AMIA 2014
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Transcript of AMIA 2014
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NIH as a Digital EnterprisePhilip E. Bourne Ph.D.
Associate Director for Data ScienceNational Institutes of Health
http://www.slideshare.net/pebourne/
http://bd2k.nih.gov/addsup_meeting.html#sthash.lS6Kw3jH.WbCnnPMq.dpbshttps://docs.google.com/document/d/12V3icSNfwOgykIkrmfq8hGu6Mm_1RbZ0kgDfwInTEwk/edit#heading=h.iwxmy5mfh114
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What Do we Mean by the Digital Enterprise?
http://bd2k.nih.gov/addsup_meeting.html#sthash.lS6Kw3jH.WbCnnPMq.dpbs
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Life in the Academic Digital Enterprise
Jane scores extremely well in parts of her graduate on-line neurology class. Neurology professors, whose research profiles are on-line and well described, are automatically notified of Jane’s potential based on a computer analysis of her scores against the background interests of the neuroscience professors. Consequently, professor Smith interviews Jane and offers her a research rotation. During the rotation she enters details of her experiments related to understanding a widespread neurodegenerative disease in an on-line laboratory notebook kept in a shared on-line research space – an institutional resource where stakeholders provide metadata, including access rights and provenance beyond that available in a commercial offering. According to Jane’s preferences, the underlying computer system may automatically bring to Jane’s attention Jack, a graduate student in the chemistry department whose notebook reveals he is working on using bacteria for purposes of toxic waste cleanup. Why the connection? They reference the same gene a number of times in their notes, which is of interest to two very different disciplines – neurology and environmental sciences. In the analog academic health center they would never have discovered each other, but thanks to the Digital Enterprise, pooled knowledge can lead to a distinct advantage. The collaboration results in the discovery of a homologous human gene product as a putative target in treating the neurodegenerative disorder. A new chemical entity is developed and patented. Accordingly, by automatically matching details of the innovation with biotech companies worldwide that might have potential interest, a licensee is found. The licensee hires Jack to continue working on the project. Jane joins Joe’s laboratory, and he hires another student using the revenue from the license. The research continues and leads to a federal grant award. The students are employed, further research is supported and in time societal benefit arises from the technology.
From What Big Data Means to Me JAMIA 2014 21:194
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I know you are interested in the policies and funding opportunities
that are coming but I think it helps to first get a sense of some things that
are motivating our thinking
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The Story of Meredith
http://fora.tv/2012/04/20/Congress_Unplugged_Phil_Bourne
Stephen Friend
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We have Entered An Era of Deinstitutionalize & Democratization
of Science
Daniel Hulshizer/Associated Press
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We have Entered An Era of Deinstitutionalize & Democratization
of Science – NIH Should Support This
Daniel Hulshizer/Associated Press
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I can’t reproduce research from my own laboratory?
Daniel Garijo et al. 2013 Quantifying Reproducibility in Computational Biology: The Case of the Tuberculosis Drugome PLOS ONE 8(11) e80278 .
Can you?
But what does it take and does it matter?
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47/53 “landmark” publications could not be replicated
[Begley, Ellis Nature, 483, 2012] [Carole Goble]
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Reproducibility Studies Are On-going Across the NIH
Expected outcomes:– Improved accessibility to data and software
– Support for workflows
– Closer relationships with publishers
– Metrics for measuring reproducibility
– Closure of the research lifecycle loop
– Rewards for reproducibility
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What Worries Me the Most - Sustainability
Source Michael Bell http://homepages.cs.ncl.ac.uk/m.j.bell1/blog/?p=830
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We Cant Go On Like This – Some Options
Introduction of business models– The 50% model
– Mergers
– Acquisitions associated with best practices
– Centralization
– Public/private partnerships
– Fee for service
– Archiving
Usage metrics / impact ….
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We don’t know enough about how current data
are used!
* http://www.cdc.gov/h1n1flu/estimates/April_March_13.htm
Jan. 2008 Jan. 2009 Jan. 2010Jul. 2009Jul. 2008 Jul. 2010
1RUZ: 1918 H1 Hemagglutinin
Structure Summary page activity forH1N1 Influenza related structures
3B7E: Neuraminidase of A/Brevig Mission/1/1918 H1N1 strain in complex with zanamivir
[Andreas Prlic]
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Ironic Since Some Industries Thrive By Asking These Questions
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Scholarship is broken
I have a paper with 17,000 citations that no one has ever read
I have papers in PLOS ONE that have more citations than ones in PNAS
I have data sets I am proud of few places to put them
I edited a journal but it did not count for much
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The reward system is in need of repair
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Okay… enough of the problems
What are some solutions?
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General Approach to Solutions …
New policies – Data sharing
– Blanket consent
– Data citation
Funding where it is most needed– New metrics
– De-identification
– Agile commons pilots
Smaller funding for the many, but with appropriate governance– Competitions
– Coordination across disciplines, agencies and countries
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General Approach to Solutions
Shared infrastructure– Commons
– Standards framework
– CDE homogenization
Support for new reward systems
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Lets Dig Down Based on How We Are Starting to Organize Ourselves
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Associate Director for Data Science
Commons BD2K Efficiency
Sustainability Education Innovation Process
• Cloud – Data & Compute
• Search• Security • Reproducibility
Standards• App Store
• Coordinate• Hands-on• Syllabus• MOOCs
• Community• Centers• Training Grants• Catalogs• Standards• Analysis
• Data Resource Support
• Metrics• Best
Practices• Evaluation• Portfolio
Analysis
The Biomedical Research Digital Enterprise
Partnerships
Collaboration
Programmatic Theme
Deliverable
Example Features • IC’s• Researchers• Federal
Agencies• International
Partners• Computer
Scientists
Scientific Data Council External Advisory Board
Training
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Associate Director for Data Science
Commons BD2K Efficiency
Sustainability Education Innovation Process
• Cloud – Data & Compute
• Search• Security • Reproducibility
Standards• App Store
• Coordinate• Hands-on• Syllabus• MOOCs
• Community• Centers• Training Grants• Catalogs• Standards• Analysis
• Data Resource Support
• Metrics• Best
Practices• Evaluation• Portfolio
Analysis
The Biomedical Research Digital Enterprise
Partnerships
Collaboration
Programmatic Theme
Deliverable
Example Features • IC’s• Researchers• Federal
Agencies• International
Partners• Computer
Scientists
Scientific Data Council External Advisory Board
Training
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Solution: The Power of the Commons
Data
The Long Tail
Core Facilities/HS Centers
Clinical /Patient
The Why:Data Sharing Plans
TheCommons
Government
The How:
DataDiscoveryIndex
SustainableStorage
Quality
Scientific Discovery
Usability
Security/Privacy
Commons == Extramural NCBI == Research Object Sandbox == Collaborative Environment
The End Game:
KnowledgeNIHAwardees
PrivateSector
Metrics/Standards
Rest ofAcademia
Software StandardsIndex
BD2KCenters
Cloud, Research Objects,Business Models
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Sustainability - the Commons
Compare Cancer Genomics Data Commons
dBGaP in the cloud
New business model
http://100plus.com/wp-content/uploads/Data-Commons-3-1024x825.png
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[Adapted from George Komatsoulis]
Commons Business Model
HPC, Institution …
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What Does the Commons Enable?
Dropbox like storage
The opportunity to apply quality metrics
Bring compute to the data
A place to collaborate
A place to discover
http://100plus.com/wp-content/uploads/Data-Commons-3-1024x825.png
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Pilots Around A Virtuous CycleExpect a Funding Call
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Associate Director for Data Science
CommonsTrainingCenter
BD2KModifiedReview
Sustainability* Education* Innovation* Process
• Cloud – Data & Compute
• Search• Security • Reproducibility
Standards• App Store
• Coordinate• Hands-on• Syllabus• MOOCs
• Community• Centers• Training Grants• Catalogs• Standards• Analysis
• Data Resource Support
• Metrics• Best
Practices• Evaluation• Portfolio
Analysis
The Biomedical Research Digital Enterprise
Communication
Collaboration
Programmatic Theme
Deliverable
Example Features • IC’s• Researchers• Federal
Agencies• International
Partners• Computer
Scientists
Scientific Data Council External Advisory Board
* Hires made
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Training & EducationTraining & Education
– Awards
– Metadata description of courses (virtual and physical)
– Cross-training
– VP training (with NSF)
– With libraries around curation etc.
http://bd2k.nih.gov/pdf/Documents_for_ADDS_Data_Science_Meeting_draft_edu_training_workforce_dev.pdf
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BD2K Training RFAsBD2K Training RFAs K01s for Mentored Career Development Awards,
RFA-HG-14-007
Provides salary and research support for 3-5 years for intensive research career development under the guidance of an experienced mentor in biomedical Big Data Science.
R25s for Courses for Skills Development, RFA-HG-14-008
Development of creative educational activities with a primary focus on Courses for Skills Development.
R25 for Open Educational Resources, RFA-HG-14-009
Development of open educational resources (OER) for use by large numbers of learners at all career levels, with a primary focus on Curriculum or Methods Development.
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Associate Director for Data Science
CommonsTrainingCenter
BD2KModifiedReview
Sustainability* Education* Innovation* Process
• Cloud – Data & Compute
• Search• Security • Reproducibility
Standards• App Store
• Coordinate• Hands-on• Syllabus• MOOCs
• Community• Centers• Training Grants• Catalogs• Standards• Analysis
• Data Resource Support
• Metrics• Best
Practices• Evaluation• Portfolio
Analysis
The Biomedical Research Digital Enterprise
Communication
Collaboration
Programmatic Theme
Deliverable
Example Features • IC’s• Researchers• Federal
Agencies• International
Partners• Computer
Scientists
Scientific Data Council External Advisory Board
* Hires made
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Data Discovery Index Coordination Consortium (Awards Sept)
Targeted Software Development (under review)
Investigator-initiated Centers of Excellence for Big Data (Awards Sept)
BD2K-LINCS-Perturbation Data Coordination and Integration Center (Award Fall)
BD2K Innovation FY 14 BD2K Innovation FY 14 (Jennie Larkin and Mark (Jennie Larkin and Mark
Guyer)Guyer)
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Relevant Workshops
– ELSI for research use of clinical data Spring 2015 Lyn Hardy and Ajay Pillai
– Private Sector Capacities Relevant to Advancing Research Use of Clinical Data Spring 2015 Nancy Miller and Valerie Florance, Jerry Sheehan and Leslie Derr
– Think Tank: Using EHRs for outcomes research and to identify risk factors/etiology of diseases. Fall 2014 Jerry Sheehan, Leslie Derr, Gina Wei, and Weinu Gan
– Think Tank: Inspiring the Game Developer Community to Engage in and Enhance Biomedical Research, Fall 2014 David Miller, Jennifer Couch
Others?
BD2K Innovation FY 15 BD2K Innovation FY 15 (Jennie Larkin and Mark (Jennie Larkin and Mark
Guyer)Guyer)
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Associate Director for Data Science
CommonsTrainingCenter
BD2KModifiedReview
Sustainability* Education* Innovation* Process
• Cloud – Data & Compute
• Search• Security • Reproducibility
Standards• App Store
• Coordinate• Hands-on• Syllabus• MOOCs
• Community• Centers• Training Grants• Catalogs• Standards• Analysis
• Data Resource Support
• Metrics• Best
Practices• Evaluation• Portfolio
Analysis
The Biomedical Research Digital Enterprise
Communication
Collaboration
Programmatic Theme
Deliverable
Example Features • IC’s• Researchers• Federal
Agencies• International
Partners• Computer
Scientists
Scientific Data Council External Advisory Board
* Hires made
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Process Current Efforts
– Clinical data harmonization
– Data citation
– Machine readable data sharing plans
– New review models, audiences etc.
• Open review
• Micro funding
• Standing data committees to explore best practices
• Crowd sourcing
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Associate Director for Data Science
CommonsTrainingCenter
BD2KModifiedReview
Sustainability* Education* Innovation* Process
• Cloud – Data & Compute
• Search• Security • Reproducibility
Standards• App Store
• Coordinate• Hands-on• Syllabus• MOOCs
• Community• Centers• Training Grants• Catalogs• Standards• Analysis
• Data Resource Support
• Metrics• Best
Practices• Evaluation• Portfolio
Analysis
The Biomedical Research Digital Enterprise
Communication
Collaboration
Programmatic Theme
Deliverable
Example Features • IC’s• Researchers• Federal
Agencies• International
Partners• Computer
Scientists
Scientific Data Council External Advisory Board
* Hires made
![Page 37: AMIA 2014](https://reader035.fdocuments.in/reader035/viewer/2022062705/556db33fd8b42a875d8b52d3/html5/thumbnails/37.jpg)
Collaboration Current Efforts
Joint public – private partnership workshop with NOAA?
2 joint workshops with NSF + Dear Colleague letter
OSTP – Open Data 2.0
HIRO’s big data meeting