backed up storage for all researchers - individual and shared spaces Sensitive data (Data Safe Haven) New, secure facility for working with sensitive data on remote server. We are pursuing ISO 27001 security certification Code versioning (Subversion, Gitlab) Private or public software code storage and management. Documents all code and allows rollback to prior versions Collaboration and data sync’ing (DataSync) Open source tool to allow external partners to access your research data Electronic Lab Notebook (RSpace) Data management for laboratory based research; interoperable with local systems Research in progress 9
  • 10. Tools and Support Description Open Access data repository (DataShare) Allows researchers to share data publicly and preserve for long-term Long-term retention (DataVault) Deposit datasets for a specified retention period (for example, 10 years), immutable copy Data asset register through the University CRIS (Pure for datasets) Record a description of your dataset along with your publications and research projects Approaching completion 10
  • 11. Tools and Support Description General RDM support Answer enquiries by email, phone or appointment; track through helpdesk system Online training (MANTRA and RDMS MOOC) Learn online at your own pace or with a cohort of peers through our open educational resources Scheduled and bespoke training Sign up for a scheduled workshop or request a special training session for your research group Research Data Service website All the tools and support in one place, increasingly self-serve Blog and promotional materials New developments on our Research Data Blog. Service video and brochure Dealing with Data annual event & workshop series Annual conference of researchers talking about their data challenges and solutions Research Data Workshop series in various settings Compact, catered networking events for researchers to engage with the service & each other about challenging topics Training and support throughout your project
  • 12. Funding model • Before 2012 – teams in IS contribute to a patchy RDM programme with existing core funds and external projects • From 2012, capital and recurrent funds are secured from the university to cover the human and physical infrastructure needed to support the services. A service owner provides oversight across teams. • Capital funding provides initial purchase of key infrastructure. • Replacement costs (e.g. storage discs) are paid by charges for some services, to be recovered from research funders through costs in grants. • From 2016, new services developed through Digital Research Services programme, in which projects compete for university investment (e.g. Data Safe Haven, DataVault).
  • 13. Staffing profile – across library and IT teams • Senior staff: data librarian and two team leaders – librarian or equivalent background, Masters and PhD • 1 p/t Research Data Support Officer – trainer background • 3 (2.5 FTE) Research Data Support Assistants (research backgrounds, subject Masters and PhD) • IT infrastructure manager and 2 IT systems engineers • 1.5 software engineers
  • 14. Staff funded by dedicated RDM allocation • Senior staff: data librarian and two team leaders – librarian or equivalent background, Masters and PhD • 1 p/t Research Data Support Officer – trainer background • 3 (2.5 FTE) Research Data Support Assistants (research backgrounds, subject Masters and PhD) • IT infrastructure manager and 2 IT systems engineers • 1.5 software engineers
  • 15. Valued skills and priorities in RDM services (A. Cox, et al) Cox, A. et al. “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 - September 2017 p. 2191. DOI: 10.1002/asi
  • 16. • “Personal Attributes” - most highly rated category overall (70% respondents ranked Very important +) • “Library Skills” - lowest rated category (40%) • Top 5 items: “Developing relationships with researchers, faculty, etc.”; “Oral communication and presentation skills”; “Teamwork and interpersonal skills”; “Written communication skills”; and “One-on-one consultation or instruction.” • Bottom 5 items: “PhD or doctoral degree”; “Professional memberships”; “Cataloging”; “Graduate degree in a [subject discipline]”; & “Collection dev’t.” Soft skills highly rated in a study of librarians doing data-related work Federer, Lisa. (2018). Defining data librarianship: A survey of competencies, skills, and training. Journal of the Medical Library Association. 106. 10.5195/JMLA.2018.306.