The Future of Open Science
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The Future of Open Science

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Presented at the NIAID Festival on Open Science April 8-9, 2014 NIH Campus, MD, USA

Presented at the NIAID Festival on Open Science April 8-9, 2014 NIH Campus, MD, USA

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  • 1. The Future of Open Science Philip E. Bourne http://www.slideshare.net/pebourne/ 4/08/14 NIAID Workshop on Open Science 1
  • 2. The future depends on who you ask Here is my biased viewpoint 4/08/14 NIAID Workshop on Open Science 2
  • 3. My Background/Bias • RCSB PDB/IEDB Database Developer – Views on community, quality, sustainability … • PLOS Journal Co-founder – Open science advocate • Associate Vice Chancellor for Innovation – Business models, interaction with the private sector, sustainability • Professor – Mentoring, reward system, value (or not) of research • NIH Strategist/Transformer - ?? 4/08/14 NIAID Workshop on Open Science 3
  • 4. Perhaps the first question to ask is: What is an endpoint? 4/08/14 NIAID Workshop on Open Science 4
  • 5. What is an Endpoint? 4/08/14 NIAID Workshop on Open Science 5
  • 6. What Does The Democratization of Science Imply? • The obvious – participation by all • Not so obvious – More scrutiny – New types of rewards – More equal value placed on all participants – The removal of artificial boundaries that corral knowledge (through power and resources) within silos that do not make sense as complexity increases 4/08/14 NIAID Workshop on Open Science 6
  • 7. Consider some personal examples that illustrate these implications 4/08/14 NIAID Workshop on Open Science 7
  • 8. More Scrutiny – Highlights Lack of Reproducibility • I can’t immediately reproduce the research in my own laboratory: • It took an estimated 280 hours for an average user to approximately reproduce the paper • Workflows are maturing and becoming helpful • Data and software versions and accessibility prevent exact reproducibility Daniel Garijo et al. 2013 Quantifying Reproducibility in Computational Biology: The Case of the Tuberculosis Drugome PLOS ONE 8(11) e80278 . NIAID Workshop on Open Science 84/08/14
  • 9. Why New Types of Rewards? • I have a paper with 16,000 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 4/08/14 NIAID Workshop on Open Science 9
  • 10. Equal Value Placed on Participants • The UC System has Research Scientists (RS) & Project Scientists (PS) as well as tenured faculty - – RS/PS have no senate rights yet: – RS/PS frequently teach – RS/PS frequently have more grant money – RS/PS typically perform more service – RS/PS are most of the data scientists you know 4/08/14 NIAID Workshop on Open Science 10
  • 11. Are Increasingly Found on the Google Bus 4/08/14 NIAID Workshop on Open Science 11
  • 12. Institutional Boundaries • Academia – Departments of physics, math, biology, chemistry etc. persist but scholars rarely confine themselves to these disciplines • NIH – 27 institutes and centers, many dedicated to specific diseases & conditions – yet a specific gene undoubtedly transcends ICs 4/08/14 NIAID Workshop on Open Science 12
  • 13. The Era of Open Has The Potential to Deinstitutionalize NIAID Workshop on Open Science 13 Daniel Hulshizer/Associated Press 4/08/14
  • 14. An Example of That Potential: The Story of Meredith NIAID Workshop on Open Science 14 http://fora.tv/2012/04/20/Congress_Unplugged_Phil_Bourne 4/08/14
  • 15. The Era of Open Has The Potential to Deinstitutionalize NIAID Workshop on Open Science 15 Daniel Hulshizer/Associated Press 4/08/14
  • 16. I have argued that the democratization of science is compelling and that much has happened around open literature, open software and now open data 4/08/14 NIAID Workshop on Open Science 16
  • 17. I Would Also Argue That This Process is About to Accelerate • Others provide a more compelling argument: – Google car – 3D printers – Waze – Robotics 4/08/14 NIAID Workshop on Open Science 17
  • 18. From the Second Machine Age 4/08/14 NIAID Workshop on Open Science 18 From: The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies by Erik Brynjolfsson & Andrew McAfee
  • 19. So what will this look like for an institution? 4/08/14 NIAID Workshop on Open Science 19 Institutions will become digital enterprises
  • 20. Components of The Academic Digital Enterprise • Consists of digital assets – E.g. datasets, papers, software, lab notes • Each asset is uniquely identified and has provenance, including access control – E.g. publishing simply involves changing the access control • Digital assets are interoperable across the enterprise 4/08/14 NIAID Workshop on Open Science 20
  • 21. 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 4/08/14 NIAID Workshop on Open Science 21
  • 22. Life in the NIH Digital Enterprise • Researcher x is made aware of researcher y through commonalities in their data located in the data commons. Researcher x reviews the grants profile of researcher y and publication history and impact from those grants in the past 5 years and decides to contact her. A fruitful collaboration ensues and they generate papers, data sets and software. Metrics automatically pushed to company z for all relevant NIH data and software in a specific domain with utilization above a threshold indicate that their data and software are heavily utilized and respected by the community. An open source version remains, but the company adds services on top of the software for the novice user and revenue flows back to the labs of researchers x and y which is used to develop new innovative software for open distribution. Researchers x and y come to the NIH training center periodically to provide hands-on advice in the use of their new version and their course is offered as a MOOC. 4/08/14 NIAID Workshop on Open Science 22
  • 23. To get to that end point we have to consider the complete digital research lifecycle 4/08/14 NIAID Workshop on Open Science 23
  • 24. The Digital Research Life Cycle IDEAS – HYPOTHESES – EXPERIMENTS – DATA - ANALYSIS - COMPREHENSION - DISSEMINATION 4/08/14 24NIAID Workshop on Open Science
  • 25. Tools and Resources Will Be Better Coordinated IDEAS – HYPOTHESES – EXPERIMENTS – DATA - ANALYSIS - COMPREHENSION - DISSEMINATION Authoring Tools Lab Notebooks Data Capture Software Analysis Tools Visualization Scholarly Communication 4/08/14 NIAID Workshop on Open Science 25
  • 26. Through Interconnection Around a Common Framework IDEAS – HYPOTHESES – EXPERIMENTS – DATA - ANALYSIS - COMPREHENSION - DISSEMINATION Authoring Tools Lab Notebooks Data Capture Software Analysis Tools Visualization Scholarly Communication 4/08/14 NIAID Workshop on Open Science 26
  • 27. New/Extended Support Structures Will Emerge IDEAS – HYPOTHESES – EXPERIMENTS – DATA - ANALYSIS - COMPREHENSION - DISSEMINATION Authoring Tools Lab Notebooks Data Capture Software Analysis Tools Visualization Scholarly Communication Commercial & Public Tools Git-like Resources By Discipline Data Journals Discipline- Based Metadata Standards Community Portals Institutional Repositories New Reward Systems Commercial Repositories Training 4/08/14 NIAID Workshop on Open Science 27
  • 28. We Have a Ways to Go IDEAS – HYPOTHESES – EXPERIMENTS – DATA - ANALYSIS - COMPREHENSION - DISSEMINATION Authoring Tools Lab Notebooks Data Capture Software Analysis Tools Visualization Scholarly Communication Commercial & Public Tools Git-like Resources By Discipline Data Journals Discipline- Based Metadata Standards Community Portals Institutional Repositories New Reward Systems Commercial Repositories Training 4/08/14 NIAID Workshop on Open Science 28
  • 29. But Lets Not Forget NIH has Contributed a Lot • NLM/NCBI • Individual IC support • Open access policies – PubMed Central • Emergent data sharing plans • Big Data to Knowledge (BD2K) • Office of the Associate Director for Data Science • .. And more to come… 4/08/14 NIAID Workshop on Open Science 29
  • 30. Call Out to Eric Green, and the Team… 4/08/14 NIAID Workshop on Open Science 30 bd2k.nih.gov
  • 31. Interesting Observations So Far • We need to start by asking, how are we using the data now? • We have the why for data sharing, but not the how • Training is spotty • Existing data resources need attention • Sometimes it is enough for me to sit down 4/08/14 NIAID Workshop on Open Science 31
  • 32. Office of Data Science Data Commons Training Center BD2K Review Sustainability Education Innovation Process • Cloud – Data & Compute • Search • Security • Reproducibility Standards • App Store • Hands-on • MOOCs • Community Engagement • Data Science Centers • Training Grants • DDI • Analysis • Domain Support • Data Resource Support • Metrics • Best Practices • Evaluation • Portfolio Analysis The Biomedical Research Digital Enterprise Communication Collaboration Programmatic Theme Deliverable Example Features • To IC’s • To Researchers • To Federal Agencies • To International Partners • To Computer Scientists Scientific Data Council External Advisory Board 04/03/14
  • 33. 1. A link brings up figures from the paper 0. Full text of PLoS papers stored in a database 2. Clicking the paper figure retrieves data from the PDB which is analyzed 3. A composite view of journal and database content results One Possible End Point 1. User clicks on thumbnail 2. Metadata and a webservices call provide a renderable image that can be annotated 3. Selecting a features provides a database/literature mashup 4. That leads to new papers 4. The composite view has links to pertinent blocks of literature text and back to the PDB 1. 2. 3. 4. PLoS Comp. Biol. 2005 1(3) e344/08/14 33
  • 34. Open Science Will: • Lead to the democratization of science • Change how institutions think and operate – they will become digital enterprises • Impact all aspects of the scholarly research lifecycle • Accelerate seek{ing} fundamental knowledge about the nature and behavior of living systems and the application of that knowledge to enhance health, lengthen life, and reduce illness and disability 4/08/14 NIAID Workshop on Open Science 34
  • 35. Thank You! Questions? philip.bourne@nih.gov Acknowledgements • Vivien Bonazzi • Eric Green • Mark Guyer • Jennie Larkin • David Lipman • Peter Lyster • Many more…. 4/08/14 NIAID Workshop on Open Science 35