The New Academia: Final chapter of a new beginning

After some thought provoking questions that might be the start of the design of a completely new type of learning institution, one that is equitable and where students and staff have influence on strategic decision making, we can now move towards the final chapter. There still are two questions that remain unanswered, first, how can we make academic publishing equitable, accessible and fair and second, how can we enable collaboration around data?

1. Can we turn this academic publishing model upside down? Can we make an equitable model for scientific peer reviewing and publishing?
2. What if we can empower data collaboration and eventually data monetisation in academia?

The new University model

When we started thinking about a decentralised university last month, you probably wondered how such a system can keep it's own pants up. This is a good question. You could form an advanced skill-share model where educators receive a basic salary and extras come from how popular their courses are, as access to courses are purchased individually, 1-1 sessions are paid for separately, assessments are paid for separately and/or course access can be resold. In all this, there are transactions & royalties which will suffice for the educators and platform to stay afloat just fine.

However, that does not yet pay for deep research and will unlikely pay for those students who depend on a pay-it-forward model (community grants for underprivileged students).

This is where the answer to question two comes-in. What happens when academics, departments, universities and even enterprises collaborate on data? What if research papers actually become copyrighted that can then be repurposed for commercial purposes?

Academic data and research, the currency that can power academia

If data is the new oil, then academic data becomes a currency that will empower researchers and will power future generations for years to come. Any enterprise looking for the highest quality data and research findings will understand that peer-reviewed datasets, data that has been developed in collaborative ways between academics, and even between academic institutions holds huge value. Whether you are a market research company, looking for new datasets or a biochemical lab that is creating new cleaning products, it is pretty straight forward to start looking for data from academia first.

So why is it that even within academic institutions data is hardly being shared, let alone that there are hardly any data collaborations? One simple answer is that it is often, even within a university, not clear what data there is and who owns it. So step one is to create a sort of internal data catalogue. Next is to open up that data internally, so that others can use it for their research or can contribute to it. The beauty of this is, that when done right, contributions can be tracked (useful for later monetisation if needed).

From here onwards is a small step to enable other academic institutions to get access and collaborate on shared datasets from each other's data catalogues. The biolabs that are doing similar research, or are gathering similar data, can work on the same datasets, regardless of where the labs are based. Again, contributions are tracked, so it is clear which institute added what amount of data. Academic institutions that focus more on social science, might do local research on consumer behaviour or emerging trends and by pulling the same research from other regions around the world together significant new insights will be gathered.

The aforementioned examples create extremely valuable datasets and/or data catalogues. This value is currently not at all captured, other than publishing academic papers (more about that later). By making such powerful combinations, these datasets can now be repurposed, for commercial use cases. Enterprises, and governments alike would be very much willing to purchase access to the data, they pay big bucks for this already. However by paying academia directly for the data, they automatically fund the next research, as the $ paid will flow directly to the institutions which can then reallocate the funds, to stimulate new research (virtuous cycle) and to enable underprivileged students to study creating that equitable environment we were looking for in the first place.

Rethinking how academic journals work

In June we talked about the ironic situation where researchers, those who wish to publish their research, are expected to pay up to $50k to get published in a mediocre journal. At the same time, these journals charge the universities giant fees so they (and their students) can get access to these same publications! All while the universities pay salaries to the researchers in order to do what they do best.

The obvious winner here are the journals, the losers are those who do not have the funds to pay to get published and eventually the tax payers that indirectly fund academic research and with that these expensive publications.

So yeah, it is time indeed for a new model. Whereas we already saw that data can be repurposed and commercialised, especially when the academic data is the result of collaboration. We can now also think how things might look when publications and the use of that is tracked properly, and where copyright is directly registered.

The new model for academic journals

Let me summarise a model that I made a few years back. What happens when there is a platform (decentralised journal) where peers do their peer-reviews 'blind' so they do not know who they are reviewing? The feedback they give is made public and transparent. We add that there need to be three reviewers, minimum two out of three need to vote 'yes' to the question if something is publishable. By 'getting it right', they earn reputation points, which in turn give them more visibility AND gives them the chance to publish more. The peer-reviewers also get a small royalty percentage, for adding their reviews to the article, so that everyone can see their expert opinions. This enhances the quality of the work eventually, and makes the research papers itself commercially more (or less) interesting.

Now when anyone (such as a newspaper) purchases access to the original paper, not only does the platform generate a small fee, so will the peer-reviewers and the original authors. By also adding reputation points to the original publishers, their publications will become more valuable, as more companies will want to have access to the work of more reputable researchers. So it pays off to keep using and publishing on the platform and it pays off to keep peer-reviewing work.

Instead of charging lots of $ for a publication, we give the researcher who aims to publish something of value back in return, as this person eventually brings value to the decentralised journal. Each article published is worth a governance token, that can be used to vote on strategic matters. Perhaps there are other possible tokenomics in play, for example part of the platform profit goes back into buying tokens on the open market to maintain the value.

There are many more angles to explore here, and to my point, it is actually a real possibility to make this happen.

So what is next for academics?

The beautiful thing is that the infrastructure for data collaboration, sharing and monetization is already there with Nuklai ! This same infrastructure can be used for decentralised academic journals and even to build decentralised learning institutions if we want to!

So should someone do it? Well, YES absolutely. And I am very much willing to help.

Leave your comments and thoughts to continue the discussion!