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Ten Simple Rules for Changing How
Scholars Communicate
Philip E. Bourne, PhD, FACMI
Associate Director for Data Science
National Institutes of Health
September 23, 2015
History & Lets Crowd Source?
http://www.ploscollections.org/article/browse/issue/info%3Adoi%2F10.1371%2Fissue.pcol.v03.i01
2.6 million downloads
Rule 1
Figure Out the Flow & Go With It
(Aka Leverage What is Already
Happening)
One Obvious Change
We are at a Point of Deception …
 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
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
Are We Being Deceived?
The 6D Exponential Framework
Digitization
Deception
Are We Here?
Disruption
Demonetization
Dematerialization
Democratization
Open science
Free & Usable
Knowledge
Rule 2
Recognize Thus Far That Open
Access Has Been a Disappointment
http://mujeresdelsiglo21.com/wp-content/uploads/2013/07/little-girl-crying-1280x800.jpg
Rule 2 OA Disappointment
 Access has improved; leveraging the content only
marginally?
 The profits of closed access journals has increased –
presumably at the cost of more scholarship?
 The system is still broken – OA has not
fundamentally changed how scholars communicate
Rule 3
“Still Crazy After All These Years”
Not Paul Simon But Ten Years After
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
Here is What I Want – The Paper
As Experiment
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) e34
Rule 4
Value the Right Things
The Google Bus
Rule 5
Data Are Scholarship
Data Are Scholarship
* 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 for
H1N1 Influenza related structures
3B7E: Neuraminidase of A/Brevig Mission/1/1918
H1N1 strain in complex with zanamivir
[Andreas Prlic]
Rule 6
Software is Scholarship
Rule 7
Its Important to be FAIR
https://www.force11.org/group/fairgroup/fairprinciples
BD2K
Center
BD2K
Center
BD2K
Center
BD2K
Center
BD2K
Center
BD2K
Center
DDICC
Software
Standard
s
Infrastructure - The
Commons
Labs
Labs
Labs
Labs
Rule 8
Recognize New Levers When You See
Them
Rule 8 Lever: Preprint Servers
http://biorxiv.org/content/early/2015/07/11/022368
Rule 8 Lever: 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 .
Rule 9
Its About The Whole Research Life
Cycle
The Research Lifecycle
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
The Research Lifecycle
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
Rule 10 Prove Me Wrong
So remember, when you're feeling very small
and insecure
How amazingly unlikely is your birth
And pray that there's intelligent life somewhere
up in space
'Cause there's bugger all down here on Earth
Monty Python - Galaxy Song Lyrics |
MetroLyrics
NIHNIH……
Turning Discovery Into HealthTurning Discovery Into Health
philip.bourne@nih.gov
https://datascience.nih.gov/

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Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
 

Ten Simple Rules for Changing How Scholars Communicate

  • 1. Ten Simple Rules for Changing How Scholars Communicate Philip E. Bourne, PhD, FACMI Associate Director for Data Science National Institutes of Health September 23, 2015
  • 2. History & Lets Crowd Source? http://www.ploscollections.org/article/browse/issue/info%3Adoi%2F10.1371%2Fissue.pcol.v03.i01 2.6 million downloads
  • 3. Rule 1 Figure Out the Flow & Go With It (Aka Leverage What is Already Happening)
  • 5. We are at a Point of Deception …  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
  • 6. 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
  • 7. Are We Being Deceived? The 6D Exponential Framework Digitization Deception Are We Here? Disruption Demonetization Dematerialization Democratization Open science Free & Usable Knowledge
  • 8. Rule 2 Recognize Thus Far That Open Access Has Been a Disappointment http://mujeresdelsiglo21.com/wp-content/uploads/2013/07/little-girl-crying-1280x800.jpg
  • 9. Rule 2 OA Disappointment  Access has improved; leveraging the content only marginally?  The profits of closed access journals has increased – presumably at the cost of more scholarship?  The system is still broken – OA has not fundamentally changed how scholars communicate
  • 10. Rule 3 “Still Crazy After All These Years” Not Paul Simon But Ten Years After
  • 11. 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 Here is What I Want – The Paper As Experiment 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) e34
  • 12. Rule 4 Value the Right Things
  • 14. Rule 5 Data Are Scholarship
  • 15. Data Are Scholarship * 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 for H1N1 Influenza related structures 3B7E: Neuraminidase of A/Brevig Mission/1/1918 H1N1 strain in complex with zanamivir [Andreas Prlic]
  • 16. Rule 6 Software is Scholarship
  • 17. Rule 7 Its Important to be FAIR https://www.force11.org/group/fairgroup/fairprinciples
  • 19. Rule 8 Recognize New Levers When You See Them
  • 20. Rule 8 Lever: Preprint Servers http://biorxiv.org/content/early/2015/07/11/022368
  • 21. Rule 8 Lever: 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 .
  • 22. Rule 9 Its About The Whole Research Life Cycle
  • 23. The Research Lifecycle 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
  • 24. The Research Lifecycle 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
  • 25. Rule 10 Prove Me Wrong So remember, when you're feeling very small and insecure How amazingly unlikely is your birth And pray that there's intelligent life somewhere up in space 'Cause there's bugger all down here on Earth Monty Python - Galaxy Song Lyrics | MetroLyrics
  • 26. NIHNIH…… Turning Discovery Into HealthTurning Discovery Into Health philip.bourne@nih.gov https://datascience.nih.gov/

Notas del editor

  1. Five Big Problems to Solve: Finding, Accessing, Interoperating with, and Re-using the data (FAIR principles) Extending policies and practices for data sharing Organizing, managing, and processing biomedical Big Data Developing new methods and tools for analyzing biomedical Big Data Training researchers who can use biomedical Big Data effectively