1. Key Challenges Strategic Advisor For Data Resources
Professor Vernon Gayle
University of Stirling
MRC, London
12th February 2010

2. Structure of 10 minute presentation
Current position of the UK data infrastructure
Overall data strategy objectives
Changes in the economic & political climate
Five key challenges
1. Balance between stability and innovation
2. Identifying portfolio gaps and overlaps
3. Appropriately engaging with new data sources (examples)
4. Advances in information technology
5. Research capacity building

3. The Current Position UK is well resourced with social science data
Strong social science infrastructure
Two decades of increasing global connectivity
Improved data archiving, curation and access
Thousands of electronic files
Multipurpose (omnibus) data resources
Strength in household panel data
Strength in birth cohort data

4. The Current Position The National Data Strategy
Successful in their aims
to provide a coherent framework for the development and maintenance of a robust data infrastructure
ensuring that relevant and timely data are available to inform and address future research priorities
emphasise the importance of creating better resources for the study of complex research questions

5. Overarching Data Strategy Objectives
Maintain (and extend) UK position in the global knowledge economy
Contributing the UK economic competitiveness
Supporting the highest quality social science
Supporting high-quality research informing public sector, third sector, government and business
Data must reflect the complexities of contemporary social and economic life
Ensuring data investments provide their fullest analytical returns

6. Changes in the Climate Moving into uncharted territory…
The UK economy & pressure of public finance
High levels of expenditure on data collection?
Political change
Potential change in political leadership
Reorganisation of government departments
Regional variations in government

7. Key Challenges Striking the (delicate) balance
Sustainable resources versus innovations
Stability (esp. longitudinal data resources)
Comparability (esp. cross-national data)
Flexibility (reacting to emerging issues)
Emphasis on multipurpose data resources but also remembering the role of adhoc data

8. 2. Identifying portfolio gaps and overlaps - example of ageing in Scotland - overlapping MCS & GUS data - developing resources in an international context - collaborating with data stakeholders

9. 3. Appropriately engaging with new data sources - “Richer data resources” * e.g. inclusion of health/medical data - Data Linking (esp. administrative data) - Qualitative data resources (inc. visual, audio) - Geo-spatial data - Non standard forms of data * Biometric data (physical samples) * Transactional data * Tracking and sensoring

10. 3. Appropriately engaging with new data sources - “Richer data resources” - Identifying new forms of funding * Cross-council funding (especially in the area of health) * European and international sources

11. Understanding Society (UKHLS)
Examples of maximising the analytical potential of new data on the horizon
Understanding Society (UKHLS)
[Innovation panel]
Sample size
Ethnic boost
Data linking (e.g. qualifications)
Biometric data
2012 Birth Cohort (Olympic)
Advances in relation to earlier cohorts & US

12. Examples of maximising the analytical potential of new data on the horizon
CENSUS 2011
Key statistics etc.
Special products (inc. neighbourhood, small areas)
Samples of Anonymised Records
ONS-LS; Scottish Longitudinal Study; N.I.
British Longitudinal Study?

13. 4. Advances in information technology - “The ever changing climate”
- Implications for data collection
- Data access (maximising)
- Data security (appropriately managing risks)
- Ethical issues (e.g. data linking)
5. Capacity Building in data analysis
- The next generation(s) of researchers
- Capitalising upon and extending ESRC investments
- Promoting awareness of resources