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The HE data and information landscape –
making it happen (painlessly ?!?)
Andy Youell
Director of Standards and Development
ARC 2012-11-12
Agenda

•   Background
•   Issues for RPG and the data processors
•   Issues for institutions
•   The end bit…
Agenda

•   Background
•   Issues for RPG and the data processors
•   Issues for institutions
•   The end bit…
RPG - Project B

• White paper: A new system that:
   – Meets the needs of a wider group of users
   – Reduces duplication
   – Results in timelier and more relevant data
• Feasibility and impact analysis - Roadmap for future
  development
• Reported to RPG June 2012
• Recommendations were accepted
Agenda

•   Background
•   Issues for RPG and the data processors
•   Issues for institutions
•   The end bit…
HEBRG survey of data collection
Issues – data collectors/processors

• Very broad range of organisations, collecting and
  processing data for many different purposes
• Low awareness of what each other is collecting
• Inconsistent definitions and terminology
• Patchy approach to data standards adoption
• No holistic view of the system
• No mechanism or forum to bring these bodies
  together
Recommendations to RPG

• Governance for data and information exchange
  across the sector

• Development of a common data language
   – Data model, lexicon, thesaurus
• Inventory of data collections
• Specific data standards work
   – JACS
   – Unique Learner Number
1. Governance framework

• Co-regulation - sector-level data processors and HE
  providers
• Collaboration: standardisation and sharing
• Challenge process (and visibility)
• Scope
   – UK dimension
   – Non-HE bodies
• How to achieve (and maintain) buy-in from
  stakeholders?
2. Data model, lexicon and thesaurus

• Review of existing collections/definitions – the as is
• Better understanding of differences/similarities
   – In definitions
   – In terminology
• Coming from both angles:
   – What are collectors asking for?
   – What are institutions supplying?
• To inform future standardisation and data sharing
  discussion
• Deliverables:
   – Data model, lexicon and thesaurus
   – Maintenance plan
3. Inventory of data collections

•   HEBRG survey identified 550 lines of reporting
•   Very little detail (width)
•   Is it complete? (length)
•   We need a solid understanding of the current burden
    – To help HEIs become more joined up in their reporting
    – To challenge data collectors to reduce duplication
• Deliverables:
    – Database of collections
    – Maintenance plan
4a JACS development

• Problems:
   – JACS could have far broader use
   – Current structure has run out of space
• Analysis of requirements
• Exploration of coding options
• Deliverable:
   – Road map for future development
4b ULN implementation

• ULN widely accepted as a Good Thing
   – Reducing burden by replacing existing IDs
   – Adding value and reducing burden through better data
     linking/sharing
• What are the real barriers to adoption?
• What would it take to resolve these issues?
• Deliverable
   – An assessment of where we currently are with ULN
   – Commitment to a roadmap?
Agenda

•   Background
•   Issues for RPG and the data processors
•   Issues for institutions
•   The end bit…
Findings – HE providers

• Few HE providers have a complete picture of their
  data reporting requirements
• Uncoordinated responses to (uncoordinated)
  requests for data
• Some weaknesses in data management/governance

  Diamond: Process improvement, simplification and
standardisation is key to unlocking the value of shared
                        services
Agenda

•   Background
•   Issues for RPG and the data processors
•   Issues for institutions
•   The end bit…
Painless….?

• If this was easy, it would have happened a long time
  ago
• Not a “clean-sheet” exercise
• Seize the moment:
   – Technologies and standards
   – Change
   – Political will and profile
Any questions?
Discussion

• How, if at all, could an information governance
  process work at a sector level?
   – Scope
   – Function
   – Power/authority
• What are the barriers to improving quality and
  efficiency in HEI data
   – Does it matter that concepts, processes and lexicon differ
     within, and between, institutions?
   – Conflict between standardisation and autonomy?
The HE data and information landscape –
making it happen (painlessly ?!?)
Andy Youell
Director of Standards and Development
ARC 2012-11-12

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“The HE Landscape – Making It Happen (Painlessly)” - Andy Youell, Director of Standards & Development HESA

  • 1. The HE data and information landscape – making it happen (painlessly ?!?) Andy Youell Director of Standards and Development ARC 2012-11-12
  • 2. Agenda • Background • Issues for RPG and the data processors • Issues for institutions • The end bit…
  • 3. Agenda • Background • Issues for RPG and the data processors • Issues for institutions • The end bit…
  • 4. RPG - Project B • White paper: A new system that: – Meets the needs of a wider group of users – Reduces duplication – Results in timelier and more relevant data • Feasibility and impact analysis - Roadmap for future development • Reported to RPG June 2012 • Recommendations were accepted
  • 5.
  • 6. Agenda • Background • Issues for RPG and the data processors • Issues for institutions • The end bit…
  • 7. HEBRG survey of data collection
  • 8. Issues – data collectors/processors • Very broad range of organisations, collecting and processing data for many different purposes • Low awareness of what each other is collecting • Inconsistent definitions and terminology • Patchy approach to data standards adoption • No holistic view of the system • No mechanism or forum to bring these bodies together
  • 9. Recommendations to RPG • Governance for data and information exchange across the sector • Development of a common data language – Data model, lexicon, thesaurus • Inventory of data collections • Specific data standards work – JACS – Unique Learner Number
  • 10. 1. Governance framework • Co-regulation - sector-level data processors and HE providers • Collaboration: standardisation and sharing • Challenge process (and visibility) • Scope – UK dimension – Non-HE bodies • How to achieve (and maintain) buy-in from stakeholders?
  • 11. 2. Data model, lexicon and thesaurus • Review of existing collections/definitions – the as is • Better understanding of differences/similarities – In definitions – In terminology • Coming from both angles: – What are collectors asking for? – What are institutions supplying? • To inform future standardisation and data sharing discussion • Deliverables: – Data model, lexicon and thesaurus – Maintenance plan
  • 12. 3. Inventory of data collections • HEBRG survey identified 550 lines of reporting • Very little detail (width) • Is it complete? (length) • We need a solid understanding of the current burden – To help HEIs become more joined up in their reporting – To challenge data collectors to reduce duplication • Deliverables: – Database of collections – Maintenance plan
  • 13. 4a JACS development • Problems: – JACS could have far broader use – Current structure has run out of space • Analysis of requirements • Exploration of coding options • Deliverable: – Road map for future development
  • 14. 4b ULN implementation • ULN widely accepted as a Good Thing – Reducing burden by replacing existing IDs – Adding value and reducing burden through better data linking/sharing • What are the real barriers to adoption? • What would it take to resolve these issues? • Deliverable – An assessment of where we currently are with ULN – Commitment to a roadmap?
  • 15. Agenda • Background • Issues for RPG and the data processors • Issues for institutions • The end bit…
  • 16.
  • 17. Findings – HE providers • Few HE providers have a complete picture of their data reporting requirements • Uncoordinated responses to (uncoordinated) requests for data • Some weaknesses in data management/governance Diamond: Process improvement, simplification and standardisation is key to unlocking the value of shared services
  • 18. Agenda • Background • Issues for RPG and the data processors • Issues for institutions • The end bit…
  • 19. Painless….? • If this was easy, it would have happened a long time ago • Not a “clean-sheet” exercise • Seize the moment: – Technologies and standards – Change – Political will and profile
  • 21. Discussion • How, if at all, could an information governance process work at a sector level? – Scope – Function – Power/authority • What are the barriers to improving quality and efficiency in HEI data – Does it matter that concepts, processes and lexicon differ within, and between, institutions? – Conflict between standardisation and autonomy?
  • 22. The HE data and information landscape – making it happen (painlessly ?!?) Andy Youell Director of Standards and Development ARC 2012-11-12

Editor's Notes

  1. Survey run for HEBRG by HESA, AHUA and UCISAFirst time such a comprehensive survey undertakenInstitutions asked to list all/any data supply48 responses550 lines of reporting identifiedRange of responses across institutions suggests no one institution has a complete picture – issue of data supply from centre vs data supply from departments