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How you can make money selling your data

Marlene Ronstedt - 00:00:06:

We want to create new ways for users so that they can actually own their data, sell their data if they want to, and create new and exciting data sets, and also tap into data sources that have been completely untapped so far.

Didier Borel - 00:00:22:

Welcome to The Swiss Road to Crypto Podcast. I seek out the brightest minds in crypto, mainly in Switzerland, but also from around the world. I seek out people that I think are right and are doing something innovative and interesting. They might be well known or below the radar screen, but they have a special insight. Through these interviews, you will hopefully gain an insight that is not obvious today of what the future will bring. Unlike in Web Two, where the winner takes all, we want users, builders, and the Data Union DAO collectively to win by empowering people to earn revenue from their data. We want the people to own their data, and we want to set a new standard for best practices. That sentence comes from the Data Union DAO. DAO meaning decentralized, autonomous organization. And today I'm speaking to one of the cofounder, Marlene Ronstedt. Data Union DAO is an offshoot that came from streamer and I previously did a podcast with the CEO of Streamr, Henry Pikhala, and you. Can find that episode in your favorite podcast player. We will discuss what the unions are and how you can benefit from them, and much more.

Didier Borel - 00:01:29:

But before we get started, a word from the sponsors who make this show possible. First up, the script. Are you interested in having your own podcast but don't know how to get started? The idea of editing your own audio files intimidates you. I use the Descript software to edit this podcast and I highly recommend it. It's easy to use, much easier than any other editing software I know. You can record directly on your PC or Mac or on another device and then import the files. It also produces a transcript of your audio files. Best of all, they have an overdub function. That means that you can type in text, and your voice generated by the program will read the text. So when you need to add in a word or sentence to an audio file that you forgot to say during the recording, you can use the overdub function to insert it afterwards. I highly recommend the Pro version, which is what I use, and if you pay annually, it costs $288 a year. I really think it's worth it. Use the link in the show notes to connect to the script and help support this podcast. Next up, Shift Crypto. Are you looking for a hardware wallet to store your bitcoin or other crypto assets? Consider BitBox made by Shift Crypto. They are based in Switzerland and have been very well audited. The CEO, Douglas Bakkum, was on this podcast, and you can find that episode in the same place you found this episode. The other co-founder, Johannes Schnelli, was a Bitcoin Core developer and submitted his first line of code to Bitcoin Core in 2013. Also, if you like cool design, this product has the coolest design of all hardware wallets I know. Use the link in the show notes to get started and to help support this podcast. And finally, Braintrust. Are you a software engineer, UI designer, content manager, content marketer, and would like to work independently as a freelancer and using privately held platforms like Fiverr or Upwork take much too much of a commission? Braintrust has replaced the middleman by code. And the amount of take home pay you get on the Braintrust platform is 100% of what you build. Other fields of work are being added continuously to the Braintrust platform as well, so check them out to see if they have a job for you. On top of that, on Braintrust, you can make money by referring other people to the platform as well. Look at the two episodes I did with Adam Jackson and your favorite podcast player. Adam Jackson is a cofounder and CEO and find out more about how Brain Trust works. Click on the show notes to get started and help support this podcast.

Didier Borel - 00:03:58:

Welcome, Marlene.

Marlene Ronstedt - 00:04:00:

Thank you so much for having me here.

Didier Borel - 00:04:02:

So can you tell us what is the purpose of a Data Union?

Marlene Ronstedt - 00:04:05:

Yeah, of course. So a Data Union is a way for people to crowdsource their own data together with others and then also to crowd sell that data. So right now, if we look at Web Two, data is being monetized every day from probably all of us, but we don't have any influence on how our data is being monetized and by joining a Data Union, we want to create new ways for users so that they can actually own their data, sell their data if they want to, and create new and exciting data sets and also tap into data sources that have been completely untapped so far. So, for example, in the realm of medical data, for instance, there's a lot of untapped data. But yeah, in general, a Data Union is basically a way for people to crowdsource their data and then to crowd sell that data.

Didier Borel - 00:04:59:

Right. That's a clear deflation. And can you tell us how it's different than Streamr? I think streamer is a data transmission network and backbone and Data Unions are cohorts of similar types of data. Is that correct?

Marlene Ronstedt - 00:05:10:

Yes. So basically what the big distinction here is that we are using the Streamr network as our data transportation layer, and that works together in tandem with Gnosis, which is an Ethereum L2 chain. So a blockchain that is on top of Ethereum, and it's also using Polygon, which is another L2 chain, also on top of Ethereum for the financial aspects of the data, for the payment rails, and the data itself is being streamed on Streamr. And what the Data Union DAO does is basically that we are providing a toolbox for developers or for entrepreneurs who want to create their own Data Unions. So if you would want to build a Data Union from scratch, it would be quite hard to do that. You would have to find something either for storage or for data transportation. You would have to find a solution for the smart contract. You would have to optimize the smart contract for distributing payments to all your members. That would all have to be optimized for gas costs. And usually that is quite tricky to optimize it for gas costs because usually the costs are high if you're talking about sending money or any kind of tokens to millions of members. So we basically have this out of the box toolbox that we're offering to developers and to builders and they can use that. And that is a service of the Data Union DAO, whereas Streamr, on the other hand side, is providing one of the puzzle pieces and one of the underlying infrastructure parts to the technology we are offering.

Didier Borel - 00:06:52:

Great, thank you. Who can participate? Is it like individuals? I mean, later when I want to sell my data, in other words, put my data in a cohort with a lot of other people benefit from my data, who participates? Is it individuals? Is it companies? And if it's an individual, how nodes. He or she participates? Does he download an app or how does that work?

Marlene Ronstedt - 00:07:16:

Yeah, so how that works is you can think of it as a B2B2C structure. So an individual cannot so it's like business to business to customer. So an individual cannot directly participate in what we're offering because we're more like you can kind of think of us as a SAS company with a blockchain twist, so to say. And then if an individual wants to join, they have to join the individual Data Unions that are being built with our technology. And for that indeed, they can just download an app where they can then join a different Data Union like the one they want to join. They don't have to join all of them and then they can start monetizing that respective data. So, for example, the biggest Data Union that we have to date is called Swash and that is a browser plug in that works on all the major browsers. So if you're using Chrome or Brave browser, you can just download that and that it is being added to your browser and then you can start monetizing your browsing history. So I think especially for the people who are using Chrome where all the data is being monetised by Google already, it doesn't make a big difference in my opinion, whether your data is already being monetized or you might just also monetize it yourself by using Swash. And that really just takes a couple of seconds to install that and then you're ready to go, basically. Then there is another Data Union. I have only recently started trying that one because I don't have my own car. But it's basically a Data Union for cars. It's called and that one is an app, but they also provide a hardware device. If you're interested in using the hardware device, you have to get on a waitlist because they're completely sold out, which is great, I think, but otherwise they offer an app, you download that one. And then if you have a Tesla or an EV or any kind of more advanced fancy car, then you can connect that with the app and then you can start monetizing a lot of the metrics the car is generating, whether that is sensory data or battery life or location data of your car. And you can choose different categories you wish to monetize in that realm. And then actually with Gimme, you can make a fair amount of money in comparison to Swash you get like a couple of cents, I would say, per week, probably. So right now the money you get is not really worth it. You're just joining this great, interesting experiment. But in the case of Demo, you can make between five and, $10 per month or what? Per month?

Didier Borel - 00:09:52:

Exactly. And to what extent is the data going to be made anonymous?

Marlene Ronstedt - 00:09:56:

Anonymous, so that really depends on the individual project. But in the case of Demo, it is fully anonymous. So it's not connected with your name or anything. It is your car that it is connected to. So there could be a way how you could then trace that back to you. But basically what is more interesting when we gather the data or when the data is being gathered is really sort of to spot the pattern in the behavior of several thousands of participants. And it's not so much about like alright? DGA or me went to this place, and bought, that kind of thing. That's not interesting. It's more about the pattern, what thousands of people are using. And the data is being encrypted at the source. So that means the data is being transported in a way that it cannot be intercepted. So any third parties that would try to get to the data or hack the data would have a hard time because it is being encrypted at the source. And, then only those who have purchased access to the data have also the ability to look at it.

Didier Borel - 00:11:03:

Great. And you mentioned before we started recording some other data categories that you were considering that were interesting to you. You've mentioned the cars, you mentioned the browsing history. You have other categories.

Marlene Ronstedt - 00:11:15:

Yeah. What I think is another really interesting use case is for health data, because health data is being generated by a lot of people, either through fitness apps, fitness trackers, wearables, but also within the realm of like, medicine. If you're going to a hospital and you're getting a treatment there or something like that, and all these kind of categories would make for really great use cases for Data Unions. One problem with health data is that at least in the European Union, it's heavily regulated. So even as an individual right now, you are legally not allowed to sell your own medical data. I think that might also depend on whether that is medical data from a hospital or whether that is a step counter. I think a step counter would probably not fall under medical data within that realm or that legal definition. But it's definitely an interesting challenge to look at that because if you consider like, what could happen if we could share all our medical history, I think for research there will be a lot of interesting kind of patterns that are becoming visible within that. And also, I guess if someone has rare disease or anything that is being treated and could share that beyond with researchers that are not only part directly in treating you, but you could kind of share that kind of medical history worldwide, I think that would be very beneficial for the greater good of humanity. And yeah, it's still a bit tricky as that legally to circumvent these barriers, but I'm very excited to see these kind of Data Unions popping up. And I think that one is a great use case of data that has been entirely untapped so far. There is not that much monetization going on in that field. And yeah, I think there is a great potential there.

Didier Borel - 00:13:09:

Great. Thank your and another question is why didn't you just develop a SAS platform either for builders, for the end client, customer, individually? I mean, can you explain a little bit what your thinking process was to develop instead of yeah, sure, tools for builders?

Marlene Ronstedt - 00:13:28:

Yeah, that's a great question, actually, because I think how I usually describe it is that we're a SAS platform, with a crypto twist. I think one of the reasons why we went down rather this unconventional route was because the people we're working with and the builders that are using so far our technology are all coming from crypto. They're all crypto native, and for them it's a lot easier. I mean, they're already in this crypto environment. They're used to certain cultural norms, so to say. They're used to the fact that you have a Discord instead of some kind of email contact form, for example, if you want to get in touch with people, or they're used to we meet these people at conferences, we are on a much more friendlier asics with them.

Didier Borel - 00:14:17:

So these people, you mean the developers?

Marlene Ronstedt - 00:14:20:

Yes, exactly. So I think it's a cultural difference, whereas I think if it was a SAS platform, it would be a lot more streamlined. And I guess maybe within the next two or three years I could see it becoming more like that because right now we're trying to fundraise and we're building out the product. So we're really still in the infancy of the product and I could very much see it that maybe in a couple of years it is going to turn more into like what you would be calling a fast platform. Whereas right now I think the focus is quite heavy also on kind of this cultural idea of what Web3 and what crypto is. And I think the other part is because we're called a DAO. So DAO as you did mentioned earlier, means decentralized autonomous organization. And that is kind of our ambition to turn ourselves eventually into a doubt. We're not a doubt right now because that would mean that there are different models of how DAO could be organized. And like different emphasis you could be putting there. But basically what it means is that it's this Internet LLC. So it's a company that is exclusively registered online, so to say it's actually just registered on chain and not with a specific jurisdiction and then all the micropayments to its employees are just being made in crypto. And then some DAOs could have sort of a voting mechanism where participants can then use their tokens to vote on the trajectory of the DOW. But some these could also be more like a CEO DAO Benevolent Dictatorship dial where you just have sort of the approach you would have in a traditional company where someone is steering the group and making very clear decisions. We don't know quite yet in which direction your did is headed. I think for us it's important to just establish really strong foundations, kind of set everything up and then think more about how we can turn ourselves into a DOW=\- and also how that could relate to being a sales platform. Because I think if you want to make it easy for people to use your product. It of course makes sense to get some inflation from how Web Two applications and how Web Two platforms are working because it's still a lot easier to just look at Web Two and be like all right. I'm just going to use AWS and everything is being taken care of me and I can pay with my credit card here and I don't have to bother with like paywalling MetaMask and using some tokens I have never heard of. So we want to make it really easy for people to join, but at the same time we also want to make sure that these possibilities that Web3 has given us that we not fully discard them. And yeah, it's going to be an interesting journey to SEC where exactly we will end up eventually and where the middle ground for all of that is. Yeah, I think to that I think personally rather that Web3 is kind of the ambition or the vision. Web Two is where we are mostly now and somewhere in between. Web 2.5 is probably where we are going to be ending up at in a couple of years.

Didier Borel - 00:17:41:

That's an interesting statement. Okay, thank you. How long have you existed? I mean, did you start about a year now?

Marlene Ronstedt - 00:17:50:

Yeah, because as you have mentioned before, we are spin off from Streamr. And Streamr started as early as 2019 to develop the Data Union technology and the Data Union framework. And that is also when the first Data Union was accepted. That is Swash that I had mentioned earlier, the browser plugin where you can monetize your browsing history. And so in that regard, it started quite early. But of course, Streamr has a different focus, which is establishing and building this Streamr network for real time data transportation. And they never had the ambition to build out this Data Union framework, even though the team was always very passionate about it and thought that it would be a great idea, but it just didn't fit into the overall story we're trying to tell a Streamr. So eventually we decided it would make a lot more sense to roll this out as a separate entity and whether it comes to marketing and communications, but also when it comes to the different relationships we have with our builders customers, we can then emphasize a lot more on the core product we're offering, which is the Data Union framework and for Streamr, the network. Yeah, and then we decided last year to roll that out as a separate entity. And then in the beginning of this year, we took things a bit more serious and set up and launched the website, incorporated the company back in April, and yes, now we're a separate entity, basically.

Didier Borel - 00:19:29:

Okay, great. Because my next question was what Data Unions have worked so far? The best? So it seems to be the browsing from Swash and the driving one with Demo because those are maybe like the two most apparent and obvious use cases. CLN you say anything else about other types of Data Unions that have worked, or is it still too early in the two months that have worked? The best of those two?

Marlene Ronstedt - 00:19:54:

Yeah, sure. So I think another one that is quite interesting is called Unbanked. So that is Unbanx with an X at the end and then me. And basically that one is unfortunately it's only available right now in the UK, but I hope they're going to be rolling that out all over Europe in the next year. And if you're joining Unbanked, then you can connect that with your bank account and that leverages the Open Banking API Act, which means that you can then as a user, start monetizing your banking data. And what's super interesting about that one is that the banks already have that data, but nonetheless, they're really interested in buying that data because it has been enriched with user consent, whereas in normal banking, the banks wouldn't have these kind of permissions to look at your data that closely. And if you're joining Unbanked, then you can start monetizing your banking data. And you're getting paid £10 a month for that one. And they're busy right now. The team is busy right now with their launch for later this year, probably around September. I think it's also an interesting social experiment to see who is willing to monetize our banking data and who's not and where this is all headed. So I think that's a very interesting and exciting one. Apart from unbanked, we also have one that they haven't fully officially launched yet. But basically it's a Netflix Data Union. So you can start monetizing with that when you're Netflix data. And that basically means that when you are watching Netflix, it's a bit like Nielsen what they have in the US, which is this box that you install on your TV, and then it kind of starts gathering data about what you're watching and then tries to get sort of like a US average from what people are watching if you're Nielsen family. So to say you're like one of the chosen ones that can monetize their TV viewing habits. And with this Netflix Data Union, basically people can start monetizing their own Netflix viewing habits. And I think that one could become quite popular because I think what you're watching on Netflix is anyways already something that you share a lot with your friends, whether it's like on social media when you're posting on this new show. Oh, God, it's so crazy. I love it or whatever. And I think most people don't have much to hide when it comes to what they're watching on Netflix. So I think that one could become a really interesting Data Union project.

Didier Borel - 00:22:29:

Is there some place or site where the average consumer can go find the available Data Unions? Like, I wasn't aware that there could be one on monetizing your Netflix viewing habits. Where would I become aware of that?

Marlene Ronstedt - 00:22:44:

That's a good question. So right now that will be actually our website, which is So Data Unions with an S the end. And and there. We have an overview of the most active ones right now. But in the long run, our goal is to build that out and to really showcase the entire ecosystem on our website and to eventually maybe even create something like our own app, where people could then just tap and join these different Data Unions instead the halving to discover them. Because I think one really interesting aspect is the cross pollination. And right now we're driving the cross pollination mostly just through socials and through marketing channels. But I think if we would have an application, that would make the cross pollination a lot easier, right? Because I think someone who would sell their browsing data with Swash would probably be very interested in sharing their Netflix data, or they would be very interested in sharing their car's data. And that's kind of the ecosystem we also then want to enable for the end user.

Didier Borel - 00:23:54:

Great. Thank you very much. Polygon. So you're doing an integration with Polygon. Maybe you want to just quickly define what Polygon is and then describe your integration with them.

Marlene Ronstedt - 00:24:04:

Yeah, sure. So Polygon is what is being considered an L2. So it's a layer two solution for Ethereum and because Ethereum has become quite costly to use because of the gas costs and also because the chain is getting kind of crowded, so to say, because a lot of people want to deploy on Ethereum and therefore Ethereum usage has become a lot more expensive. And then there are these layer two solutions for Ethereum that make it cheaper if you want to use Ethereum, but you might not need the level of scrutiny and security that Ethereum offers. So therefore these blockchains are these L two solutions are a lot cheaper, also often faster. And yeah, considerably cheaper. I think that's probably the main aspect and Polygon is probably one of the biggest ones in the ecosystem of Ethereum. And we have decided to use Polygon for the deployment of the smart contracts and. I think that's especially smart contracts for a Data Union. It can still be deployed on Ethereum, but now it can also be deployed on Polygon. And basically what that means is if you're a developer and you just want to try out something, you want to play around with it. You don't have the ambition yet to build this big Data Union project, but you're just looking at it for the first time. And if you can then use Polygon to deploy this, you're going to pay maybe like a dollar or a couple of cents to do that, to deploy a smart contract Ethereum. Whereas in the Ethereum ecosystem, if gas prices are right, you might be paying as much as $200 for doing this. And that's usually not what people do if they just want to try out something. So for us, the main reason is we need to make it easier for people to play around with the framework also to organize hackathons where people can then try out the framework and see what they can build with it. And yeah, in addition to that, we also have a partnership with the Polygon DAO for grants programs, which is going to start later this year, which basically means that if somebody is building on Polygon and is building with our technology, then we can offer them some kind of a match funding brand where they would be getting ten k from us and ten k from Polygon. And. So we kind of want to have this cross pollination of the ecosystems and we want to make it easier for builders to get started with our technology.

Didier Borel - 00:26:38:

Basically continuation at that point. I think the Data Union wants to take a protocol tax. Correct? What is it and what's the point there?

Marlene Ronstedt - 00:26:46:

Yeah, so the idea there is, as I had just mentioned, we're giving out these brands to builders and to project and the idea of the protocol tax is that we collect 1% of the revenue that is flowing through our entire ecosystem. And that protocol tax is then being used for our grants program so that if there are new builders that are coming into the ecosystem that have ideas for a new Data Union, then we CLN tap into this treasury pool to give them a grant so they can build their ideas. And the idea here is that they will bring in new users which will then subsequently also join existing Data Unions. So once again, this kind of cross explanation of the ecosystem that we want to create here. So that is one of the reasons for the 1% protocol fee. Another reason for it, and we're still.

Didier Borel - 00:27:37:

Exploring this, who's paying the protocol fee? It's the person who's buying the data from the Data Union.

Marlene Ronstedt - 00:27:42:

Yeah, exactly. That's how it works. So if somebody buys the cash API, then automatically 1% of that purchase goes back into our ecosystem. One of the other ideas we're exploring right now is to create a buyback and burn mechanism for our future token. So that would mean that when we launched the token, that 1% of these protocol fees are going to be used to burn the token, which would mean to decrease the token supply. And therefore we could create some interesting synergies to kind of indirectly give back some of the value that we have created through the token economy. But yeah, we're still in talks with our lawyers with regards to that one, whether we can actually introduce this by back hard forks mechanism, because it obviously does have some difficulties when it comes to the legal definition of what the token is. And we want to make sure that this is all in the interest of our users.

Didier Borel - 00:28:43:

Okay, great. So let's finish it up with some rapid fire questions. Most important book you ever read?

Marlene Ronstedt - 00:28:49:

Oh, yeah, I saw that question earlier about the most important book. It's such a tricky one. I really enjoy Japanese literature of all these, but I wouldn't want to settle on a specific author, to be honest. I would say the most important book I have read this year is probably The Order of Time from Carlo Rubelli. He's a physics professor and basically has written this very poetic book on what time actually is or what time is actually not, and kind of defines what time means on a molecular level and on an atomic level, which is very interesting to see. And I really enjoyed reading that book. I read it basically just within one sitting during a long flight to the US. And. Yeah, that was probably my favorite book this year. Overall, I don't have a favorite book, actually. I think there are too many good books out there.

Didier Borel - 00:29:46:

Yeah, I agree. Somebody you admire. And why do you admire them?

Marlene Ronstedt - 00:29:51:

I would probably say my dad, actually, I think my dad, he has quite an. Interesting background. He was born during World War II and then spent the first five years of his life as a refugee, and then from there really worked his way up. He had two businesses. First, he had a fashion business, then he had a furniture business that were really highly successful. He was making a lot more money than I'm making right now. At my age, especially. The second company was really big with over 150 employees. And I really admire how he worked his way out there and how he was very focused in his mission and how he is still I mean, he's retired now, and he is still very passionate about, like, being active. And doing stuff, and he doesn't complain, he just does stuff.

Didier Borel - 00:30:48:

I hope he listens to podcasts so he can listen to this one. He'd be very happy to hear that, I'm sure. Okay. And this might be him as well. The best advice you ever got? And who gave it to you?

Marlene Ronstedt - 00:31:00:

Yeah, I think that's an interesting one. I don't have a specific piece of advice I have received, which I really enjoyed, but I started actually talking with a business coach last year, and she's been incredibly helpful in kind of helping me to discover what I want, the direction I want to work in, what I want to do. And there wasn't, like, a specific piece of advice she gave me, but it was more about, like, self realization, and she kind of pushed me in the right direction to do that.

Didier Borel - 00:31:35:

Okay, finally, favorite movies?

Marlene Ronstedt - 00:31:39:

Favorite movies probably enter the void from gustan Away. He's a French director.

Didier Borel - 00:31:48:

Wait a second. I think I saw that. What's it about? Again.

Marlene Ronstedt - 00:31:52:

It'S quite an intense one. It takes place in Tokyo, and it's about looking at the idea of rebirth in combination with taking DMT, which is this psychedelic drug, and it's super trippy movie. It doesn't have a single cut, so basically the camera just follows the main character around Tokyo and everything just morphs into each other. It's a three hour long movie. It's quite intense in terms of visuals, and content and story. But I really like it. I watched it as a teenager for the fiat time, and I think ever since, it's been my favorite movie.

Didier Borel - 00:32:26:

Great. Thank you very much. Marlin. So, if people want to get in contact with you or discover more about. Data Unions, where should we send them.

Marlene Ronstedt - 00:32:34:

So they can learn more about Data Unions on the Data Union website, which is www.Data So Data Unions was an s at the end. That's very important. And they can also find out more on Twitter if they follow us at Data Unions also with an S at the end. And then they can find out more about me and follow me on Twitter at Ronstedt. That's Ronstedt. Yeah, that's basically it. Thank you so much.

Didier Borel - 00:33:05:

Okay, thanks. So I'll put those links in the show notes for people and it was a pleasure to speak to you. Marlene.

Marlene Ronstedt - 00:33:11:

Thank you very much. Thank you so much for having me. Bye.

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