My Private key was compromised.

This is where I originally posted all my research & investment thesis:

Hence, I’m re-uploading all my writings to this account.

Please subscribe to this new account and support me in my research.

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This research was originally posted on August 12, 2022.

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EXECUTIVE SUMMARY

Data is the new oil: Today, we are generating more data than ever. And it's stored forever. Data is powering the next industrial revolution. The growth in data velocity, volume, and variety requires innovative business models to generate value from data, from smart data. Data management is a contractual right and not a natural property. One company’s action of selling or sharing email addresses or logs of my online activity to generate profit undermines the value of the data I willingly provide to this company. Instead, 1) let me own the data I generate and allow companies to monetize only use of that data, or 2) share the profits that my data set generates. Data users are modern-day cavemen. They are in charge of making discoveries. But they tend to manage data in a cold fashion.

Why is it essential to collect & understand data? Most community interactions and engagement with the content being shared or consumed or products/services purchased online give us a premonition of what's about to come. Our online activity on the everyday web matters. Its immense, weaponized reach and guiding principles pave the way for the importance of privacy as a fundamental human right.

But, everything is siloed. On the front, what is advertised as Artificial Intelligence companies are just companies mining and harvesting your data to target you. Centralized (Siloed) data 1) Limits our potential to act on it from everyone’s point of view, and 2) Builds a network of influence rather than actionable plans. In web2, no one cares what you can do; everyone cares what you can do for them. In web3, everyone cares what you can do for yourself and others.

We have to build the reality we want. The dominance of the tech giants over user data, and the oligopoly of the duopoly giants over user data, present a unique set of problems. This data allows these companies to be increasingly powerful and socially influential, and this technology wields disproportionate influence over society. The fragmented nature of siloed data creates data deficits that contribute to the following gaps: 1) Data gap, 2) Access gap, 3) Governance gap, and 4) Utility gap.

The Paradox of data that we face today is that 1) We want our engagement on the internet to be data-informed, where we want to make our decisions ourselves without the help of any third party, and 2) Still, we as individuals always need to be told what to do, which forces us to follow data-driven steps, which we obviously do not control but follow.

Building the decentralized data ecosystem (DDE). The personal data of hundreds of millions of people has been repeatedly stolen and often sold. Furthermore, forecasts show that the amount of data generated will outstrip the installed data storage capacity growth between 2021 and 2025. The main question is: How can we build a system that makes data actionable, reliable, and accessible to all? I further discuss the three pillars that will possibly accelerate the need for a DDE. Decentralizing data matters because the current data companies rely on where things can go wrong.

So, how do we break these siloes? We control the demand (folks needing loads of data) and supply (folks with access to lots of data) and build a decentralized infrastructure that ensembles two critical aspects of data sharing: 1) Technology to store and tokenize data sets and 2) Open marketplace for buyers and sellers to interact. Alvin Roth put forward a framework that identified several requirements that would assist in building decentralized data exchange. 1) Markets must be efficient & liquid, 2) Markets must have minimal congestion in terms of transactions happening, 3) Markets need to be perceived as safe, and 4) Markets need to respond to social norms and comply with local regulations.

I further map out the working of a hypothetical data marketplace, DataX, that builds a system of exchange in which individuals control how their data (and identity) is used in open, secure environments with the underlying DTX utility token.

Further, I categorize the different possibilities of structures a platform or protocol such as DataX could assume: 1) one-to-one, 2) one-to-many, 3) many-to-one, and 4) many-to-many. The focus of these structures should be a trade-off between provenance (representing control and quality) and liquidity.

Who benefits from decentralizing data? One of the many concepts I genuinely advocate for is the widespread adoption of web3 technology by web2 natives. Second, I believe that Tokenization is the only economic activity that can help everyone adopt web3 technology. The focus of decentralizing data should be on 1) increasing credibility, 2) enhancing governance, and 3) the provenance part of the origination. Democratizing data will eventually create brand-new communication, commerce, and social interaction systems.

Perceived risks of sharing data. There are five risks of decentralizing data: 1) Fragile data security systems within the developer community, 2) Skeptical legal and regulatory framework worldwide, 3) Damage to customer or shareholder relationships or public image, 4) Loss of competitive advantage, and 5) Technical and Operational barriers.

But, there’s significant economic value in decentralizing data. Data is a valuable asset, and capturing the value of data is an essential task for implementing the data revolution. One of the reasons why people were willing to give up their data is because they don’t know what to do with it themselves. As a result, the "data economy" has been dominated by a handful of prominent players, like Google, Meta, and Amazon. Once data becomes a property right, everything, including the derivatives, must be treated similarly. But today, data management is a contractual right rather than a natural property. The implication for data companies is massive. It will change the paradigm if we turn data from contract rights to property rights because we are the creators of our data. The value comes down to one additional layer— Identity. The ownership paradigm is explained with a case study of the P2E game Axie Infinity.

The tokenization of data sets will happen because of digital identity & legacy and will provide the roadmap for a broader collaborative business model. We want to digitize everything because it speaks to our identities. New, collaborative business models address individuals’ core needs and build trust – while enabling new business opportunities. New ecosystems are becoming increasingly important as society becomes more digitalized and the mobile internet becomes the dominant platform for interaction. This shift is reshaping industries from media to advertising and telecoms. These business models drive customer engagement, co-creation, social currency, transparency, and – most importantly – data.

Revenue & Engagement drivers for the new paradigm of data. Data, as it flows between people, devices, and the web, opens the door for innovative business models. Business strategies that ensure efficiencies, productivity, and increased transparency/distribution are full of potential for everyone because all parties benefit. Three areas drive these opportunities 1) Novel Data Pools: a case study of Airbnb, 2) Novel Partnership Models: a case study of F45 fitness, and 3) Enriched Product-Market Experiences: a case study on data, context, and trust of a hypothetical individual data marketplace.

User Data on-Demand (DoD): This is how we democratize access to data. Basically, user data is collected by a given company, turned into a data package and tokenized, and then delivered to other companies. Do you know how much data you have access to? Only 5% of users understand how much they can collect and analyze. This lack of knowledge about efficiency, scope, precision, and range of their data stands in our way as data is becoming ever more essential to life. User DoD brings efficiency, reduces costs, and creates a new internet of value.

Conclusion. The cry of 'for your data, for your freedom', has echoed through the web for the last 25 years. It was whispered as a promise by the first wave of internet pioneers. They were building the future in a certain way, making promises that could not be kept. The promises started to fade as greed and illusions took center stage. As we collectively understand, internet data is not the only thing that can be harnessed and shared for profit. With smartphones, dashcams, and drones, people collect valuable, real-time geographical information every day without any intention of profiting from it. This sort of information is valuable to everyone, from surveyors to researchers. However, I believe that significant progress and community growth require defining every participant's clear and compelling role in this ecosystem.

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DATA IS THE NEW OIL

Today, we are generating more data than ever. And it's stored forever.

Our digital lives leave behind a digital footprint creating massive amounts of data that identifies and tracks us. Data enables us to build better and more innovative models of internet-era applications. It is the new oil, yet we, who contribute most of it, are unaware of that treasure. Unfortunately, most service providers collect user data without disclosing the reason; meanwhile, users unconsciously barter their data in exchange for a free app or service.

Our data is being monetized and used against us while we are left with nothing. Still, there's no way you and I can figure out the intrinsic economic value of our data combined and utilized together. But, of course, there are instances where we don't realize the kind of data that is collected & tracked from us. So we are an essential misguided stakeholder of a $1T data analytics industry.

Data management is a contractual right and not a natural property. One company’s action of selling or sharing email addresses or logs of my online activity to generate profit undermines the value of the data I willingly provide to this company.

Instead, 1) let me own the data I generate and allow companies to monetize only use of that data, or 2) share the profits that my data set generates. Data users are modern-day cavemen. They are in charge of making discoveries. But they tend to manage data in a cold fashion.

Decentralizing data is the way to change how the world transmits and permanently stores value and information. Leveraging its embedded advantages of data security, transparency, and immutability, decentralized applications (dApps) are gaining traction in healthcare, government, banking, trade finance, real estate, diamond mining, law, and insurance, among others.

Hence, the amount of data generated and stored globally will continue to grow exponentially. For example, 90% of all generated data was generated in the last few years alone. This is an ample opportunity as large corporates seek new markets, and startups strive to disrupt established companies by adding value to their product or services. By 2025 there will be 75 billion IoT-connected devices with an estimated 200 zettabytes of data.

Public data initiatives are an example where alternative governance models could influence the emergence of public goods, such as distributed digital identities. For instance, Defi is an alternative architecture to secure and monetize data in a way that compensates individuals and communities.

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WHY IS IT ESSENTIAL TO COLLECT AND UNDERSTAND DATA?

Most community interactions and engagement with the content being shared or consumed or products/services purchased online give us a premonition of what's about to come. Web2 incumbents can use their collected siloed data against us. We have reached a point in the internet/web2 era where every interaction, engagement, or click can be monetized at scale. But it is one-sided. We have reached a saturation point.

Data influences every major part of our life. What we eat, where we go, which movies we watch, and who we criticize and vote for—all of it. The path forward is not to rely on a handful of companies that dictate what we should do and think.

Our online activity on the everyday web matters. It has immense, weaponized reach, which goes against the doctrine of humanity.

The guiding principles for the development, implementation, and governance of personal data should be based on:

1. The importance of privacy as a fundamental human right

2. The importance of individual data subject’s rights to privacy and control of personal data

3. Subjects have the right to access their personal data and obtain, correct, and delete it where required.

4. Consideration of disorder, disruption, and fragmentation.

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BUT, EVERYTHING IS SILOED

Anything that has to do with data is a data company. On the front, what is advertised as Artificial Intelligence companies are just companies mining and harvesting your data to target you. So every time you visit Google and FB, they’re studying you and making billions out of it. And this data is siloed. This is dangerous to society and our collective freedom as well.

Centralized (Siloed) data:

• Limits our potential to act on it from everyone’s point of view, and

• Builds a network of influence rather than actionable plans.

One of the common misconceptions that I believe are stalling the widespread adoption of the concept of decentralized data is that:

• First, many still believe data is abundant, but it is not. It is highly fragmented.

• Second, many activities involving our data are treated, shared, and monetized at ‘one-to-many’ marketplaces, where one entity provides data to many.

In web2, no one cares what you can do; everyone cares what you can do for them.

In web3, everyone cares what you can do for yourself and others.

Web2 companies arbitrage your data for a higher value. We’re data swindled. Suppose we genuinely want to build a decentralized data ecosystem.

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WE HAVE TO BUILD THE REALITY WE WANT

The dominance of the tech giants over user data, and the oligopoly of the duopoly giants over user data, present a unique set of problems. This data allows these companies to be increasingly powerful and socially influential, and this technology wields disproportionate influence over society.

Accessing data efficiently requires the visibility, accessibility, and control of data which, at first glance, seems nearly impossible. The fragmented nature of siloed data creates data deficits that contribute to the following gaps:

DATA GAP

Instances where development needs a significant amount of data to come up with great products/services, but at the moment, we don't have it.

This happens for two reasons when there are:

• No data on undocumented users for existing services

• Silos with a centralized data stream

ACCESS GAP

Instances where data exists but can't be accessed because it's too costly, complicated, unlawful, or siloed.

I think security or privacy is not as important as we usually think they are. Instead, I believe a better focus should be on what our data is used for and how it can be abused. Most services (especially by big companies and not small startups) seem to underestimate privacy, making it hard to find the data in the first place.

And the most significant gap I see is that when finding your data, no tools exist that you can use.

Why? A few reasons:

• Almost all companies do not publish their APIs. Instead, their data is scattered across multiple servers, which makes it extremely hard to access.

• There is no specification for a data flow or structure, and what is available often does not match.

• No tools exist which allow you to query all available services. However, even centralized services like your Twitter account do not allow you to query all public services, which leads me to believe that Twitter does not want you to find your tweets from another source.

But where can we go from here? How can we use data without getting all of our data audited by large companies?

GOVERNANCE GAP

There are instances where data exists, but the stakeholders are relatively immature and, therefore, not ready to negotiate standards, rules, and regulations that protect users from using their data by companies & national agencies.

USABILITY GAP

Instances where lots of data are available to smart people, but getting them entirely right is quite complex (even if you know historical data, and it is growing exponentially, it still can be hard to extrapolate).

For example,

1. If you make a new prediction on how much something will cost next week, it is quite tricky to compute the odds and calculate the return.

2. Domain expertise to guide the appropriate use of data and to enable users to locate data needles in data system haystacks is often missing. Additionally, the absence of communities of practice to serve as engines of learning, innovation, and diffusion is a challenge.

These gaps must be bridged to give decision-makers in every sector the tools to understand the impact of the policy and business decisions they make in a data-driven world.

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THE PARADOX OF DATA

As stakeholders of everything that contributes not only to the internet but the massive reserves of centralized data, we are confused and limited to the kind of benefits we want to be exposed to.

The paradox of data that we face today is that:

• We want our engagement on the internet to be data-informed, where we want to make our decisions ourselves without the help of any third party.

• Still, we as individuals always need to be told what to do, which forces us to follow data-driven steps, which we obviously do not control but follow.

If you find yourself in this paradox, what would you do?

• Being data-informed needs you to be data literate, and

• Being data-driven needs you to compromise on your data literacy

No matter which side of the paradox you face, the inefficiencies of the data economy for the greater good are skewed towards the few who control our data. The only change we need is control and incentivization.

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BUILDING THE DECENTRALIZED DATA ECOSYSTEM

The personal data of hundreds of millions of people has been repeatedly stolen and often sold. Furthermore, forecasts show that the amount of data generated will outstrip the installed data storage capacity growth between 2021 and 2025.

Also, every AI model, growth forecast, analyst, startup, industry incumbent, and who knows who else—needs data. The thing is: they use it for a myriad of purposes.

The main question is: How can we build a system that makes data actionable, reliable, and accessible to all?

Trust centralized entities and run the risk of your private data being leaked.

The criticisms around data manipulation by internet companies are very valid. They have gradually destroyed the internet and retained most of its power themselves.

Building a new data economy is the only way to reclaiming the only iteration of the web we should have had— a two-sided interactive platform & marketplace that evenly incentivizes participants for their contribution and engagement.

I am, without exception, vocal about decentralizing everything. Today, the idea is to reimagine how the monopolized data ecosystem works. We’ve seen one thing happen in one reality, one timeline. We know how things work in this space and now have a blueprint. So now we have the chance to build something new— A decentralized data ecosystem.

I believe the following three pillars will accelerate the need for and adoption of decentralized data:

1. Moderation of content

2. Participation by users

3. Monetization of engagement

To implement a governance standard across the three pillars of decentralizing data, the following aspects are essential to be upheld:

• Equitable and unbiased allocation of ownership, value, and command.

• Resist centralized monopolies.

• Comply with the regulations within geographies, and

• Be completely community-owned and operated.

Lastly, the underlying goal of decentralizing data exists to:

1. Build a community for users to engage

2. Categorize every action on any platform as data points

3. Build an infrastructure to curate data to build intelligent AI models

4. Reap the benefits to the community

Also, decentralizing data matters because the current data companies rely on where things can go wrong.

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SO, HOW DO WE BREAK THESE SILOES?

It’s simple, isn't it?

We control the demand (folks needing loads of data) and supply (folks with access to lots of data) and build a decentralized infrastructure that ensembles two critical aspects of data sharing:

1. Technology to store and tokenize data sets

2. Open marketplace for buyers and sellers to interact

Roth’s theory of market design identifies several requirements that are associated with efficient market operation, in other words, markets where prices consistently reflect all the available information. Economic efficiency thus implies that valuable resources are in their best uses.

• Firstly, as markets become more efficient, there is an increase in liquidity and new possibilities for sellers and buyers with an extended range of commercial partners. Put differently; a market is liquid when there is a sufficient pool of market participants willing to transact with one another. In markets for unique data that are valuable in highly specific contexts, a lack of liquidity or active backing by participants can be a significant factor leading to inefficiency.

• Secondly, while liquidity is a necessary precondition for an efficient market, popularity can also create “congestion” by slowing down transaction time and thus limiting participants’ alternatives. Speed is crucial for ensuring market efficiency, but markets should not let transactions run so fast that people cannot evaluate opportunities, thus limiting participants' access to other options.

• Third, the market needs to be perceived as “safe”. A safe market is one where information can be settled and prevent anyone from dipping their hands in it. It provides credible provenance information, creates a more or less equal playing field for all participants, reliable knowledge, and safety precautions that no one can access the data. Imagine that the marketplace has a function where users can block and report malpractice without breaching data protection rules.

• Finally, the marketplace needs to respect social norms. Resources obtained through a user-generated market may suffer from social and ethical standards, legislation, and user expectations. That's why consumers should see if and how companies can comply with the law to thrive and conveniently use their data. Large companies benefit when they can absorb the cost of managing and analyzing data, which are the core functions of any company in today’s world. It all starts and ends with the community.

Do we need to assemble pillars that will accelerate the need for decentralizing data? Yes, we do.

How can we do it efficiently?

Here’s how I visualize it: A Hypothetical Protocol

DataX ($DTX), the first platform for decentralized data exchange – opening the world of personal data to companies, DAOs, and anyone who needs it. Built on the Ethereum blockchain, data owners can certify, sell, share or license their information directly via their own personal controls (wallet, ID).

The DTX token will help facilitate the open exchange of data. By functioning as a unit of trade, DataX’s token helps foster an ecosystem of data sharing between data owners and applications. Data owners can cut out the middleman and directly connect themselves and their data to 3rd party applications and services, preferably APIs.

With blockchain technology, data owners will be empowered to control exactly what data gets collected, who receives it, and how much they receive in return. For developers, DataX’s blockchain-based, open-source platform will provide fast and easy access to individuals’ data, which is vital for building the next generation of apps.

With a blockchain-based profile system, DataX will build a system of exchange in which individuals control how their data (and identity) is used in open, secure environments.

Data ownership for those who created it. Freedom of usage of the data, without brokering or data collection.

A data marketplace structure canvas

Quadrillions of dollars of data are aggregated, anonymized, aggregated again, and made available to a broad spectrum of users by a multitude of businesses. The data is collected, de-identified and then sold to third-party data brokers who sell it to literally anyone, often without ever knowing the buyer's identity.

1. One-to-one marketplace: A two-way partnership involving two parties with negotiated terms of exchange, as Google and Acxiom exemplify.

2. One-to-many marketplace: A distribution marketplace characterized by standardized terms of exchange, such as data distributed through APIs.

3. Many-to-one marketplace: Characterized by data harvesting, where many sellers provide their data to a single buyer in exchange for services under terms of trade as recorded under the smart contract.

4. Many-to-many marketplace: Platforms upon which anybody (or at least a large number of registered users) can upload and maintain datasets and where access to and use of the data is regulated through varying licensing models handled via smart contracts.

The focus of the marketplace structures mentioned above should be a trade-off between provenance (representing control and quality) and liquidity.

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WHO BENEFITS FROM DECENTRALIZING DATA? EVERYONE.

We as humans are exposed to more data today than we had access to yesterday. The internet is compounding information daily, and at the end of the day, it’s all concentrated at data centers we know nothing about.

Transparency in data is the hardest part. Even harder is being able to articulate why decisions were made the way they were made. Decentralizing data is how we push ourselves out of the slavery of data monarchy and become truly free.

It makes your engagement valuable to people that don’t have access to a solution for a problem at parity.

One of the many concepts I genuinely advocate for is the widespread adoption of web3 technology by web2 natives. Second, I believe that Tokenization is the only economic activity that can help everyone adopt web3 technology.

The focus of decentralizing data should be towards:

1. increasing credibility,

2. enhancing governance and

3. the provenance part of the origination

Never again should it be possible to say ‘we didn’t know.’ No one should be invisible, and where the data comes from can be actively reflected in the tokenized identities and further onto the tokenized data. And if investors make mistakes with tokenized assets (tangible or intangible), they could spend more than they can afford.

Hence, it’s essential to know what made it to the market and what didn't.

This is the world we want – a world that counts.

Democratizing data will eventually create brand-new communication, commerce, and social interaction systems. We can apply this power to more significant problems, such as the climate crisis and inequality.

The network effects of each market are significant with data and more users/ community participating in the market, creating more trading, hype/storytelling around product launches, and enabling brands to develop customized, limited-edition products at premium prices and high sell-throughs. By improving the quantity and quality of data, the tokenized product or service will also have a higher valuation during its operating life.

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THERE ARE RISKS TO DECENTRALIZING DATA

How do we solve this problem?

• Integrate security recommendations into the existing schedules

• Promote affordable data security and vulnerability assessments of engagements between users and consumers

• Invest in affordable data security technologies, capacities, and policies

• Create safer, open-computing technology architectures

• Create affordable security audit, training, and compliance products

• Improve public, private, and hybrid IT risk management provisions

• Promoting cost-effective, scalable cyber security and privacy audits and policies for those entering strategic partnerships

• Embed security-coding solutions and policies into existing smart contracts

• Developing scalable, cross-blockchain smart contracts with secure data formats and workflows

• Develop secure, decentralized data exchange protocols

Skeptical legal and regulatory framework worldwide

I believe that the more developed a country, the more it focuses on reducing risk instead of leveraging the possibility of unexpected outcomes, hence the low use of innovative methods. Moreover, the perceived risks associated with sharing proprietary data are substantial, mainly because they are not easily measured. The generic concerns are that sharing data costs time, money, and personnel resources.

We can term this positive risk as Anticipatory Uncertainty.

It determines how developed countries differ from developing ones regarding strategic risks. Preferring to fight declining international demand, investment in R&D and capacity expansion as investments can be seen as anticipatory uncertainty.

Developing countries, however, focus on reducing perceived risks, usually through liberalization, freeing markets, and reducing barriers, and are seen as buyers. Moreover, a country with a high propensity towards anticipatory uncertainty will be an innovator, and a country with a lower inclination towards anticipatory uncertainty will be a buyer.

How do we solve this problem?

1. Establish an ongoing dialogue with industry, policy-makers, and civil society on the impact of robust data sharing

2. Support ongoing efforts to create, pilot, and scale standard agreements for cross-sector data sharing

3. Identify examples of scalable use of data for diverse solutions to users

4. Manage shared risks by transferring liabilities as a result of strategic partnerships

Damage to customer or shareholder relationships or public image

To engage with complexity, data providers and users are clearly essential. However, in the absence of a clear and agreed vision and strategies that facilitate alignment between multiple stakeholders, it is unclear where data providers and users fit. While many organizations will have single, simple questions, there are more significant risks associated with poor engagement.

The end user will often have a simple question: Why has this aspect of technology/culture/business process/organization affected me this strongly?

A root cause of this could be that technology/culture/business process & organization was simply not designed for the end-user.

How do we solve this problem?

• Create clear smart contract agreements that stipulate risks and responsibilities among stakeholders

• Ascertain data queries in strategic partnerships so that the insights distilled respect individuals’ privacy

• Adopt regulatory terms for access across administrations to support data flows and improve permitted interoperability with partnerships across borders

Loss of competitive advantage

Realizing the full benefits of the data revolution in web3 will require equal economic access to data. Competition must democratize data and the information attached to it. Without such equality, the data revolution remains fragmented and is susceptible to capture by a small number of players. Once captured, data providers cannot easily liberate the data.

In particular, all digital rights, including the right to own your data, are undermined without economic access to data. Without the economic incentive to decentralize data, the decentralization of the industry will be slow.

Data monetization is currently restricted to a few gateways and data providers, such as centralized exchanges and centralized brokerages.

These intermediaries have two main motivations:

1. End-users pay fees for access to these gateways, and

2. the intermediaries can monetize the access by running additional features on top of the existing protocols.

Studying these incentives, it becomes clear how centralized these monetization schemes are.

There are ways out, however. We need a back end for a decentralized data economy, a new protocol that allows on-demand access to data. Such a new protocol is key to a decentralized data economy.

How do we solve this problem?

• Identify and align clearly articulated use cases that demonstrate a compelling use case for pooling of shared data resources (discussed below)

• Operate with clear agreements in place which define intended uses

• Engage in research quantifying the “cost of not sharing” and the pro-competitive impact of co-management of data across market competitors.

Technical and Operational barriers

How do we solve this problem?

1. Improve transparency of operations, product releases, and disclosures through open APIs and signing nodes with “smart contracts”

2. Support open tools to reduce operating costs: “free” storage, processing, and network capacity.

3. Share and leverage underlying technical infrastructure for reduced operational costs

4. Share risk and costs & rewards from new data dApps

5. Devise new business models for both public and private sectors

6. Overcome technical and operational barriers:

   1. Make it easy to interface with a variety of databases.

   2. Make data virtualization technology in low-cost commodity hardware/software.

   3. Enable numerous application developers and entrepreneurs to make web3-enabled data accessible for all.

   4. Automate data sharing, computing, and communication.

   5. Enable data providers to safely and legally monetize their data.

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BUT, THERE’S SIGNIFICANT ECONOMIC VALUE IN DECENTRALIZING DATA

Data is a valuable asset, and capturing the value of data is an essential task for implementing the data revolution. One of the reasons why people were willing to give up their data is because they don’t know what to do with it themselves. As a result, the "data economy" has been dominated by a handful of prominent players, like Google, Meta, and Amazon.

For example, if we discovered oil in our backyard 500 years ago, we wouldn’t know what to do with it. We don't have the technology to extract anything out of it. But if some company were able to make something valuable, it would seem like a net benefit to give away the oil, regardless of the percentage of value we could receive, because the company was able to use the oil and get something out of it. Data is the same.

You can download your photos or your record in your location history. It matters little to you individually. But suppose you give it to an engine like Facebook or Google. In that case, that collective data is an absolute power right in this construct.

Once data becomes a property right, everything, including the derivatives, must be treated similarly. But today, data management is a contractual right rather than a natural property. The implication for data companies is massive. It will change the paradigm if we turn data from contract rights to property rights because we are the creators of our data.

Internet is an extremely powerful technology, but it's very difficult to monetize your data in any significant way. There's no technology to extract value out of the data. But, some companies (like Google and Facebook), realized they could use the data to target ads. So instead of giving away our data, we give up our data in return for better ads.

For example, every one of us is already a contributor to the network effect on Facebook. If we all suddenly stop using Facebook, the face value of Facebook could be zero. The users' value is not fair, given the amount of profit these businesses have.

When we go from rental to ownership, the economics shift dramatically. NFT's may be worth hundreds or thousands because it is no longer a rental asset but ownership proof.

For example, if you buy a house, it is worth at least 30-40 years of rent, which is why you can take a mortgage for the home. The bank can provide a service because it has unquestionable certainty that you can repay it, and the property will be there for hundreds of years to come. If a country has substantial property rights, it will have flourished businesses, high innovation and high level of accountability, democratic values, and capitalism. The digital world is currently entirely rental for the most part. It has great potential in economic value when it turns into ownership.

The value comes down to one additional layer— Identity.

Everything we purchase in the physical world is physical assets that are non-fungible, which actually speaks to our identity. Our own selves aren’t the signals of our identities in the physical world. It’s the decisions we make.

For example, we can travel by Ferrari just as well as we can by a less expensive car from a utility standpoint. We choose to buy a Ferrari because it says something about us. The same is true in the digital world.

These are all social identifiers. If you build in Sandbox, you’re making a statement. It’s no different from opening a big store in Oxford Street in London.

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CASE STUDY: Ownership Paradigm explained in P2E

Play-to-earn game is an example of what an ownership paradigm can do.

Take Axie Infinity as an example. It is a play-to-earn game, and it became popular because of gaming guilds, which were formed to rent out the relevant in-game assets to players. The gaming guild appealed to users in rural areas of the Philippines. The ownership paradigm is actually what allowed for the construction of a new business on top of something with the permission of the spaces.

In web2, in a game that is free to play, 97% of free-to-play game players pay nothing. It is the 1%-3% that actually creates the billions of dollars inside a game economy. Players pay because they can interact with the free players as well. If the free players stop playing, then the pay players are not paying because there's nobody to play with.

The ownership paradigm is an incredible power. Game companies would do a marketing campaign for a traditional game to enter the Philippines market. They would address the customers and do it themselves, which is also limited in capacity. But the entire network of its community actually becomes the ones promoting and building a business because of ownership. And we see the same extending into the physical world. It’s the same in terms of Sandbox. So if I own a piece of land, I can construct a new experience and allow people to enter it. It may look a certain way initially, but I can probably sell it to third parties over time.

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TOKENIZATION OF DATA SETS WILL HAPPEN BECAUSE OF DIGITAL IDENTITY & DIGITAL LEGACY…

Moore's Law will continue to grow, as it is with technologies. We’re at the edge of quantum computing. I believe the capacity to digitize everything exists and will continue to exist. For example, the idea of storing all our photos would seem ridiculous 30 years ago because the cost of storing them was tremendous, even digitally. But those days are long gone now.

We want to digitize everything because it speaks to our identities. Take a wedding ring, for example. In some ways, a wedding ring is fungible. We keep our wedding rings with us and probably pass them on to the next generation because we’re attached to them. In a digital world, it can be a digital legacy. It's an asset that matters to you and maybe only to you and your direct family.

Digital identities are precious because we value them the same way as we do in the physical world. If they're not non-fungible in nature, we can't track them.

One problem with Web2 is that our data can be deleted because it’s controlled and owned by the data companies. Facebook could delete our digital identity and entire history, which means we no longer exist in a digital world. Hence, I believe everything can end up in a blockchain as tokenized assets.

…AND WILL PROVIDE THE ROADMAP FOR COLLABORATIVE BUSINESS MODELS

New, collaborative business models address individuals’ core needs and build trust – while enabling new business opportunities. They augment customers’ data sets with external data, creating ecosystems for new opportunities and delivering a broader range of products and services. They embed privacy, security, and agency. These are digital-driven, technology-forward, and data-driven.

New ecosystems are becoming increasingly important as society becomes more digitalized and the mobile internet becomes the dominant platform for interaction. This shift is reshaping industries from media to advertising and telecoms.

Many companies are creating new ecosystems by partnering with companies outside the traditional industry.

These companies, both incumbents and challengers, are extending their reach beyond their markets — typically through acquisitions and partnerships.

Why is this happening?

Companies are creating new ecosystems to extend their reach. These partnerships drive fundamental changes in industry, media, and telecom business models. Companies like Amazon, Apple, Facebook, and Google (e.g.) are extending their reach far beyond their markets.

These partnerships are enabling new business models:

1. Search, advertising, and social networking are cornerstones of the media industry.

2. Game creation and mobile payment have become core to media distribution channels.

3. Pharma and biotech are creating and documenting their new therapeutics on the blockchain.

4. Telecom companies are creating new programmable networks that connect people, devices, and machines.

These are the new monopolies that digital web2 networks have enabled.

Specifically, Data-driven business models typically evolve through these phases:

1. Inception of technology (Early web)

2. Consumerization of IT: the cycle of users adopting consumer technology in their personal lives, which then extends into usage for work, and organizations finally adopting these technologies. (Skype, WhatsApp, Dropbox, NASDAQ)

3. Surveillance capitalism: The monetization of data captured through monitoring people's engagement and behaviors online (and in the physical world—Google) (Google, Facebook)

4. Facilitation through Distributed networks: (Twitter, Snapchat)

These business models drive customer engagement, co-creation, social currency, transparency, and – most importantly – data.

However, while most of the big companies (e.g., Google, Facebook, etc.) can gather all this data and use it to their advantage, smaller companies and startups do not have access to it. So, how can we unlock this data sharing that could be worth trillions of dollars? And how can we make it not only easier to share but also more useful?

Smart, data-driven business models transform data into insights, drive customer value, unlock opportunities, and can exponentially grow a company's revenues, margins, and valuation.

Decentralized, peer-to-peer (DPTP) networks empower people to create, share, and monetize data. DPTP networks are the networks that allow the applications and participants of the future.

There are three characteristics of data that must be enabled to become user-controlled data:

1. Decentralized: not owned or controlled by a central authority

2. Peer-to-peer networks: make data transactions cheap, decentralized, and fast.

3. Reputational: Users' reputations govern network governance rather than a central authority. Reputational networks are more resistant to whale voting.

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NEW REVENUE & ENGAGEMENT DRIVERS ARISE FOR COMPANIES IF THEY EMBRACE THE EMERGENCE OF A NEW PARADIGM OF DATA

Data, as it flows between people, devices, and the web, opens the door for innovative business models. Partnering with other organizations, being able to access data, or leverage data, could produce new revenue sources and provide monetization opportunities for consumers. Business strategies that ensure efficiencies, productivity, and increased transparency/distribution are full of potential for everyone because all parties benefit.

Data-driven organizations create new opportunities within key areas that drive growth and innovation.

1. Novel Data Pools

New revenue streams, products, and services, as well as richer insights for a broader range of stakeholders, all while ensuring privacy and security, are the results some businesses achieve through data insights and technology. They are exchanging and combining data sets, codifying and selling analytical capabilities, and engaging with new configurations of customers, providers, and other actors to create new markets for value generation.

Data and decentralized systems (aka "dApps & dWeb") are creating new business models, new ways of conducting business, and reshaping entire industries. Traditional companies face change as exponentially growing data, the analysis of unstructured data, and decentralized systems disrupt fundamental processes and value chains.

For example:

Airbnb is the largest online marketplace for lodging, primarily homestays for vacation rentals and tourism activities. However, they see one of the most significant movements of people worldwide. This data could be helpful for a variety of other businesses.

This data includes, and is not limited to:

1. Where users stay (location) and where they are coming from (location),

2. Which part of the city do they prefer staying in (North, east, west, south, etc.)

3. How many people travel to this place yearly (number of travellers)

4. What type of travellers are primarily seen in this city (Families, friend groups, business professionals, etc.)

5. How does travel vary during seasons (holidays, business conferences, crypto meets, hiking seasons, etc.)

6. How much do travelers spend on their travel?

Suppose you're expanding your restaurant chain; you could benefit widely from the Airbnb traveller's data. For example, you can define your restaurant's menu, interiors, opening & closing times, discounts for specific food items, arrange their supply chain well in advance and hire staff that speaks the same language as the most frequent travelers.

Airbnb can enter into an agreement with their users where every engagement on the Airbnb platform (their data) is tokenized and sold to relevant buyers via APIs or CSV data sets. The earnings from selling this data are shared on a pre-agreed percentage split.

As a customer, you are incentivized to share your itinerary details anonymously and combine them with other traveller's details which are then tokenized. The tokens cannot be traded on exchanges. Instead, they are proof of your share in the data sets, and earnings are shared equally among participants.

For Airbnb, this is an additional revenue stream incentivizing travellers to use their platform and share their itinerary details. This also ensures customer retention and accurate predictions of their financials & operational metrics.

This approach can prove that to benefit from the essence of web3, it is not necessary to structurally change the entire business model with blockchain and crypto applications.

2. Novel Partnership Models

New, strategic partnership models address users’ core needs and build trust, enabling new opportunities for users and companies alike.

They enrich user data sets with external data, creating ecosystems for new opportunities and delivering a broader range of products and services. It’s worth wondering how these new models fit within the current tech startup ecosystem, which is obsessed with building software to solve the “problem” of the economy.

One of the most intriguing elements of these models, also known as Partnership Models – is how naturally they fit into the existing ecosystem.

Four Key Characteristics of Partnership Models:

1. They amplify and symbolize resources, skills, and knowledge to create user value.

2. They connect individuals and communities with systems, software, tools, or infrastructure.

3. They manage resources or surpluses and do not move them to external stakeholders.

4. They leverage existing networks, physical or virtual, to bring collective value.

A strategic partnership enables distributed data ownership between current & prospective users and the companies involved.

For users, it creates a distributed data ownership model. For example, instead of a company storing siloed snippets of personal data on their servers, users store it in interoperable online data stores, e.g., specific data sets as NFTs, giving them unprecedented choices over how their data is shared and used.

For example:

A strategic partnership enables distributed data ownership between current & prospective users and the companies involved.

F45 fitness can explore a strategic partnership with a health insurance company. For example, F45 can propose its users to share their fitness data with a health insurance company to develop better insurance products. F45 can tokenize their user data sets as fractionalized NFTs (for proof of contribution to the data set).

Alternatively, users can create a distributed data ownership model. For example, instead of companies storing siloed snippets of personal data on their servers and then tokenizing it, users store it in interoperable online data stores, e.g., tokenized sets on Arweave, giving them unprecedented choices over how their data is shared and used.

With these strategic partnerships, developers have access to a rich store of personal information that is continually updated. It unlocks innovative iterations of:

1. existing products or services,

2. market ecosystems,

3. decentralized applications, and many more.

This approach essentially flips the rules of sharing inclusive benefits from the data with users and companies alike.

3. Enriched Product-Market Experiences

Data. Context. Trust.

That mantra plays out in the consumer, advertising, financial services, medical, insurance, automotive, and telecommunications sectors. The growing use of contextual data creates opportunities for companies

1. to align their business goals better with user needs;

2. to offer a more personalized experience;

3. to increase ROI;

4. to minimize risk;

5. to drive revenue; and

6. to measure results.

Context is the new currency. When users willingly submit their information for tokenized data sets, it corresponds to better actionable intelligence, which benefits both— the data provider and data consumer.

Examples of what context can enable with the help of tokenized data sets:

1. Brands use data from online consumer behavior, demographic and geographic targeting, and consumer health, well-being, and lifestyle preferences to drive better products, services, and marketing

2. Networks of companies using efficient tokenized data sets from users to better understand customers and markets; develop more efficient supply chains; reduce fraud and loss; and attract more customers

3. Cities, states, and countries use data to manage services, infrastructure, and resources better and to address local issues and opportunities

4. Companies in different markets use B2B data to open and create new markets (and raise capital), innovate, and compete.

5. Governments using data to identify and solve systemic issues (such as pollution, insufficient infrastructure, etc.) and to deliver more targeted governmental initiatives (health care, education, etc.)

For example, Let's say I built a web3 dApp called MyData.

Using MyData, an individual can invite the banking system, health-care system, or e-commerce platform to access & share their information and merge it into a data set with information from similar users. Users are asked to compile personal, financial, health, and location data which are then used to establish limitations for working with data within the smart contract.

The MyData app tracks the size and scope of each data set. It enables the individuals to claim ownership of it by tokenizing it. Users can further exchange data for utility or governance tokens or hold it for a more extended period for financial benefits.

Companies find a new data model centered on the individual or a group of individuals, which ensures a single source of data with richness, robustness over time, accuracy, and ease of use. Individuals receive value, agency, privacy, and consent, all of which encourage more data sharing. In addition, the platform can enable use cases spanning health and well-being, finance and banking, and government agencies.

In the background, a blockchain manages how data gets verified, shared, and monetized, enabling trust, transparency, and verification at scale. It tokenizes and publishes the data itself rather than the underlying person.

This app outlines how everyday consumers can own their data and, with consent, share it with companies. By putting consumers in control of their data rather than the other way around, blockchain enables new business models to work.

It also allows new types of products, services, and business models like micropayments, escrow payments, specific e-commerce marketplaces, or an enhanced data analytics platform.

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User Data On-Demand (DoD)

The potential to be infinite, from data analysis to the creation of new products.

Basically, user data is collected by a given company, turned into a data package and tokenized, and then delivered to other companies.

Do you know how much data you have access to?

Only 5% of users understand how much they can collect and analyze. This lack of knowledge about efficiency, scope, precision, and range of their data stands in our way as data is becoming ever more essential to life.

User DoD brings efficiency, reduces costs, and creates a new internet of value.

There are several examples of data flows on the web today. For example,

1. when a user visits a website and goes through a particular process,

2. web companies get data about that action.

3. Then, the data goes through analytics, ads, etc., and is delivered via an API to other parties.

Many large analytics and ad companies have already started to package and sell data as a service. For example, if you ping Google and go through a certain process, it stores all this data on its own. Then, it can send this data to other accounts, businesses, and companies interested in them. This is mainly done via API.

In general, these three flows lead to five values:

1. Ad & Analytics — Companies who want to monetize your activity via advertising (see Facebook, Google).

2. Identity — This is the vital piece, especially today.

3. Authorization — This service permits different services. So, it can be seen as an authorization network.

4. Exchange — Basically, a service that is used to sell something or get stuff.

5. Caching — This explains the network effect since it allows a company to store their data, so if the same user comes back, they get fast results instead of always having to refresh the page.

Many users are involved in these flows, and they are there to harvest money.

However, there are still millions of companies and users out in the world, even though big companies do not lock up data. So, who can benefit from decentralizing this data?

Who Benefits From DoD?

So, User DoD can help companies that deal with identity verification, from small startups and companies to developed countries with huge populations. It will be interesting to see how blockchain projects utilize DoD, especially for the critical aspect of DeFi: under-collateralized loans. Although blockchain projects have different implementations, they usually have similar flows.

In a decentralized data marketplace, that business owner could directly pay specific groups of people for data on their interests and locations instead of paying a centralized entity like Facebook for the same information. Those groups of people would profit from sharing their data. They would know exactly where and why their data was being used, eliminating worries about dubious data usage. The business owner would profit from increased, specific exposure of their business through transparent marketing tactics.

Internet data is not the only thing that can be harnessed and shared for profit. With smartphones, dashcams, and drones, people collect valuable, real-time geographical information every day without any intention of profiting from it. This sort of information is valuable to everyone, from surveyors to researchers.

If online user data were monetized, it would provide additional passive income for its users and increase the amount of available data for improving technology and conducting research. Much like Tesla’s use of its cars’ data, this additional availability of knowledge would allow for a creative and revolutionary expansion of technology at the individual level.

Such an approach would enable the use of data by normal users for their own monetary gain. For example, users could opt into having their digital footprints and browsing habits tracked and monetized by advertisers. Data monetization could target a user’s interests, hobbies, or profession.

Data monetization is the initiation of a feedback loop between the data provider and the users, where:

1. Data consumers (e.g., website operators, advertisers) pay to gain insights from the data (e.g., tracking users or tracking advertising effectiveness)

2. Data creators (e.g., users) receive monetary compensation for the data in exchange.

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LAWS OF WEB3 DATA OWNERSHIP

1. Do what you want with your data with what you have at whichever platform you are on.

2. All internet activity is the study of data; wherever your attention & engagement goes, companies will follow you.

3. In web3, the quality of data on the internet counts, and the quantity of community engagement metrics matters.

4. Your level of engagement defines your influence on the platform, especially DAOs.

5. Data flows should move fluidly between firms, organizations, and functions with increasing complexity. The passive data economy will be driven by billions of nodes collecting data on our lives.

Now, How would you propose incentivizing users to contribute their data to & for the network?

1. Defining the characteristics of data sets that span the spectrum from reports containing personally identifying information to highly aggregated reports to anonymized data sets.

2. Characterization of platforms & services based on blocks retrieved from existing data sets.

3. Developing a clear and concise outline of what security and ethical frameworks are in place for a specific form of data sharing

4. Developing a framework to test out which data sets contain personal information and segregating it.

5. Development of trusted data sharing frameworks that enable organizations to assign permissions across companies using the said data sets.

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WHAT CAN WE EXPECT IN THIS DECADE?

Ensuring that data exchanges are inclusive and equitable requires that both governance frameworks and technical architectures are grounded in inclusion and equity. Systems need the ability to price and monetize data in a way that allows anyone to participate, not only large corporations.

Public data initiatives through APIs are an example where alternative governance models could influence the emergence of public goods, such as distributed digital identities. For instance, User DoD is an alternative architecture to secure and monetize data in a way that compensates individuals and communities.

As pioneers in data governance emerge, the User DoD strategy will position itself to influence the development of future data architectures, working with governments, communities, and technology companies.

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CONCLUSION

When we discover some data on our own, we don't even have a plan of what to do next. Today we can see the early stages of this transformation. Decentralized platforms are springing up, empowering community-driven, market-aligned, and mission-driven systems to create new efficiencies, unique value, and better outcomes with our data. Public data initiatives are an example where alternative governance models could influence the emergence of public goods, such as distributed digital identities.

The cry of 'for your data, for your freedom', has echoed through the web for the last 25 years. It was whispered as a promise by the first wave of internet pioneers. They were building the future in a certain way, making promises that could not be kept. The promises started to fade as greed and illusions took center stage.

Banking was happy with their corner of the internet, happy to make profits from your data. The web became more about advertising than about empowering people. People worked harder, and life started getting harder and harder. Then the third wave arrived. The web3 wave. An attempt to do the internet right. The voices of internet pioneers inspire us to build the web3 community.

As we collectively understand, internet data is not the only thing that can be harnessed and shared for profit. With smartphones, dashcams, and drones, people collect valuable, real-time geographical information every day without any intention of profiting from it. This sort of information is valuable to everyone, from surveyors to researchers.

While the use of location data is not new, today's data is exponentially more precious, thanks to the new networks powered by blockchains. Smart contracts ensure this connectivity between people and devices and between people and data.

Disruptive technologies may change consumer behavior, from targeting ads based on location to sharing data to access public services. Data privacy, which is essential for everyone, may regain the focus it has lost in the last two decades as we move away from a centralized data economy toward a decentralized data economy.

Ultimately, we, the consumer's revolution, will stand or fall by how well we harness and share data. Much data is currently stuck, lost, or inaccessible because it's only accessible to a few. If everyone had mobile connectivity and uninterrupted, two-way access to the Internet, everything could change.

However, I recognize that significant progress and community growth require defining every participant's clear and compelling role in this ecosystem.

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Thank you for reading through. I’d appreciate it if you shared this with your friends who would enjoy reading it.

Consider buying an NFT to support me or using this investment thesis for your whitepaper or website (reference it to this research).

You can contact me here: 0xArhat.

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Read More:

1. ‘Surveillance Capitalism, COVID-19 and Social Work’: A Note on Uncertain Future(s)

2. Data Revolution Report - UN Data Revolution

3. Data Marketplaces: What, Why, How, Types, Benefits, Vendors

4. The state of data in 2022? Decentralization.

5. Creating Data Value With a Decentralized Data Strategy

6. Decoding & Democratizing web3