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From policy to strategy Peter Dukes Policy Lead – Data Sharing & Preservation

From policy to strategy Peter Dukes Policy Lead – Data Sharing & Preservation ESDS - Sharing Research Data: Pioneers, Policies and Protocols 13th March 2009. “Sharing” is a good thing Data diversity Other challenges MRC Data Support Service project.

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From policy to strategy Peter Dukes Policy Lead – Data Sharing & Preservation

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  1. From policy to strategy Peter Dukes Policy Lead – Data Sharing & Preservation ESDS - Sharing Research Data: Pioneers, Policies and Protocols 13th March 2009

  2. “Sharing” is a good thing • Data diversity • Other challenges • MRC Data Support Service project

  3. Internationally : Data sharing is a good thing OECD policy study • “Publicly-funded research data are a public good produced in the public interest”

  4. Nationally: Data sharing is a good thing • 7 UK Research Councils • Common datasharing policy • Wellcome Trust • Archives & repositories • ESRC: Archive and Data service • NERC & STFC: Data Centres • Informatics • Databases & tools • Research • E-science Infrastructure • Software tools • Grids

  5. “Sharing” can mean… • Comparative analyses between independent data sets • Replication of findings from one dataset in another • Pooling of like data from different studies • E.g. Individual patient data meta analysis – randomised clinical trials • Gain in statistical power  definitive answers • Linkage of different kinds of data that relate to a common set of individuals • Interactions between causative factors • Re-analysis • Validation, audit • Methodology development • Testing of new hypotheses

  6. Data sharing: Realizing the value of our data for new knowledge and better health Cohorts & Trials Patient groups “Omics” NHS Clinical Data Bio Banks Demographic data Educational Environmental & Social Data Leadership, partnership, investment Investment in methodology, strategic skills & infrastructure Connecting for new knowledge  better health

  7. Strategies for promoting sharing Skills Population health science E-health records research Asking the Q Outcomes of interventions Fund excellent research Determinants of healthy ageing Study design Analysis NHS Research Capability Programme Innovate methods & develop capacity Cross cohort e.g. HALCyon Methods development ITC & data infrastructure Diverse, routine patient data Support & value great data management Rich, diverse, high quality Data capture Patients Nurture research participants Research cohorts Communication

  8. MRC policy • Data sharing is the norm – in the public interest • Researchers should submit DSP plans as part of grant proposals • The plans will be assessed as part of peer review • Access rules should be clear • Transparent governance • MRC does not prescribe the period for PI’s exclusive use • Recognition that creators add value • MRC will fund preservation & sharing

  9. MRC is a diverse & devolved organisation • Hitherto • Hardly ever… • Never!

  10. “Sharing” is a good thing • Data diversity • Other challenges • MRC Data Support Service project

  11. Data-resources are diverse Databases, archives, biobanks… • Community resources • Set up & funded to ingests & share data • Data user-led oversight • Funded as a resource & service • Performance: data service quality Clinical & population studies… • Science-focused • Set up by Principal Investigators • Nurtures the cohort • Collects, cleans & analyses data • Funded as research grants • Performance: science outputs

  12. Some data-resources are not set up for research Routine data of value for policy & research • Data not collected for research • NHS clinical & management data • Social services data… • Education… • Data to support service improvement and policy

  13. Data Preservation: Sustaining the value of our data for new knowledge and better health • Real issue of non-digital data • Fragility and corruptibility of paper, fiche & digital media • Real issues with digital data • Hardware, software and formats become obsolete • Without metadata, the research data have little or no value • Selectivity • Cost, value and ethics

  14. “Sharing” is a good thing • Data diversity • Other challenges • MRC Data Support Service project

  15. “Sharing” is a good thing • Data diversity • Why doesn’t MRC just get on with it! • MRC Data Support Service project

  16. “Sharing” is a good thing • Data diversity • ESRC, NERC… have been doing it for decades! • MRC Data Support Service project

  17. MRC Council says Data sharing is the norm – in the public interest Researchers should submit DSP plans as part of grant proposals The plans will be assessed as part of peer review Access rules should be clear Transparent governance MRC does not prescribe the period for PI’s exclusive use MRC will fund preservation & sharing What MRC Council says… Hierarchy MRC Council & Executive Funding Boards Unit Directors Study PIs Data scientists & Managers

  18. Science leaders say The benefits include Validation of research findings Testing of new & alternative hypotheses Validation of new methods Creation of new data sets Mining new “seams” in large data sets Systematic analysis of trials data Data linkage “Encourages diversity of analysis and opinion” Challenge previous findings What science leaders say… MRC Council & Executive Funding Boards Unit Directors Study PIs Data scientists & Managers

  19. National Survey of Health & Development HALCyon Focused on healthy ageing Physical & cognitive capability Psychological & social well-being Biology of ageing 23 scientists in nine UK cohorts Methodology Knowledge transfer Collaborative science Inter-relationships between indicators Changes in indicators with age Common lifetime determinants Data Access Project What PIs are actually doing now… Unit Directors Professor Di Kuh

  20. But some study PIs say… “The idea is OK, but for many investigators restricted access to their data set is their intellectual capital” “Not everyone can be a scavenger feeding off the work of others” “You can’t just put it all up there on the web!” “Data protection regulation places scientists at risk” Some scientists have concerns… MRC Council & Executive Funding Boards Unit Directors Study PIs Data scientists & Managers

  21. Concerns PIs have identified… Risk to competitive advantage Intellectual property Lack of recognition Reputational risks to the study to their science Risk of participant withdrawal Loss of statistical power We need to address risks… MRC Council & Executive Funding Boards Unit Directors Study PIs Data scientists & Managers

  22. Hierarchy Benefitsof an Infrastructure for Sharing Preventing loss of knowledge Preserving the value of historic investment New opportunities for collaboration Discovery Open up legacy assets Networking & spread of good practice What Data Managers say (2008) MRC Council Funding Boards Unit Directors Study PIs Data scientists & Managers

  23. Hierarchy Benefitsof an Infrastructure for Sharing Technical enhancements Automation – reduced burden Up to date guidance “No need to ‘roll your own’” More effective induction & training Greater cost effectiveness across MRC Confident partnerships – NHS, other RCs But we need resources and support from the top What Data Managers say (2008) MRC Council Funding Boards Unit Directors Study PIs Data scientists & Managers

  24. What and say Patients & Public Media Public survey shows • The public has concerns about (mis-)handling of personal information • Most people do not distinguish between health records and research records • Some people object to their anonymised health data being shared But also • “Won’t someone please use my health records to help someone else suffer less!” • Acceptance is high following patient / public engagement in a specific research study

  25. Some barriers to policy implementation • Little evidence of realbenefits and costs • Uncertainty about researchers real needs and solutions • Complex regulatory environment • Complexity: everything is connected to everything else MRC Data Support Service to address barriers

  26. “Sharing” is a good thing • Data diversity • Challenges • MRC Data Support Service project

  27. March 2009: DSS Project “soft launch” Consortium Science and Technology Facilities Council (STFC) University College London (UCL) University of Oxford Working with MRC community 6 pioneer Units / Programmes 2006: MRC Council approval in principle for a Data Support Service The Data Support Service Project

  28. A web-based directory of 100+ population studies With evidence of use & value Accessible guidance, targeted to real needs With evidence of use & value Study-specificstrategies forpreservation & sharing With evidence of benefits & costs Evidence of cultural & practice changes Unaware  aware  informed  advocate Community engagement in standards development Experience informing an evolving DSP strategy In two years, we expect to see…

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