The document discusses why FAIR data principles and the author's 2005 dream of seamlessly integrating data and literature have not been fully realized. It argues that incentives across the research lifecycle from funders to publishers and institutions must change to value open data sharing. While progress is being made with some funders and universities establishing data science programs, challenges remain around complex data, metadata standards, and determining compliance. Overall it presents an optimistic view that with continued coordination among stakeholders to promote reproducible science, FAIR data practices can become the norm.

1. It’s Just Not FAIR
Philip E. Bourne PhD, FACMI
Stephenson Chair of Data Science
Director, Data Science Institute
Professor of Biomedical Engineering
peb6a@virginia.edu
https://www.slideshare.net/pebourne
July 23, 2019 ISMB 2019 1
@pebourne

2. My Role Here
• Co-developer of the RCSB PDB
• First President of FORCE11
• An author of the FAIR Principles
• Chair of Data Policy Committee at PLOS
• Acting Dean of a proposed school that
will reward open
• What follows are my own opinions & I
can’t contribute much to the technology
discussion
Printer's Device of Johannes Froben
https://commons.wikimedia.org/wiki/File:Printer%27s_Device_of_Johannes_Froben.jpg
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3. Probability of
finding the data
associated with a
paper declined by
17% every year
Vines, Timothy et al. “The
Availability of Research Data
Declines Rapidly with Article Age.”
Current Biology (June 1, 2014)
Image: Nature doi:10.1038/nature.2013.14416
Just One Motivator –
Data Availability Declines Over Time
ALMOST ALL DATA LOST 10-15 YRS AFTER PUBLICATION
From Emma Ganley @ PLOS

4. July 23, 2019 4
In 2005 I Had a Dream
0. Paper is but one view
1. User clicks on thumbnail
2. FAIR data provide a
rendered image that
can be annotated
3. Selecting a features
provides a
database/literature
mashup
4. That leads to new
papers
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
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
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5. Why has the dream not been realized?
FAIR is like broccoli …
You know it is good for you,
but no one wants to eat it
By Fir0002 - Own work, GFDL 1.2, https://commons.wikimedia.org/w/index.php?curid=5772317
The incentives are not there
https://www.wideopeneats.com/recipes/broccoli-topped-cheese-sauce/July 23, 2019 ISMB 2019 5

6. What is the secret sauce …..
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7. Need to Impact All Aspects of the Research
Lifecycle
Publishershttps://www.vertigoventures.com/lesson/embedding-impact/impact-research-life-cycle/
Funders
Academic
Institutions
Publishers
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8. The role of institutions …
The secret sauce is they know they need to
change, but change is hard…
Needs to happen slowly with exemplars …
Data science initiatives represent those exemplars
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9. One institution with an
important opportunity
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We would not exist if
not for open data
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10. We Need to Change the Institutional Culture
Surrounding Data
• We need use cases of “eat your own dog food” to show value
• We need to embrace the institutional libraries role as one beyond
data preservation to that of curator & analyst
• We need to reward reproducible science and open science where
data plays a major role:
• Part of the faculty/staff handbook
• Part of the hiring process
• Part of the promotion process
• We need better data governance
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11. We need the institutional infrastructure for data …
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https://blog.lexicata.com/wp-content/uploads/2015/03/platform-model-
750x410.png
We need to move from pipes to platforms
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12. What is it Going to Cost and What is in it for
Me?
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13. We Need a Realistic Business Model
• Tuition
• Students use and reuse data and hence should pay for that quality data
• Federal Funding
• It’s a part of the solution, but not the whole solution, it will not scale
• Philanthropy
• Most philanthropists are not aware of the importance of data in what they give
money to support – Advancement offices need to be educated first
• Public Private Partnership
• Funding agencies should encourage this – it is more than SBIRs – witness capstones
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14. We Are Not Alone
Data Science Offerings at USA Research Universities (n=116)
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2019 N> 160
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15. Need to Impact All Aspects of the Research
Lifecycle
Publishershttps://www.vertigoventures.com/lesson/embedding-impact/impact-research-life-cycle/
Funders
Academic
Institutions
Publishers
July 23, 2019 ISMB 2019 15

16. PLOS Data Policy
• PLOS journals require authors to make all data underlying the findings
described in their manuscript fully available without restriction at the
time of publication. When specific legal or ethical requirements
prohibit public sharing of a dataset, authors must indicate how
researchers may obtain access to the data.
• When submitting a manuscript, authors must provide a Data
Availability Statement describing compliance with PLOS's policy. If the
article is accepted for publication, the data availability statement will
be published as part of the accepted article.
• Reliance on resources whose sustainability is unknown
• Who checks?
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17. >100,000
papers published with a data statement at PLOS
<0.1%
of submissions rejected due to authors’
unwillingness or inability to share data
~20%
of submissions use data repositories
From Emma Ganley @ PLOS

18. Natural Tension & Resistance
https://commons.wikimedia.org/wiki/File:Water_surface_tension_2.jpg

19. Challenges
• Research areas such as clinical studies require more
complex data sharing considerations and data release
mechanisms. Community input is important for policy
implementation
• Data citations and mechanisms to provide author
credit need to see a stronger uptake
• Metadata of published data sets is often lacking,
needs community-agreed standards
• It is not always clear what constitutes compliance
From Emma Ganley @ PLOS

20. Related PLOS Efforts Beyond Data
• Moving towards a software sharing policy
• Working a pilot with CodeOcean to include executable code in
publications
• Notion of reproducible models
• Emphasizing benchmarking section to show the value of data
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21. Summary - Why Has FAIR (Let Alone My
Dream) Not Been Realized (Optimistic View)?
• It starts with funder incentives – things are looking up
• Institutions have a role to play – the value of data is slowly
being realized
• Small publishers like PLOS have limited leverage - publishers
need to coordinate
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22. Thank You!
Questions?
peb6a@virginia.edu @pebourne
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