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Open data and research 
data management at the 
University of Edinburgh: 
policies and services 
Open Research Data: EPFL 
28 October, 2014 
Robin Rice, R.Rice@ed.ac.uk, 
EDINA and Data Library 
University of Edinburgh
Overview 
• Edinburgh and data-driven science 
• Drivers for Edinburgh (institutional) RDM Policy 
• Research Data Management (RDM) Policy: 
key points, roles and responsibilities 
• RDM Roadmap: implementing the policy 
• RDM training for researchers and support staff 
• Challenges in RDM support & open data advocacy
Uni. of Edinburgh and 
data-driven science 
• School of Informatics, 1998-present 
o Doctoral Training Programme in Data Science, 2014 
• EPCC, 1990-present 
o Supercomputing infrastructure: HECToR and Archer; RDF 
• Information Services (Computing Service, ECDF) 
• Data Library, 1984-present 
o EDINA, 1995-present 
• National e-Science Centre & eSI, 2001-2011 
• Digital Curation Centre, 2004-present 
• University RDM Programme, 2012-present 
• Edinburgh Data Science initiative, 2014
Int/external drivers for 
Edinburgh RDM Policy 
• OECD Principles and Guidelines for Access to 
Research Data from Public Funding, 2007 (& 2004) 
• Research Computing Survey, 2007 
• Data Audit/Asset Framework (DAF), 2008-9 
• Adoption of UK Research Integrity Office’s Code of 
Practice for Research, 2009-10 
• UK funders requiring Data Mgmt & Sharing Plans 
• Publishers requiring underlying data be available 
• ‘Climategate’ E. Anglia University email review, 2009 
• (Summer, 2011: EPSRC “expectations” published)
Edinburgh policy ‘worldle’
UoE RDM Policy: 
key points for open data 
“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.” 
“Any data which is retained 
elsewhere, for example in 
an international data 
service or domain repository 
should be registered with 
the University.” 
• “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.”
Policy: Roles, rights, 
responsibilities 
• Who will support your researcher's planning? 
• Who has responsibility during the research project? 
Who has archival responsibility? 
• Who has rights in the data ? (What about 
collaborative research, what about subjects of 
research?) 
• What responsibilities fall to the individual researcher, 
PI, department, college, university? 
• Are students considered in the policy?
Activities involved in 
RDM 
 Data Management 
Planning 
 Creating data 
 Documenting data 
 Accessing / using data 
 Storage and backup 
 Sharing data 
 Preserving data 
A Data Lifecycle
UoEResearch Data Management 
Roadmap (2012-2015) 
Involvement from across University and Information Services
Support for DMPs 
INVOLVES: 
Research office 
Research administrators 
RDM Coordinator 
DCC (DMPOnline tool) 
Central IT consultants 
Local IT/web support 
Data Library 
Academic Service 
Librarians 
before research 
data are collected 
or created 
Principal Investigator
Data Infrastructure 
INVOLVES: 
Central IT 
Local IT & data mgrs 
Info Services Helpdesk 
IT Consultants 
RDM & IT Committees 
(policy oversight) 
• Half TB storage/researcher 
• Networked, secure backup 
• ‘Dropbox-like’ service 
• Long-term, private vault 
(proposed)
Data Stewardship 
INVOLVES: 
(Data) librarians 
Repository administrators 
Archivists 
Records managers 
Local data managers 
Disciplinary repositories 
Standards bodies 
• Ongoing 
curation of 
completed 
research data 
outputs 
• Access & 
preservation 
• Metadata 
records, DOIs
DataShare Repository
DataShare progress 
Number of Items (datasets) 
Total Latest month (September, 
2014) 
Of which are new 
depositors 
162 15 3 
Total size of deposited items: 111 GB 
Total sessions (end-users and depositors) 
August, 2010 to 18 October, 2014 totalling 16,961 with 9,806 unique visitors 
and 86,698 page views in Google Analytics (chart shows sessions per week).
Data Support 
• General consultancy 
and support service 
throughout the 
research process 
• Training & advocacy 
• Specialised support 
(data collection, 
analysis, visualisation) 
INVOLVES: 
Academic Service Librarians 
Data Librarians 
IT Consultants 
Local IT & Data Managers 
PhD Supervisors & trainers
Research Data MANTRA 
• Openly licensed online learning 
self-paced course in RDM for 
postgrads and early career 
researchers 
• Embedded in at least 3 
graduate schools at UoE 
• Video stories from researchers 
in variety of settings 
• Interactive quizzes make it fun 
• Data handling exercises in four 
software analysis packages 
• “Continuous improvement”: 
Four releases in 4 years 
backlit buddha by .ash on Flickr 
http://datalib.edina.ac.uk/mantra
Academic Service Librarian Training 
 Data Library & User Services 
Division piloted training with 4 
liaison librarians – then all (12 
more) 
 Aimed to reuse MANTRA in a 
blended learning approach for 
academic liaison librarians 
 Materials gathered together in 
the DIY Training Kit for Librarians 
on the MANTRA website 
http://www.mcphee.com/laf/
Benchmark: DCC 2014 UK 
survey - RDM services in place 
n=87 respondents at 61 institutions incl. 24 Russell Group. 
Angus Whyte, DCC, http://www.dcc.ac.uk/blog/rdm-strategy- 
action-glass-half-full
Challenges in RDM support 
& open data advocacy 
• Reaching critical mass of students and academics 
at point of need (timing, priorities, scheduling) 
• ‘Turnaround time’ in writing data management 
plans 
• Identifying ‘RDM’ requests at helpdesk; proper 
routing to expert support 
• Costing intensive data services & in-depth support 
in grants 
• Getting balance right for private and open data 
o Incentivising sharing 
• Working ‘upstream’ in research process is hard
DCC 2014 UK survey results 
Obstacles to RDM provision (Table 8) % (n=87) 
Lack of appropriate staff resources and infrastructure 71% 
Availability of funding 64% 
Low priority for researchers 56% 
Lack of relevant accepted standards 38% 
Lack of knowledge of appropriate solutions 36% 
Lack of appropriate skills and expertise to implement solutions 34% 
Low priority for management 23% 
Pre‐release Briefing 1, 23 April 2014. Angus Whyte, Diana Sisu, DCC.

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Open data and research data management at the University of Edinburgh: policies and services

  • 1. Open data and research data management at the University of Edinburgh: policies and services Open Research Data: EPFL 28 October, 2014 Robin Rice, R.Rice@ed.ac.uk, EDINA and Data Library University of Edinburgh
  • 2. Overview • Edinburgh and data-driven science • Drivers for Edinburgh (institutional) RDM Policy • Research Data Management (RDM) Policy: key points, roles and responsibilities • RDM Roadmap: implementing the policy • RDM training for researchers and support staff • Challenges in RDM support & open data advocacy
  • 3. Uni. of Edinburgh and data-driven science • School of Informatics, 1998-present o Doctoral Training Programme in Data Science, 2014 • EPCC, 1990-present o Supercomputing infrastructure: HECToR and Archer; RDF • Information Services (Computing Service, ECDF) • Data Library, 1984-present o EDINA, 1995-present • National e-Science Centre & eSI, 2001-2011 • Digital Curation Centre, 2004-present • University RDM Programme, 2012-present • Edinburgh Data Science initiative, 2014
  • 4. Int/external drivers for Edinburgh RDM Policy • OECD Principles and Guidelines for Access to Research Data from Public Funding, 2007 (& 2004) • Research Computing Survey, 2007 • Data Audit/Asset Framework (DAF), 2008-9 • Adoption of UK Research Integrity Office’s Code of Practice for Research, 2009-10 • UK funders requiring Data Mgmt & Sharing Plans • Publishers requiring underlying data be available • ‘Climategate’ E. Anglia University email review, 2009 • (Summer, 2011: EPSRC “expectations” published)
  • 6. UoE RDM Policy: key points for open data “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.” “Any data which is retained elsewhere, for example in an international data service or domain repository should be registered with the University.” • “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.”
  • 7. Policy: Roles, rights, responsibilities • Who will support your researcher's planning? • Who has responsibility during the research project? Who has archival responsibility? • Who has rights in the data ? (What about collaborative research, what about subjects of research?) • What responsibilities fall to the individual researcher, PI, department, college, university? • Are students considered in the policy?
  • 8. Activities involved in RDM  Data Management Planning  Creating data  Documenting data  Accessing / using data  Storage and backup  Sharing data  Preserving data A Data Lifecycle
  • 9. UoEResearch Data Management Roadmap (2012-2015) Involvement from across University and Information Services
  • 10.
  • 11. Support for DMPs INVOLVES: Research office Research administrators RDM Coordinator DCC (DMPOnline tool) Central IT consultants Local IT/web support Data Library Academic Service Librarians before research data are collected or created Principal Investigator
  • 12. Data Infrastructure INVOLVES: Central IT Local IT & data mgrs Info Services Helpdesk IT Consultants RDM & IT Committees (policy oversight) • Half TB storage/researcher • Networked, secure backup • ‘Dropbox-like’ service • Long-term, private vault (proposed)
  • 13. Data Stewardship INVOLVES: (Data) librarians Repository administrators Archivists Records managers Local data managers Disciplinary repositories Standards bodies • Ongoing curation of completed research data outputs • Access & preservation • Metadata records, DOIs
  • 15. DataShare progress Number of Items (datasets) Total Latest month (September, 2014) Of which are new depositors 162 15 3 Total size of deposited items: 111 GB Total sessions (end-users and depositors) August, 2010 to 18 October, 2014 totalling 16,961 with 9,806 unique visitors and 86,698 page views in Google Analytics (chart shows sessions per week).
  • 16. Data Support • General consultancy and support service throughout the research process • Training & advocacy • Specialised support (data collection, analysis, visualisation) INVOLVES: Academic Service Librarians Data Librarians IT Consultants Local IT & Data Managers PhD Supervisors & trainers
  • 17. Research Data MANTRA • Openly licensed online learning self-paced course in RDM for postgrads and early career researchers • Embedded in at least 3 graduate schools at UoE • Video stories from researchers in variety of settings • Interactive quizzes make it fun • Data handling exercises in four software analysis packages • “Continuous improvement”: Four releases in 4 years backlit buddha by .ash on Flickr http://datalib.edina.ac.uk/mantra
  • 18. Academic Service Librarian Training  Data Library & User Services Division piloted training with 4 liaison librarians – then all (12 more)  Aimed to reuse MANTRA in a blended learning approach for academic liaison librarians  Materials gathered together in the DIY Training Kit for Librarians on the MANTRA website http://www.mcphee.com/laf/
  • 19. Benchmark: DCC 2014 UK survey - RDM services in place n=87 respondents at 61 institutions incl. 24 Russell Group. Angus Whyte, DCC, http://www.dcc.ac.uk/blog/rdm-strategy- action-glass-half-full
  • 20. Challenges in RDM support & open data advocacy • Reaching critical mass of students and academics at point of need (timing, priorities, scheduling) • ‘Turnaround time’ in writing data management plans • Identifying ‘RDM’ requests at helpdesk; proper routing to expert support • Costing intensive data services & in-depth support in grants • Getting balance right for private and open data o Incentivising sharing • Working ‘upstream’ in research process is hard
  • 21. DCC 2014 UK survey results Obstacles to RDM provision (Table 8) % (n=87) Lack of appropriate staff resources and infrastructure 71% Availability of funding 64% Low priority for researchers 56% Lack of relevant accepted standards 38% Lack of knowledge of appropriate solutions 36% Lack of appropriate skills and expertise to implement solutions 34% Low priority for management 23% Pre‐release Briefing 1, 23 April 2014. Angus Whyte, Diana Sisu, DCC.