How Web3 starts a paradigm shift in data economies

My colleague, Gerben van den Bergh , recently did an interesting comparison where he compared the growing importance of oil in the past to the growing importance of data in the economies today. I am aware of the fact that it is difficult to make direct comparisons, as the spikes of oil prices have always been heavily influenced by politics and wars. Just go back to 1973, where the oil prices increased significantly due to the Yom Kippur war, and the embargo from Arab oil producers. In Great Britain this eventually resulted in the fall of the UK government.

The idea that 'data is the new oil' is to a large extent correct. There are many similarities, though I do not think that any government will ever fall over this topic. The data topic has been deeply ingrained and influenced in our politics, big tech giants have been given significant fines for 'abuse' and presidential candidate Andrew Yang even made this a key part of his campaign.

Oh how I would love to have had voting rights that year.

Another person who is using her influence in a very valuable way is Brittany Kaiser who founded the Own Your Data Foundation , I would definitely recommend giving her a 'follow' and check what her foundation does. I was lucky enough to have a few meetings with her, back in my Elastos DAO days. There are many more people who have helped me shape my vision of what I would like to see in future data economies, and I thank you all for that.

En route to participative data economies

The idea of a data economy really is nothing new, however data is (perhaps like oil) controlled and monetised by a select few giants. Of course these tech giants do everything they can to remain in control over the data, harvest more data and remain key players in the data economy. After all, big data is big money.

Interestingly, the political, societal and technological developments are opening up the data economy (or rather data economies) to a much larger group of businesses and people. It is actually already possible to enter the data-economy and get paid for the use of your data, and this new opportunity has gained a lot of interest recently.

In my view, the biggest drivers of the change towards participative and open data economies do not come top-down, in fact the most important driver is YOU! The businesses that want to enter the data economy, and the people who want to benefit from data sharing.

There has been an influx of businesses and their ecosystems that are trying to find ways to enter these data economies. Their interest is in how to get access to high-quality data, how large data sets can be combined to gain better insights and more recently, how they can train their AI better. This requires a strong infrastructure, after all, who would not want to tap into an economy that is expected to grow in value to $7t by 2027?

This has been a key topic that we have been working on for over two years, and we built the infrastructure needed to open doors to the new data economies for anyone.

I will end with a short explainer on how we do it, but first!

Data economy or data economies

In my view, it is much easier to talk about data economies versus one data economy. The reason we can talk about "the data economy" today, is that there are only a few players that really make up the whole market, therefore it is still pretty easy to throw everything into one category. However with more of you joining the data economy, new categories of interest appear, and ideally these categories consist of 'consortiums' where data sharing and monetisation (if you want) are relevant. Let me give you two topical areas.

Universities

Our conversations with leading professors in the Netherlands show that there is a great need (and actual requirement) for data sharing. However that is easier said than done. There are challenges in data-quality, privacy and different formats in which data is offered (amongst others). What if there was an easy way to deal with these challenges to allow Universities to work on data-sets together, in real time, and power more and better research that way?

One area that, at least in Europe, has remained unexplored is what else can be done with data gathered from Universities. We can safely say that this data is of high quality, as there are already so many checks-and-balances in play naturally. We also know that data between universities should be available 'for free', that is part of the way that industry works. However, what if there was a way for those Universities that contribute to data-sets to actually commercialise it? What if you could 'lease' access to that data to businesses, and use that income to fund new research?

Researchers would love that, as they will be able to continue to fund more research. Businesses would love that, as they will be able to get access to the best data. Governments would love that, as the wider societal impact grows. And I would love that as it fits my data-narrative perfectly.

Agricultural consortia

This is a new area for me, however data driven agriculture is nothing new to the experts. Especially around the impact of climate change on soil and plants, the horrible mistakes made in monoculture, and the use of the wrong fertilisers (and pesticides). The need for data has increased significantly, from satellite imagery to soil data. This data can then be used as a base for the much needed transition to sustainable agriculture.

There are many farmers globally that are now experimenting with different ways of regenerative agriculture, biochar incentives, satellite imagery, laboratories that test quality of plants and soil etcetera. An ecosystem of farmers, start-ups and large businesses has grown around this very topic (and I am not even adding carbon offsetting or insetting).

This means that another potential economy is growing around agricultural data. We know that a lot of data is being generated, and we know that there are buyers of that data for commercial purposes (grow better seeds, offer the right seeds to micro-climates etc.). Even Universities are willing to pay for data, as long as that means a time-benefit (so they do not need to gather that data themselves, and spend a lot of $ on that).

My point is, that next to a 'university data economy', we might also soon see the rise of the 'agricultural data economy'. Hence we will see many 'data economies'.

The AI data economy

A topic that deserves a whole separate newsletter, I suppose. The rise of AI has resulted in a whole new need for data. Newspapers already call it the "AI data wars" as AI companies are franticly searching for data, and are very much willing to pay good $ for that.

So what is the deal? Well, LLMs have been trained on content. Anything that is publicly (or behind the paywalls of tech giants) available can be used to train AIs that feel or sound smart. Ask ChatGPT (or any other GPT) a question, and the quality of the answer is dictated by the content it is trained on. So is there not enough content? Well, I believe that there is more than enough conversational data out there, though language naturally evolves and so should AI.

The problem is in the lack of structured data, ask ChatGPT to do market predictions, weather predictions or whatever predictions and if it gives you an answer, it 'hallucinates' most of it. AI has not been trained on real data, on structured data, and consequently the use of the AI remains limited.

So what if an AI company aimed at biotech gets paid access to data from Universities? Well, then that means that their AI can be trained on that data, and with that whole new opportunities arise as new insights can be found much faster.

Keeping my promise

At Nuklai we take on a new approach to data economies and the Nuklai ecosystem is growing rapidly because of that. We started by lowering the main entry barriers to data economies for you, so that you can focus on getting the most out of (your) data. Next to that, we see that consortiums (perhaps such as consortiums built around AI, Agricultural data, Universities etc.) need a little bit more around data access management and accounting, so we built the tools needed for these consortiums to flourish.

Some highlights for consortiums:

• Data can remain on your servers, you remain the owner.
• Infrastructure is decentralised, meaning that the power is with everyone in the consortium and not with one single entity. This solves the often occurring 'trust' problem.
• Usage can be tracked and data access can be managed. This leads to a whole lot of different benefits.

Other highlights relevant to every single user (data publisher or data consumer):

• Anyone can add to the quality of meta-data and contributions are valued (you receive a fair share of rewards in micropayments for that work).
• Multiple people/organizations can contribute to shared data-sets making them more valuable.
• Sensitive information can easily be filtered out.
• Data sets are standardised.
• Publishers get access to tools for data-control (so you decide who gets access and who does not).
• Easy and transparent payment and access models can be applied (pay per use, subscription models).
• Businesses benefit from tools to drastically reduce costs on the end of the publisher and data consumer.
• Use visual data query (so no-code).
• Combine data-sets to get deeper insights.

Interested in entering the data economy? Feel free to connect with me and I am happy to show you around and help you get prepared for the opportunities that data economies have to offer you!