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RDM Roadmap@Edinburgh
- an institutional approach
Stuart Macdonald & Robin Rice
EDINA & Data Library
IASSIST, Cologne, 30 May 2013
A JISC-funded pilot project produced 6 case studies from research
units across the University in identifying research data assets and
assessing their management, using DAF methodology developed by
the Digital Curation Centre.
Edinburgh Data Audit Framework (DAF) Implementation Project
(May – Dec 2008)
4 main outcomes:
• Develop online RDM guidance
• Develop RDM training
• Develop university research data management policy
• Develop services & support for RDM (in partnership IS)
Background
• RDM policy* containing 10 aspirational statements affirming
both the researchers’ and the University’s responsibilities, e.g.
• PI responsible for RDM
• University will provide RDM support and training
• University will provide RDM services (such as back-up, storage,
deposit)
• Data retained elsewhere will be registered with the University
• RDM plans must ensure that data are available for access and re-
use under appropriate safeguards
• In 2011, RCUK issued a set of Common Principles on Research
Data Policy which push for data to be made openly available with
as few restrictions as possible. Most funding bodies have issued
data policies, however the extent and coverage of these varies
greatly.
Drivers
* http://www.ed.ac.uk/schools-departments/information-services/about/policies-and-regulations/research-data-policy
An RDM Policy Implementation Committee was set up by the
Vice Principal Knowledge Management Prof. Jeff Haywood to
implement recommendations:
• Membership from across IS
• Charged with delivering services that will meet RDM policy
objectives
• Iterate with researchers to ensure services meet the needs of
researchers
The Vice Principal also established a Steering Committee led by
Prof. Peter Clarke comprising members of Research Committee
from the 3 colleges, IS, DCC and Edinburgh Research and
Innovation (ERI).
Their role is to:
• Provide oversight to the activity of the Implementation
Committee
• Ensure services meet researcher requirements without
harming research competitiveness
Committees
• EPSRC expects funded projects to have developed a roadmap
aligned with EPSRC’s RDM expectations by 1st May 2012, and to
be fully compliant with these expectations by 1st May 2015.
• The Executive Summary of the Information Services Plan, 2012-
13 states, “Research data management & storage – policies,
training, curation, preservation, baseline 0.5Tb/user,” is a major
IS-led project for the year.
• The Edinburgh RDM roadmap was set out as a high level plan for
its delivery, noting objectives, outcomes, deliverables and target
dates for an 18-month period.
• A new timeline has been agreed by the implementation
committee to take into account delayed funding consisting of
Phase 0 planning period (May – Sept. 2013) followed by 3 x six
monthly phases up to April 2015.
Roadmap
Costs !
• The roadmap follows up a business case submitted to the University
IT Committee in Summer 2012 by Jeff Haywood which estimated one-
off and recurrent costs.
• Last month the Vice Principal announced that funding would be in the
order of ÂŁ2 million split between infrastructure and RDM support
and technical personnel.
• Currently the Roadmap does not include itemised costs. Details are
currently being discussed by the Implementation Committee.
Data Management Support
General consultancy and support service throughout the research
process – addresses policy points 1, 2, 4
Example services might include:
• Tailored awareness and advocacy activities
• Online Data Management guidance
• Training (online / F-2-F)
• Data Management consultancy
Data Management Planning
Support and services for planning activities that are typically
performed before research data is collected or created – addresses
policy points 3, 4
Example services might include:
• Bespoke Data Management Planning (DMP) support
• Customised Data Management Planning tool
Active Data Infrastructure
Facilities to store data that is actively used in current research
activities, to provide access to that storage, and tools to assist in
working with the data – addresses policy points 5, 8
Example services might include:
• Accessible cross-platform Data Store
• File Access Services (e.g. Dropbox-like)
• Data Synchronisation (e.g. mobile devices)
• Web-based Collaboration tools
• Structured Data Version Control (WebDAV)
• Central Database service
Data Stewardship
Tools and services to aid in the description, deposit, and on-going
management of completed research data outputs – addresses policy
points 6, 7, 9, 10
Example services might include:
• Data archive service (vault)
• Data asset register
• Data repository (enhanced)
• PURE Current Research Information System integrated with
other systems
RDM Roadmap: http://tinyurl.com/bu2dllr
 Potential pitfalls a University could fall into:
 
To wrongly assume there can be a one size fits all requirements
checklist
 
• Requirements are too diverse and in detail are incompatible across
disciplines / sub-disciplines (size, volume, format, space, time)
To wrongly assume that all data is Edinburgh centric and needs to be
stored in a university repository
• For much large scale science this is inappropriate & impossible
 
To wrongly assume that all data is the same.
 
• Raw data – probably need to preserve – but maybe not open access
as it would be practically unusable - e.g. 100 Pbytes from SKA
telescope
• Processed data – probably more useful to make open access
• Awareness Raising in Colleges/Schools
• DataShare Pilots - 3 sets of “communities and collections” set up to
determine how the data repository meets the needs of Edinburgh
researchers
• MANTRA training module for early career Researchers
• RDM Training for Liaison Librarians
• Data Asset Register
• Overall Architecture & Workflow (storage, hardware, security…)
Summary of Current Activity
Email: stuart.macdonald@ed.ac.uk
Acknowledgements:
Dr. Cuna Ekmekcioglu (VP’s office)
Sarah Jones (DCC)
Stuart Lewis (Digital Library)
Kerry Miller (DCC)
Tony Weir (ITI)
Questions!

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RDM Roadmap@Edinburgh - an institutional approach

  • 1. RDM Roadmap@Edinburgh - an institutional approach Stuart Macdonald & Robin Rice EDINA & Data Library IASSIST, Cologne, 30 May 2013
  • 2. A JISC-funded pilot project produced 6 case studies from research units across the University in identifying research data assets and assessing their management, using DAF methodology developed by the Digital Curation Centre. Edinburgh Data Audit Framework (DAF) Implementation Project (May – Dec 2008) 4 main outcomes: • Develop online RDM guidance • Develop RDM training • Develop university research data management policy • Develop services & support for RDM (in partnership IS) Background
  • 3. • RDM policy* containing 10 aspirational statements affirming both the researchers’ and the University’s responsibilities, e.g. • PI responsible for RDM • University will provide RDM support and training • University will provide RDM services (such as back-up, storage, deposit) • Data retained elsewhere will be registered with the University • RDM plans must ensure that data are available for access and re- use under appropriate safeguards • In 2011, RCUK issued a set of Common Principles on Research Data Policy which push for data to be made openly available with as few restrictions as possible. Most funding bodies have issued data policies, however the extent and coverage of these varies greatly. Drivers * http://www.ed.ac.uk/schools-departments/information-services/about/policies-and-regulations/research-data-policy
  • 4. An RDM Policy Implementation Committee was set up by the Vice Principal Knowledge Management Prof. Jeff Haywood to implement recommendations: • Membership from across IS • Charged with delivering services that will meet RDM policy objectives • Iterate with researchers to ensure services meet the needs of researchers The Vice Principal also established a Steering Committee led by Prof. Peter Clarke comprising members of Research Committee from the 3 colleges, IS, DCC and Edinburgh Research and Innovation (ERI). Their role is to: • Provide oversight to the activity of the Implementation Committee • Ensure services meet researcher requirements without harming research competitiveness Committees
  • 5. • EPSRC expects funded projects to have developed a roadmap aligned with EPSRC’s RDM expectations by 1st May 2012, and to be fully compliant with these expectations by 1st May 2015. • The Executive Summary of the Information Services Plan, 2012- 13 states, “Research data management & storage – policies, training, curation, preservation, baseline 0.5Tb/user,” is a major IS-led project for the year. • The Edinburgh RDM roadmap was set out as a high level plan for its delivery, noting objectives, outcomes, deliverables and target dates for an 18-month period. • A new timeline has been agreed by the implementation committee to take into account delayed funding consisting of Phase 0 planning period (May – Sept. 2013) followed by 3 x six monthly phases up to April 2015. Roadmap
  • 6. Costs ! • The roadmap follows up a business case submitted to the University IT Committee in Summer 2012 by Jeff Haywood which estimated one- off and recurrent costs. • Last month the Vice Principal announced that funding would be in the order of ÂŁ2 million split between infrastructure and RDM support and technical personnel. • Currently the Roadmap does not include itemised costs. Details are currently being discussed by the Implementation Committee.
  • 7.
  • 8. Data Management Support General consultancy and support service throughout the research process – addresses policy points 1, 2, 4 Example services might include: • Tailored awareness and advocacy activities • Online Data Management guidance • Training (online / F-2-F) • Data Management consultancy
  • 9. Data Management Planning Support and services for planning activities that are typically performed before research data is collected or created – addresses policy points 3, 4 Example services might include: • Bespoke Data Management Planning (DMP) support • Customised Data Management Planning tool
  • 10. Active Data Infrastructure Facilities to store data that is actively used in current research activities, to provide access to that storage, and tools to assist in working with the data – addresses policy points 5, 8 Example services might include: • Accessible cross-platform Data Store • File Access Services (e.g. Dropbox-like) • Data Synchronisation (e.g. mobile devices) • Web-based Collaboration tools • Structured Data Version Control (WebDAV) • Central Database service
  • 11. Data Stewardship Tools and services to aid in the description, deposit, and on-going management of completed research data outputs – addresses policy points 6, 7, 9, 10 Example services might include: • Data archive service (vault) • Data asset register • Data repository (enhanced) • PURE Current Research Information System integrated with other systems
  • 13.  Potential pitfalls a University could fall into:   To wrongly assume there can be a one size fits all requirements checklist   • Requirements are too diverse and in detail are incompatible across disciplines / sub-disciplines (size, volume, format, space, time) To wrongly assume that all data is Edinburgh centric and needs to be stored in a university repository • For much large scale science this is inappropriate & impossible   To wrongly assume that all data is the same.   • Raw data – probably need to preserve – but maybe not open access as it would be practically unusable - e.g. 100 Pbytes from SKA telescope • Processed data – probably more useful to make open access
  • 14. • Awareness Raising in Colleges/Schools • DataShare Pilots - 3 sets of “communities and collections” set up to determine how the data repository meets the needs of Edinburgh researchers • MANTRA training module for early career Researchers • RDM Training for Liaison Librarians • Data Asset Register • Overall Architecture & Workflow (storage, hardware, security…) Summary of Current Activity
  • 15. Email: stuart.macdonald@ed.ac.uk Acknowledgements: Dr. Cuna Ekmekcioglu (VP’s office) Sarah Jones (DCC) Stuart Lewis (Digital Library) Kerry Miller (DCC) Tony Weir (ITI) Questions!

Hinweis der Redaktion

  1. Publicly funded research area public good produced in the public interest; data with long-term value should be preserved & accessible for re-use; metadata for searching and description/context; embargo for privileged use by researcher; data citation/attribution
  2. Funders have policies, responsibilities fall to theuniversity as well as the researcherResearchers are mobileInstitution and researcher must work together,define the responsibilitiesAwareness raising within university of practicalties