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Jisc research analytics service

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Jisc’s plans for a potential new research analytics service have started with a discovery phase to help define the problems around research analytics as the starting point to possible solutions. At the end of this phase there will be a brief defining the work required to produce a research analytics service. We have been working with a number of institutions and stakeholders to explore the problems faced by institutional leaders, managers, professionals and academic staff concerning the planning, management and evaluation of research, where better analytic insight would help address these problems. This presentation will highlight the progress made defining these problems, what we have learnt and plans for the next stage in the discovery process.

Jisc research analytics service

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Developing a research analytics service –
Discovery Phase
1 July 2019
Research Analytics Webinar
Rob Johnson (Research Consulting)
Research Analytics Service
Research Analytics Service2
Running a discovery phase to scope a research analytics service
• Jisc’s members are increasingly focused on the use of data to inform their planning, though mindful
of GDPR and competition law
• A Jisc research analytics service would build on existing work undertaken in the area of learning
analytics, and would extend the scope of the existing Jisc Analytics Labs and Heidi Plus Community
Dashboards initiative to meet urgent policy drivers such as the Industrial Strategy, REF and KEF.
• A research analytics service offer from Jisc is not limited in scope to data just from Jisc services and
might also be based on data from HEI services, and/or third party (sector and commercial
organisations, etc) sources as well.
3
ResearchAnalytics Sophistication Model
Maturity of Research Analytics Development
Researcher/Group/Organisational/SectorImpact
LimitedIntegrated
Immature Advanced
Aware
Experimentation
Organisational
transformation
Research group
Researcher
PGR student
Sector
transformation
Research
organisation
• Basic reports
• Log data
• Drill down reports
• Sample dashboards
• PGR dashboards
• Researcher
dashboards
• Business intelligence
reporting tools
• Cross-system data
integration
• Predictive models
• Measured by impact
and organisational
strategy
• Data sharing
capabilities
• Innovation
• Open data
• Sector-wide agility
Emerging
Research Analytics Service
Research Analytics Service4
Discovery Phase
• Problem Definition
• Broad context
• Stakeholders
• 5 HEI case studies
• Problem dossier
• Refine solutions
• Wireframe prototypes
• Initial thoughts on business model, vision, competitive landscape, alignment with political and
international landscape, and technical approach
• Solution pitch to Investment Committee
• Active engagement with UKRI, Research England, and the Forum for Responsible Research Metrics
Double Diamond model (Copyright Design Council 2014)
Assessing Research Analytics Capability – 5 case study HEIs
5
•Research analytics remains
immature in most HEIs.
•‘Research intelligence’ still
primarily qualitative in nature.
•Analytics expertise resides in
Planning & MI functions, and is
focussed on teaching & learning.
•Analytics maturity linked to size
and data availability, but also
internal leadership.
HighLowMedium
Immature Emerging Mature
Availabilityofdata
ResearchAnalytics Development
HEI A
HEI B
HEI C
HEI D
HEI E
Application of research analytics
6
Thematic analysis of c.160 user stories derived from case studies, workshops and
interviews
Infrastructure and
technical capability
Resourcing and
skills
Negligible number
of user stories
relating to research
integrity

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Jisc research analytics service

  • 1. Developing a research analytics service – Discovery Phase 1 July 2019 Research Analytics Webinar Rob Johnson (Research Consulting)
  • 2. Research Analytics Service Research Analytics Service2 Running a discovery phase to scope a research analytics service • Jisc’s members are increasingly focused on the use of data to inform their planning, though mindful of GDPR and competition law • A Jisc research analytics service would build on existing work undertaken in the area of learning analytics, and would extend the scope of the existing Jisc Analytics Labs and Heidi Plus Community Dashboards initiative to meet urgent policy drivers such as the Industrial Strategy, REF and KEF. • A research analytics service offer from Jisc is not limited in scope to data just from Jisc services and might also be based on data from HEI services, and/or third party (sector and commercial organisations, etc) sources as well.
  • 3. 3 ResearchAnalytics Sophistication Model Maturity of Research Analytics Development Researcher/Group/Organisational/SectorImpact LimitedIntegrated Immature Advanced Aware Experimentation Organisational transformation Research group Researcher PGR student Sector transformation Research organisation • Basic reports • Log data • Drill down reports • Sample dashboards • PGR dashboards • Researcher dashboards • Business intelligence reporting tools • Cross-system data integration • Predictive models • Measured by impact and organisational strategy • Data sharing capabilities • Innovation • Open data • Sector-wide agility Emerging
  • 4. Research Analytics Service Research Analytics Service4 Discovery Phase • Problem Definition • Broad context • Stakeholders • 5 HEI case studies • Problem dossier • Refine solutions • Wireframe prototypes • Initial thoughts on business model, vision, competitive landscape, alignment with political and international landscape, and technical approach • Solution pitch to Investment Committee • Active engagement with UKRI, Research England, and the Forum for Responsible Research Metrics Double Diamond model (Copyright Design Council 2014)
  • 5. Assessing Research Analytics Capability – 5 case study HEIs 5 •Research analytics remains immature in most HEIs. •‘Research intelligence’ still primarily qualitative in nature. •Analytics expertise resides in Planning & MI functions, and is focussed on teaching & learning. •Analytics maturity linked to size and data availability, but also internal leadership. HighLowMedium Immature Emerging Mature Availabilityofdata ResearchAnalytics Development HEI A HEI B HEI C HEI D HEI E
  • 6. Application of research analytics 6 Thematic analysis of c.160 user stories derived from case studies, workshops and interviews Infrastructure and technical capability Resourcing and skills Negligible number of user stories relating to research integrity
  • 7. Research analytics – Potential areas of focus Insert footer7 Numberofuserstories
  • 8. Provenance of data needed to address the user stories 8 0 5 10 15 20 25 30 35 40 Strategy and planning Researcher development and careers Financial performance and sustainability Collaboration, impact and knowledge exchange Understanding and evaluating research performance Compliance with legal, regulatory or funder requirements Scholarly communication Research integrity HEI data only HEI & external data External data only Numberofuserstories
  • 9. NEXT STEPS Insert footer9 •11 July - Interim findings presented to Forum for Responsible Research Metrics •Mid-July – internal progress review with Jisc •August – proceed to solution phase...? •Autumn – solution pitch to Jisc investment committee?
  • 10. christopher.brown@jisc.ac.uk jisc.ac.uk rob.johnson@research-consulting.com Rob Johnson Director Research Consulting) Tel: 07795 117747 Twitter: @rschrobUK Comments and feedback? www.research-consulting.com