Activity 2-unit 2-update 2024. English translation
Northumbria University case study
1. Northumbria University:
Towards a robust RDM solution
Dr David Young
Research Funding and Policy Manager, Research and Innovation Services, Northumbria University
2. Context: Research at Northumbria
Metric Value
Research Grants and Contracts Income (2015/16) £6M
Active research projects (2017) 473
Total outputs in repository (2017) 22,438
Students (2015/16) 32,000
Academic staff FTE (2017) 1,200
Ranking in REF2014 “research power” tables 50th
REF2014 GPA 2.71
Research information systems PURE, Agresso, Eprints, SAP, SITS
3. Timeline I: RDM at Northumbria
…But no supporting infrastructure in place, and then no IT representative! (Summer 2015)
RDM policy and guidance approved by RIC (April 2015)
In-depth interviews with EPSRC award holders (Spring 2015)
Initial survey of research data management practice (Early 2015)
RDM Working Group reporting to Research and Innovation Committee (Late 2014)
4. Interaction with DCC
• Jan 2016 – Workshop on RDM policy development and
implementation
Services that are being implemented across UK HEIs
based on results of 2015 DCC survey which collected
responses from 60 institutions
Results of group exercise which indicates RIS, Library
and IT Services seen as natural leads in delivering
majority of RDM services
5. RISE Workshop I
• May 2016 – RISE Workshop with RDM WG focusing specifically on
options appraisal for data repository
Level One Level Two Level Three
Service primarily supports data deposit to
third-party repositories, and holds datasets
in-house when legal /regulatory compliance
requires this
Service defines criteria for in-house
retention of datasets of long-term value to
the institution
Service defines criteria for developing datasets
as special collections and ensures these meet
specialist depositor and user needs
Level One Level Two Level Three
Service supports minimum external
requirements for metadata and publicly
accessible data
Service supports community best practice
standards for data access, citation and
metadata exchange
Service supports bespoke content
discoverability, access and quality review
needs for user groups or organisations
6. RISE Workshop II
Area of Data Management Capability E-Prints
ReCollect
Figshare for
Institutions
PURE
Ingest 2 2 1.5
Data access, publishing and discovery 2 2 1.5
Preservation 2.5 2 1.5
Management and reporting 2 2.5 2.5
Integration 3 2.5 2
7. How has the RISE model helped us?
• Enabled us to have a clear view of our current capabilities and
shortcomings around RDM support infrastructure
• Provided a benchmark for senior managers
• Formed part of evidence base for position paper on RDM
• Helped secure budget allocation for RDM support system and staffing
• Bridged the communication gap between research support services
(RIS, Library) and other critical central services (IT, procurement)
• Key input to formal University options appraisal and business
requirements paper
8. Timeline II: RDM at Northumbria post-RISE
Aim to pilot system and then roll out (from Jan 2018)
Aim to go to procurement (Sept 2017)
Business requirements and options appraisal (May-June 2017)
Budget allocation for RDM system and staffing (Mar 2017)
Further survey of likely heavy data users (Jan 2017)
IT Services representation on RDM Working Group (late 2016)
Sources for data:
RGCI and student numbers: https://www.northumbria.ac.uk/static/5007/finpdf/finstat1516
Active research projects: internal G&C database
Academic staff FTE: internal HR database
Repository data: http://nrl.northumbria.ac.uk/view/divisions/
REF2014 ranking/GPA: https://www.timeshighereducation.com/sites/default/files/Attachments/2014/12/17/k/a/s/over-14-01.pdf
RDM working group chaired by PVC Research, with academic representation from all faculties, and Library, Research & Innovation Services, IT, VCO/Legal, established to formulate an RDM policy for the University and support development of RDM good practice and technical infrastructure
Research data management practice survey (Spring 2015): responses from 11/22 departments, showed a wide range of practices in relation to management of data during and post-project, including storage on memory sticks, personal hard drives, laptops, varied backup practice, low awareness of need for long term preservation
In-depth EPSRC award holder interviews revealed similar lack of awareness of EPSRC’s requirements around RDM
Policy and guidance: https://www.northumbria.ac.uk/research/research-data-management/
No RDM infrastructure: awareness of what was required, but no data repository, no staffing to support staff development
IT representative left the group and was difficult to replace
Initial workshop with Joy Davidson and Angus Whyte (DCC) indicated aspects of good practice across areas of: policy and strategy (RDM part of good practice rather than just about funder mandates), data management planning, managing active data, but that longer term business planning, long term preservation and storage were areas of weakness.
Also initial scoping of responsibility for RDM showed most people in working group felt RIS, Library and IT were natural leaders for this
The first part of the RISE workshop involved a self assessment on the University’s current level of capability to support RDM against the level we would like to achieve. In total we measured current performance and target according to RDM policy on 8 criteria:
Data collection
Security, legal and ethical risk assessment
Preservation, planning and action
Continuity support
Monitoring locally produced datasets
Data publishing mandate
Level of data curation
Metadata collection policy
On most of these criteria we assessed current performance as being at level 1, with the aim of reaching level 2 by the end of the RDM WG lifecycle. The examples given on this slide relate to data collection policy – where the aim is to move from existing practice of deposit on third party datasets towards in-house retention – and data publishing – where the ambition is to move from minimum support to best practice standards for data access, citation and metadata exchange
The next part of the workshop defined a platform longlist and shortlist. The shortlist was assessed by DCC against the ReCap model (an extension of RISE) and forms an initial options appraisal to be used to inform further work by the University.
Each of the broad areas listed above was broken down into specific criteria in the full report. The table above shows the (rounded) average score for each system in each area of data management capability (each area had a number of criteria which were rated between 1 and 3.
The only system which didn’t meet Northumbria requirements in some areas – in the opinion of the report author – was PURE.
This was supplemented by a narrative report discussing the pros and cons of each longlisted system, including the three in the shortlist above.