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Introduction to Big Data and its Potential for Dementia Research

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Presentation at Dementia Conference (Evington Initiative) held at Wellcome Trust, 22-23 October 2012. Acknowledgements to McKinsey & Company, also Tim Clark (MGH) and Iain Buchan (University of Manchester), for input to slides.

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Introduction to Big Data and its Potential for Dementia Research

  1. 1. Introduction to Big Data and itsPotential for Dementia ResearchDavid De Roure
  2. 2. Overview• What do we mean by Big Data?• Role in medical research• Impact on future research• Application to dementia research• Challenges and issues
  3. 3. ...the imminent flood of scientific data expected from the next generation of experiments, simulations, sensors and satellites Source: CERN, CERN-EX-0712023, http://cdsweb.cern.ch/record/1203203
  4. 4. http://www.slideshare.net/RockHealth/rock-report-big-data
  5. 5. Linked Data Investment is worthwhile when the data is: • Discoverable1. Use URIs as names for things • Reusable2. Use HTTP URIs so that • Linkable people can look up those names3. When someone looks up a URI, provide useful information, using the standards4. Include links to other URIs so that they can discover more things
  6. 6. http://www.ajtmh.org/content/86/1/39.full
  7. 7. http://stanmed.stanford.edu/2012summer/
  8. 8. http://www.slideshare.net/RockHealth/rock-report-big-data
  9. 9. BioEssays,, 26(1):99–105, January 2004 http://research.microsoft.com/en-us/collaboration/fourthparadigm/
  10. 10. A Big Picture e-infrastructureMore machines Big Data The Future! Big Compute Conventional Social online Computation Networking R&D More people
  11. 11. method data
  12. 12. Some Social Machines Nigel Shadbolt
  13. 13. Notifications of new data and results, automatic re-runs of analysis pipelines New research? Autonomic Curation Self-repair • Automation assists the scientist • Use the computational capability • Scale the capability to the problem, not the problem to the desktopMachines are users too
  14. 14. Massachusetts General Hospital (MGH) will receive $5.4million from the nonprofit Cure Alzheimer’s Fund, in what thefund said was the largest single private scientific grant everinvested in Alzheimer’s whole-genome sequencing focusedon families with the disease.Over the next 12 to 18 months, the Alzheimer’s GenomeProject will obtain complete genomic sequences of more than1,500 patients in families that have Alzheimer’s, and willinclude over 100 brain samples. The genomes of familymembers with Alzheimer’s will be compared to thosemembers who have been spared the disease to identify sitesin the genome that influence risk for Alzheimer’s. Tim Clarkhttp://www.genengnews.com/gen-news-highlights/mgh-wins-5-4m-grant-toward-sequencing-for-alzheimer-s-risk/81247502/
  15. 15. Significant added value throughappropriate additional data collection
  16. 16. Big Data methodologywww.methodbox.org
  17. 17. Troublesome Threes• 3 Ingredients – Data; Models; Expertise Challenge conventional assumptions• 3 Myths – Big data warehouses are the solution – Science provides the models to utilise the data – Clinicians will continue to be the main source of data• 3 Pipelines – R&D; Quality Improvement; Payor & Public Health Iain Buchan
  18. 18. Big Data in Context orDatasets(+ models) Data Models Expertise(searched by experts) “sense-making network” Iain Buchan
  19. 19. Closing thoughts1. Big Data is not just a quantitative change, it’s a methodological change – using digital methods • Use what we already have (in silos)2. Tremendous opportunity to collect additional data with significant impact on dementia research • Surveys and social machines • Data from instrumenting care process today3. Think sociotechnical – community matters • Method sharing, and usage adds value • Machines are users too – assistance vs automation
  20. 20. david.deroure@oerc.ox.ac.ukwww.oerc.ox.ac.uk/people/dderwww.scilogs.com/eresearch@dderPersonal slide credits: Nigel Shadbolt, Tim Clark, Iain Buchan

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