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Making Biomedical Research More Like Airbnb

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The notion of biomedical research as a platform. Presented at the International Data Forum, September 14, 2016, Denver CO.

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Making Biomedical Research More Like Airbnb

  1. 1. Making Biomedical Research More Like Airbnb Philip E. Bourne, PhD, FACMI Associate Director for Data Science The National Institutes of Health http://www.slideshare.net/pebourne philip.bourne@nh.gov
  2. 2. I am not crazy, hear me out • Airbnb is a platform that supports a trusted relationship between consumer (renter) and supplier (host) • The platform focuses on maximizing the exchange of services between supplier and consumer and maximizing the amount of trust associated with a given stakeholder • It seems to be working: • 60 million users searching 2 million listings in 192 countries • Average of 500,000 stays per night. • Evaluation of US $25bn
  3. 3. Is not biomedical research the same?
  4. 4. Why a comparison to Airbnb is not fair • Airbnb was born digital • The exchange of services on Airbnb are simple compared to what is required of a platform to support biomedical research Nevertheless there is much to be learnt
  5. 5. Is not biomedical research the same?
  6. 6. Author Submission via the Web Depositor Submission via the Web Syntax Checking Syntax Checking Review by Scientists & Editors Review by Annotators Corrections by Author Corrections by Depositor Publish – Web Accessible Release – Web Accessible Similar Processes Lead to Similar Resources Bourne, PLoS Comp. Biol. 2005 1(3) e34de Waard Nature Proceedings 2010 10101/npre.2010.4742.1
  7. 7. What is different is the perceived value of each to the research enterprise. That value difference is diminishing in part because of openness, accessibility, policy, governance, increased data reuse and lets not forget other forms of madness…
  8. 8. The Analog-Digital Data Knowledge Cycle P.E. Bourne, 2016, There is No Intelligent Life Down There
  9. 9. Paper Author Paper Reader Data Provider Data Consumer Employer Employee Reagent Provider Reagent Consumer Software Provider Software Consumer Grant Writer Grant Reviewer Supplier Consumer Platform MS Project Google Drive Coursera Researchgate Academia.edu Open Science Framework Synapse F1000 Rio Educator Student Platforms - The Situation Today
  10. 10. In summary there is not currently a widely adopted single platform for the exchange of services in biomedical research. Either there is a platform per service or no platform at all. Why have we not done better and what are the impediments today?
  11. 11. Impediments to a biomedical platform • Current work practices by all stakeholders • Entrenched business models • Size of the undertaking aka resources needed • Trust • Incentives to use the platform http://www.forbes.com/sites/johnhall/2013/04/29/10-barriers-to- employee-innovation/#8bdbaa811133
  12. 12. The NIH through the Big Data to Knowledge (BD2K) is experimenting with a platform, keeping in mind the need to overcome these impediments Enter The Commons https://en.wikipedia.org/wiki/Ealing_Common#/media/File:Eali ng_Common_-_geograph.org.uk_-_17075.jpg
  13. 13. Paper Author Paper Reader Data Provider Data Consumer Employer Employee Reagent Provider Reagent Consumer Software Provider Software Consumer Grant Writer Grant Reviewer Supplier Consumer Platform MS Project Google Drive Coursera Researchgate Academia.edu Open Science Framework Synapse F1000 Rio Educator Student Commons – Initial focus is on integrating two layers of the scholarly workflow
  14. 14. Commons Topology Compute Platform: Cloud or HPC Services: APIs, Containers, Indexing, Software: Services & Tools scientific analysis tools/workflows Data “Reference” Data Sets User defined data DigitalObjectCompliance App store/User Interface PaaS SaaS IaaS https://datascience.nih.gov/commons
  15. 15. Commons Compliance • Treat products of research – data, methods, papers etc. as digital objects • These digital objects exist in a shared virtual space • Digital object compliance through FAIR principles: • Findable • Accessible (and usable) • Interoperable • Reusable
  16. 16. NIH + Community defined data sets possible FOAs and CCM BD2K Centers, MODS, HMP & Interoperability Supplements Cloud credits model (CCM) BioCADDIE/Other Indexing NCI & NIAID Cloud Pilots Compute Platform: Cloud or HPC Services: APIs, Containers, Indexing, Software: Services & Tools scientific analysis tools/workflows Data “Reference” Data Sets User defined data DigitalObjectCompliance App store/User Interface Mapping BD2K Activities to the Commons Topology https://datascience.nih.gov/commons
  17. 17. Incentives • Airbnb • Monetize unutilized space • Ease of use • New vacation experience • Commons • Need to improve rigor and reproducibility • Productivity • Sustainability • Education and training • Opportunity to undertake elastic compute on large complex data
  18. 18. Summary • NIH has endorsed the Commons and the FAIR principles • The Commons is the beginnings of a platform from which to conduct biomedical research • Over the next 1-2 years we are conducting pilots to evaluate the feasibility of the Commons • If feasible the intent is to expand into additional layers of the scholarly research lifecycle
  19. 19. “I really admire Airbnb as a pioneer of the sharing economy and for building community. They've found an elegant way to help hosts make more money and for guests to have authentic experiences. It brings those people together in a unique way. “ Logan Green
  20. 20. “The Commons is an effort at creating a sharing economy and for building community. We hope for a more cost effective and productive research environment while bringing people together in a unique way. “ Phil Bourne
  21. 21. Speaking of a shared economy… You are invited to contribute to a shared document that describes this concept.. You will be acknowledged and the document put forward for NIH clearance to be blogged/preprinted/published…. https://docs.google.com/document/d/18WHyncB SvMNkD2h98eXf6BF7D_6fG_Ysi2ecInEIdR4/edit#h eading=h.ybszlhx51mar
  22. 22. Acknowledgements • ADDS Office: Vivien Bonazzi, Jennie Larkin, Michelle Dunn, Mark Guyer, Allen Dearry, Sonynka Ngosso, Tonya Scott, Lisa Dunneback, Vivek Navale (CIT/ADDS) • NCBI: George Komatsoulis • NHGRI: Valentina di Francesco • NIGMS: Susan Gregurick • CIT: Debbie Sinmao, Andrea Norris • NIH Common Fund: Jim Anderson , Betsy Wilder, Leslie Derr • NCI Cloud Pilots/ GDC: Warren Kibbe, Tony Kerlavage, Tanja Davidsen • Commons Reference Data Set Working Group: Weiniu Gan (HL), Ajay Pillai (HG), Elaine Ayres, (BITRIS), Sean Davis (NCI), Vinay Pai (NIBIB), Maria Giovanni (AI), Leslie Derr (CF), Claire Schulkey (AI) • RIWG Core Team: Ron Margolis (DK), Ian Fore, (NCI), Alison Yao (AI), Claire Schulkey (AI), Eric Choi (AI) • OSP: Dina Paltoo, Kris Langlais, Erin Luetkemeier, Agnes Rooke,
  23. 23. NIH… Turning Discovery Into Health philip.bourne@nih.gov https://datascience.nih.gov/ http://www.ncbi.nlm.nih.gov/research/staff/bourne/

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