Fiona Nielsen founded Repositive to address the challenges of data sharing and accessibility in genomics research. Repositive developed tools to make large amounts of genomic data more discoverable, including a search engine of over 1 million public data sets. Repositive also launched a marketplace to help cancer researchers find the right models for their studies by organizing complex data on genetic profiles and phenotypes of thousands of cancer models. However, Nielsen notes that while standards and tools are important, incentives are also needed to motivate data sharing and reuse at scale. She advocates recognizing data stewardship contributions and aligning policies and practices, like hiring and funding, to incentivize open data practices.

1. Standards, tools, incentives – what does it take to enable data sharing?
Fiona Nielsen at AIDR, May 14th 2019

2. I used to be a scientist
- like you

3. I became frustrated by my lack
of data access
Picture by Melissa O’Donahue CC-BY-ND

4. Strongly motivated by the journey of my mother

5. “Someone has got to do something!”
Fiona Nielsen
Around 2012

6. I wanted to build a data broker for genomics data
To speed up research
DNAdigest
Founded Repositive with Adrian

7. With Repositive we built a search engine for genomics
Contributed our data
search expertise to the
NIH Data Commons
Pilot
Open pages – all
indexed by Google
Index of >1million
public genomic data
sets
All users can
contribute
annotation and data
sets
Visit http://discover.repositive.io

8. We launched a marketplace for translational cancer models
Biopharma Cancer R&D Cancer model vendors
(CROs)
Help researchers find the right cancer
model to suit their needs in drug
development for precision medicine

9. What do cancer models have to do with data?
The cancer models are described by complex data:
• Genetic profile
• Tumor type
• Cancer growth and phenotype
There are 100s of cancer model providers
With 1000s of cancer models

10. Finding the right cancer model is a data access problem
Photo by Marblesgalore.com

11. We organize the data to make it easily searchable
Photo by Marblesgalore.com

12. Our platform enables data discovery and data sharing
Biopharma Cancer R&D Cancer model vendors
(CROs)
Serving pre-
clinical
CROs
seeking
customers
who are
interested in
their cancer
models
Serving
researchers
who are
looking to
outsource
their cancer
model
experiments World’s largest inventory of cancer
models 5,000+ models in our partner
networkRead more on http://repositive.io/

13. Why is data sharing still a
problem?

14. The scientific approach for addressing challenges
Solving the problem for Alice and Bob:
1. Define the problem
2. Design a solution
3. Publish a paper
You are done.
By odder - own work, based on png version originally uploaded to the Commons by Dake., CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=1812312

15. Some steps are missing to solve the problem
Your solution/algorithm/standard method (i)
need to be implemented into an easy-to-use and available tool (ii)
And the people who are experiencing the problem need a reason/incentive (iii) to use the tool
Unfortunately, the scientific approach only addresses (i)

16. We have lots of algorithms and proposed standards
But not all of them are solving real problems…
https://xkcd.com/927/

17. On the other hand, if you have incentives…
©Derek Law

18. What have I learnt across academia and industry?
Data sharing is a multi-step process
Before you can access data, you need to
 Assert this data is the data that you need
 Discover that the data exists
 someone made that data discoverable
Each step of the process requires
incentives, tools, standards

19. My prediction
No advanced AI/ML tool will dramatically improve the data contributed,
discovered or accessed outside the communities and problem domains
where there is a strong incentive for it’s use.

20. But will incentives alone fix the problem?
You have to fix two sides:
- Increase the incentives
- And/or lower the effort needed to use the tools
- Incentives?
- Fix scientific publishing to include data
- Fix hiring, promotion, tenure criteria
- Fix funding requirements
©ReinierVanOorsouw

21. Take an example from AirBnB
Incentives and tools existed before AirBnB
Holiday homes would be listed on Craigslist
What did AirBnB do?
They made it easier to search for rentals,
And super-easy to make data about your rental home
discoverable!
AirBnB:
Incentives > tools > standards and methods
http://ui-patterns.com/explore/domain/airbnb+com

22. My message to you
Is not to stop developing methods 
It is:
If you care about the impact you want to make and you want to see the problem solved on a
larger scale, you have to care about making easy to use tools and fixing the incentives.
It is not an easy task, but I am with you on this one!

23. What can I do today to fix incentives?
Acknowledge and give credit for good data stewardship data creation, data visibility, data
accessibility, data curation, data publishing and data sharing.
Start in your day-to-day work: e.g. create a data steward award in your lab!
Always include when hiring, promoting and funding: promote good data stewardship
Make your data stewardship tools really easy to use (documentation, support, etc)
& keep developing cool methods 

24. Thank you for your attention – go share that data!

25. repositive [ re-poz-i-tiv ], noun;
1. a positive experience of accessing
genomic data repositories
Thanks for listening!
Find me on twitter @glyn_dk
and read more about us at Repositive.io