The document proposes a new model for faster communication of academic research based on a website like StackExchange. On the site, researchers could upload data, hypotheses, analyses, and visualizations which peers could then vote on. A researcher's profile would track their reputation in different areas. Universities may then consider reputation on the site for hiring and funding decisions. Publishers could also write narratives combining and peer reviewing research from the site. The proposed model aims to minimize delays and biases in current publishing while encouraging more open contributions and specialization.

1. A new model for
faster communication
of research
Kaveh Bazargan
www.RiverValleyTechnologies.com

2. @kaveh1000www.RiverValleyTechnologies.com
About us
• 28 years in publishing
• Typesetting of academic books and journals
• Last 10 years, put our systems into cloud
• Moving from service industry to SaaS
• Authoring
• Peer review
• Auto-pagination

3. @kaveh1000www.RiverValleyTechnologies.com
Our clients

4. @kaveh1000www.RiverValleyTechnologies.com
Current publishing model
• The academic “paper” is 350 years old
• Not going to change next year or even in 10 years
• But let’s stand back and examine the system

5. @kaveh1000www.RiverValleyTechnologies.com
Complaints about
scholarly publishing
(perceived or real)

6. @kaveh1000www.RiverValleyTechnologies.com
Delay in publication
• The “Paper” is the currency of academic impact
• But research is not “paper-shaped” – so takes time
• And needs peer review, proofreading, author
correction, typesetting…
• …Typically 1 year from discovery to dissemination

7. @kaveh1000www.RiverValleyTechnologies.com
Plagiarization and
misconduct
• 1 in 3 admit questionable practice to get published
• Increase in retractions in recent years
• “Purchased” papers, e.g. China, Middle East

8. @kaveh1000www.RiverValleyTechnologies.com
Bias in review
• Gender bias – e.g. research by Cassidy Sugimoto
• Early career researchers fear “retribution” in review

9. @kaveh1000www.RiverValleyTechnologies.com
Insufficient attribution
• 100s or 1000s of authors, but…
• who contributed most
• who did what – theory, data analysis, narrative

10. @kaveh1000www.RiverValleyTechnologies.com
And a few more problems
• Unreadable jargon, opaque for non-specialist
• Negative results not published
• Salami slicing to maximise publications

11. @kaveh1000www.RiverValleyTechnologies.com
An alternative way to
communicate research?

12. @kaveh1000www.RiverValleyTechnologies.com
A look at
StackExchange

13. @kaveh1000

14. @kaveh1000

15. @kaveh1000

16. @kaveh1000

17. @kaveh1000www.RiverValleyTechnologies.com
Why so much effort?
• Programmers want recognition by peers
• … just like academics

18. @kaveh1000www.RiverValleyTechnologies.com
A bit more about
StackExchange
• Strict code of conduct, moderated by community
• Reputation is gained in time by contribution
• Every contribution can be voted up or down
• Job portal connects with employers

19. @kaveh1000www.RiverValleyTechnologies.com
Let’s imagine a similar
site for research…

20. @kaveh1000www.RiverValleyTechnologies.com
microbiology.org
• Open for all to see
• Register using real name or pseudonym
• Members can vote peers’ work (up or down)

21. @kaveh1000www.RiverValleyTechnologies.com
A typical scenario
• Jeff Lewis uploads new data and hypothesis
• Peers vote for data gathering and original idea
• bio532 creates visualisation of data
• bio532 gets votes for data visualisation
• micro_bio_guy analyses data
• micro_bio_guy gets votes for data analysis

22. @kaveh1000www.RiverValleyTechnologies.com
A user profile
Theoretical insight
Data quality
Data analysis
Data visualisation
Copy editing
Bibliography
Clear explanation

23. @kaveh1000www.RiverValleyTechnologies.com
Now imagine…
• Universities and funders note reputation on site
• Applicants for academic posts include reputation
• University can judge
• Precise expertise (experimental or theoretical)
• Teaching ability

24. @kaveh1000www.RiverValleyTechnologies.com
Bias minimised
• Applicants for posts could be anonymous until
interview date
• … so no race, age or gender bias

25. @kaveh1000www.RiverValleyTechnologies.com
Do we need a
publisher?

26. @kaveh1000www.RiverValleyTechnologies.com
Absolutely!

27. @kaveh1000www.RiverValleyTechnologies.com
We need narrative
• Anyone (e.g. journalist) can write the “story”
• Any publisher can publish (open or subscription)
• Can publish part of research or combine research
• Publishers might “scout” the site
• Not a formal paper but a readable narrative
• Fully peer reviewed

28. @kaveh1000www.RiverValleyTechnologies.com
Advantages of new system
• Research moves fast
• No bias (identities can be hidden)
• All do what they like and are good at
• No plagiarization, misconduct, retractions
• Anyone can contribute
• Better publications