This document discusses the importance of digital research objects being not just open, but FAIR (Findable, Accessible, Interoperable, Reusable). It notes that big life science companies have evolved from keeping data and innovation mostly inside the company to now distributing data more openly and collaborating in heterogeneous partnerships across different organizations. However, current academic incentive and evaluation systems do not properly recognize or reward activities like sharing data, software, publications or patents. The document calls for rethinking these systems and designing new career paths for data scientists to better align incentives with open and collaborative research practices.

1. Consultant,
Honorary Academic Editor
Associate Director,
Principal Investigator
Susanna-Assunta Sansone, PhD
@biosharing
Westminster Higher Education Forum
London, 25 March, 2015

2. Not just data, but digital research objects

3. Not just open, but FAIR research objects

4. Big
Life
Science
Company
Yesterday Today Tomorrow
Yesterday Today Tomorrow
Innovation Model Innovation inside Searching for Innovation Heterogeneity of collaborations;
part of the wider ecosystem
IT Internal apps & data Struggling with change
security and trust
Cloud, services
Data Mostly inside In and out Distributed
Portfolio Internally driven and owned Partially shared Shared portfolio
Credit to: Pistoia Alliance
Big
Life
Science
Company
Proprietary
content
provider
Public
content
provider
Academic
group
Software vendor
CRO
Service provider
Regulatory
authorities
Benefits to business, e.g. life sciences companies

5. The value of public-private-partnerships

6. An example advancing the FAIR concept

7. More progresses and alliances in UK, EU…

8. More progresses and alliances in UK, EU & USA

9. What counts
• Money
• Grants
• Papers
• Teaching
• Service…
What does not
• Sharing data
• Sharing software
• Open access
• Collaboration
• Patents…
Paraphrasing:
Getting Ahead as a Computational Biologist in Academia PLOS Comp Biol
doi:10.1371/journal.pcbi.1002001
Credit to: Melissa Haendel
What really matters to researchers?

10. What counts
• Money
• Grants
• Papers
• Teaching
• Service…
What does not
• Sharing data
• Sharing software
• Open access
• Collaboration
• Patents…
Paraphrasing:
Getting Ahead as a Computational Biologist in Academia PLOS Comp Biol
doi:10.1371/journal.pcbi.1002001
Credit to: Melissa Haendel
What really matters to researchers?

11. New driving forces…..

12. Re-think REF
+
Design career paths for data scientists
New driving forces…..