Exactly!
Starting 5 years ago during my PhD in Biological & Medical Informatics, I decided I wanted to apply the “open source software” model to my research.
For this I used a site called Thinklab (now defunct) to discuss our project openly from the beginning. We engaged 40 individuals outside of our team, who received financial rewards for their contributions. The collaboration was a huge success, as was the resulting study:
Nowadays, we’re primarily using GitHub Issues for discussion, which work well because our research is entirely computational, and hence largely encapsulated by git repositories.
We also write manuscripts openly via GitHub using Manubot. This enables the “pull request” model for contributions where anyone can propose changes to a manuscript in a public venue with a transparent history. We’re hoping to reinvent publishing towards rigor, hackability, transparency, efficiency, automation, and reproducibility.
What is really missing today are the curation and incentive layers. We need greater incentives for researchers to work entirely in the open and collaborate as part of online, globally dispersed teams. Furthermore, when open scholarly content is posted online, we need curation systems to assess its value and reliability.
Steem is an interesting example of a blockchain that aims to generate and curate social content. As a decentralized platform for posting content it works well… I currently use it as my everyday blogging platform. Where Steem has fallen short is in its ability to promote good content, while demoting bad content. Vote selling and influence proportional to wealth rather than quality are two of its pitfalls.
But I think we’re close to a point where we can alter the incentives model and apply it to scholarly communication. Decentralized platforms that reward good science are so promising because they offer an alternative to the current journal-based publication & evaluation system.
Preprints are a step in the right direction (e.g. by dismantling paywalls & publishing delays). But alone preprints don’t solve the greatest inefficiencies in science: that research is siloed and that the same investigations are blindly repeated because efficient methods of sharing and discussing in-progress research have not been adopted. (currently, I’m working with Knowledgr to see if we can change this.)
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