1. Where Have We Been & Where
Are We Going?
Philip E. Bourne, Ph.D.
Associate Director for Data Science
philip.bourne@nih.gov
2. Its 4 years since many of us stood
before the bear.. What has been
accomplished?
http://saltypeppergames.com/why-your-feedback-matters/
https://sites.google.com/site/beyondthepdf/
3. I decided to crowd source an
albeit biased answer to that
question
4.
5.
6. Major Contributors (In Order):
Policy
• Funder mandates
• Journals requiring data accessibility
• Joint declaration of data sharing principles
• Gates foundation
• Peer review
– Open
– Post publication
– Independent e.g., axios
7. Major Contributors (In Order):
Software
• GitHub
• R
• Dropbox
• Google Docs
• Impact Story
• eNotebooks
• MathJax
8. Major Contributors (In Order):
Methodology
• Crowdfunding
• Prepublication servers
• Open worm – crowd funding – 60
developers
• Software carpentry
10. Major Contributors (In Order):
Resources
• Figshare
• Wikidata
• Dryad
• Twitter
• Blogs
11. Major Contributors (In Order):
Other
• Altmetrics
• Social reference management
• Growing awareness of research expertise
eg Vivo
• Data science as a profession
• Resource Identification Initiative
• Ioannidis work
• Mega journals
13. My Personal View
• Pluses
– The strength and
breadth of the FORCE
community
– The emergence of
other related
communities
– Funder mandates
– The worldwide focus
on data {sharing}
• Minuses
– That not more has
been done with the OA
corpus
– OA impact has been
minimal
– Top down and bottom
up have yet to be truly
synergistic
– The global community
is not united (HIROs)
14. The Way Forward is 3-Fold
Community
Policy
Infrastructure
• Sustainability
• Collaboration
• Training
15. A point of note:
Both EBI in the EU and NLM in the
US will soon assume new
leadership
This is a major opportunity
16. Community Policy
Infrastructure
The library has a tradition of supporting
community, being an infrastructure to
maintain knowledge and in the case of NLM a
place to set policy
17. What should the library / data
center of the future look like and
can that view inform our future
objectives?
18. The library (or whatever it is
called) should curate, catalog,
preserve, and disseminate the
complete digital research lifecycle
You can also imagine this model
extending to physical artifacts
20. Individual Research Objects
within a lifecycle should be
referenced and described
Temporal order should be
maintained
Languages will describe,
compare, relate and analyze such
lifecycles
21. Collections (Formally Databases)
Particular collections of curated
research objects that can be
reviewed within the research
lifecycle and as part of a
collective analysis
Collections are persistent or
dynamic
22. This is a different model than we have
today but there are signs and also
resistance
• Signs
– Institutional
repositories run by
libraries
– Academic presses (?)
– Preservation of
workflows
– Portals
• Resistance
– Publishers punting on
data and software
– Reward structure
ingrained
– Few funding
opportunities
23. It Will Be Interesting to See What
Evolves
Thank You!