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Big Data as a Catalyst for Collaboration & Innovation
Big data is disrupting biomedical research through digitization of data sources. The National Institutes of Health (NIH) launched the Big Data to Knowledge (BD2K) initiative to support this disruption. BD2K funds various programs including data sharing policies, data science training, and the development of shared infrastructure and standards. This infrastructure includes the "Commons" which would provide discoverable, accessible, interoperable and reusable research objects to catalyze collaboration using open APIs and computing platforms. SRP could interact with BD2K through initiatives like open science competitions, data standards development, and leadership in trans-NIH big data efforts.
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Big Data as a Catalyst for Collaboration & Innovation
- 1. Big Data asa Catalyst for Collaboration & Innovation Philip E. Bourne Ph.D., FACMI Associate Director for Data Science National Institutes of Health philip.bourne@nih.gov SRP Annual Meeting Puerto Rico, November 18, 2015
- 2. Thesis… We are enteringa period of disruption in biomedical research and we should all be thinking about what this means http://i1.wp.com/chisconsult.com/wp- content/uploads/2013/05/disruption-is-a- process.jpg http://cdn2.hubspot.net/hubfs/418817/disruption1.jpg
- 3. Evidence of Disruption… Evidence: – Google car – 3D printers – Waze – Robotics – Sensors From: The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies by Erik Brynjolfsson & Andrew McAfee
- 4. Disruption: Example -Photography Digitization Deception Disruption Demonetization Dematerialization Democratization Time Volume,Velocity,Variety Digital camera invented by Kodak but shelved Megapixels & quality improve slowly; Kodak slow to react Film market collapses; Kodak goes bankrupt Phones replace cameras Instagram, Flickr become the value proposition Digital media becomes bona fide form of communication
- 5. Disruption: Biomedical Research Digitizationof Basic & Clinical Research & EHR’s Deception We Are Here Disruption Demonetization Dematerialization Democratization Open science Patient centered health care
- 6. Disruptive Features: Sustainability SourceMichael Bell http://homepages.cs.ncl.ac.uk/m.j.bell1/blog/?p=830
- 7. Disruptive Features: Reproducibility Changing Valueof Scholarship (?)
- 8. “And that’s whywe’re here today. Because something called precision medicine … gives us one of the greatest opportunities for new medical breakthroughs that we have ever seen.” President Barack Obama January 30, 2015 Disruptive Features – New Science
- 9. Precision Medicine Initiative National Research Cohort – >1 million U.S. volunteers – Numerous existing cohorts (many funded by NIH) – New volunteers Participants will be centrally involved in design and implementation of the cohort They will be able to share genomic data, lifestyle information, biological samples – all linked to their electronic health records
- 10. Big Data inBiomedicine… This speaks to something more fundamental that more data … It speaks to new methodologies, new skills, new emphasis, new cultures, new modes of discovery …
- 11. Open Educational Resources Software Discovery and Sustainability Community Based Standards Clinical Data Challenges Database Sustainability Aboutthe BD2K Program • Initial FY 2014 funding of $32M. • Proposed investment of $656M through 2020. • Funded by ALL NIH Institutes and Centers. Software and Tool Development Centers of Excellence for Big Data Computing Data Discovery Index Coordination Consortium Scientist Training Awards Data Science Courses Data Sharing
- 12. BD2K FY14 Awards supportedby all NIH Institutes
- 13. Big Data:MRI images & GWAS data from over 30,000 people. Collaboration: Data came from 190 worldwide sites across 33 countries. Methods: To homogenize data from different sites, the group designed standardized protocols for image analysis, quality assessment, genetic imputation, and association. Found five novel genetic variants influencing volume of brain regions. Results provided insight into the variability of brain development, and may be applied to mechanisms of neuropsychiatric dysfunction. (Nature, 2015)
- 14. Detect Predict Adapt MD2KApplications – CHF and Smoking
- 15. Elements of TheDigital Enterprise Community Policy Infrastructure • Sustainability • Collaboration • Training
- 16. Elements of TheDigital Enterprise Community Policy Infrastructure • Sustainability • Collaboration • Training
- 17. A Culture ofSharing 1999 20042003 2007 20142008 Research Tools Policy NIH Data Sharing Policy Model Organism Policy Genome-wide Association (GWAS) Policy 2012 NIH Public Access Policy (Publications) Big Data to Knowledge (BD2K) Initiative Genomic Data Sharing (GDS) Policy Modernization of NIH Clinical Trials White House Initiative (2013 “Holdren Memo”)
- 18. Policies – Now& Forthcoming Data Sharing – Goal: legitimize data as a form of scholarship – Now: Genomic data sharing announced – Coming: Data sharing plans on all research awards – Data sharing plan enforcement • Machine readable plan • Repository requirements to include grant numbers – Data citation http://www.nih.gov/news/health/aug2014/od-27.htm
- 19. Elements of TheDigital Enterprise Community Policy Infrastructure • Sustainability • Collaboration • Training
- 20. Elements of TheDigital Enterprise Community Policy Infrastructure • Sustainability • Collaboration • Training
- 21. The Commonsis a shared virtual space which is FAIR: – Find – Access (use effectively) – Interoperate – Reuse An environment to find and catalyze the use of shared digital research objects The Commons Concept
- 22. The Developer orUser Defines the Environment from the Appropriate Building Blocks
- 23. Infrastructure - TheCommons: Conceptual Framework Research Objects (with UIDs) Discoverability (Search & Find) TheCommons Open APIs Data and tools Computing Platform(s) Containers Packaging software
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- 25. Commons - Pilots The Cloud Credits - business model BD2K Centers MODs (Model Organism Databases) HMP Data and tools available in the cloud NCI Cloud Pilots & Genomic Data Commons
- 26. Elements of TheDigital Enterprise Community Policy Infrastructure • Sustainability • Collaboration • Training
- 27. SRP & BD2K PossibleInteractions? (1/3) Innovation – Join IDEAS Labs – Propose new EHS programs Collaboration – Participation in standards efforts • EHS vocabulary • CDE harmonization • BD2K standards coordination center Training – BD2K training coordination center
- 28. SRP & BD2K PossibleInteractions? (2/3) Open Science - FAIR – Participate in the Open Science Competitions – With EPA challenge to produce device to measure atmospheric pollutants and biologic response (2013). • Toxicogenomics challenge with NTP/NIEHS, UNC, and Sage/DREAM to predict response to a given chemical based upon individual genetic susceptibility (2014). • With HHS to generate visualization tool to demonstrate impact of climate change on health risk (2016). – CHEAR data science center.
- 29. SRP & BD2K PossibleInteractions? (3/3) Leadership and coordination – Trans-NIH, BD2K – Interagency Big Data Senior Steering Group – Sustainability Working Group – Research Data Alliance Interest Group, Toxicogenomics Databases Interoperability
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- 31. NIH… Turning Discovery IntoHealth philip.bourne@nih.gov https://datascience.nih.gov/ http://www.ncbi.nlm.nih.gov/research/staff/bourne/