Personal data has become the cornerstone of the internet economy. Over the past two decades, we have accepted a simple transaction model: platforms collect user data through the provision of free services and monetize it. This model—'if you aren't paying, you're the product'—has shaped various business forms, from targeted advertising to data brokerage.
The rise of AI has added complexity to the situation. Platforms are now selling user data for hundreds of millions of dollars to train AI models—transforming personal information from a resource for targeted advertising into a core building block of artificial intelligence. However, the users who create this data have not received commensurate value.
This was not the original intention. The internet designers initially envisioned that users, not platforms, would control personal information. Tim Berners-Lee dedicated years to restoring this data sovereignty. However, the convenience of cloud infrastructure and the prevalence of free services ultimately dominated, making platforms the controllers of our digital world.
Today, two transformative shifts converge: AI exponentially increases the value of personal data, while advancements in decentralized technology finally empower individuals with tools to control their data.
Vana is the first open-source data sovereignty protocol. It allows users to export their own data from platforms and join data collectives, negotiating directly with AI companies and developers. Through encrypted personal storage and client-side computation, users achieve network effects previously only accessible through centralized platforms while maintaining control over their data. It offers a self-sovereign internet where both parties can benefit: developers can build transformative applications using ideal datasets, while users have full control over their most valuable asset.
Today, we launched the Vana white paper ahead of the mainnet release. In this article, we will explore how Vana transforms personal data from an extractable resource into an asset class controlled by creators.
Overcoming the data double-spending problem
Unlike other digital assets, the core challenge of data monetization is that the economic value of data relies on access permissions—once data is public, it loses its market value. Traditional blockchains focus on public verifiability, making them unsuitable for handling private data. Vana addresses this issue through a framework that combines private data custody with public ownership.
The Vana network maintains a global state that includes the following:
· Data ownership records: cryptographic proof of data ownership
· Access permissions: who can access what data under what conditions
· Verification proof: certification of data quality, authenticity, and metadata
· On-chain data collective contracts and token balances: economic rights and governance
Even though data remains encrypted and stored on personal servers or secure enclaves, the network enables users to decide who can access the data, under what conditions, and how to return value to data creators through programmatic control.
In practice, users can export their private data from any platform and store it on a personal server protected by encryption keys, subsequently joining the data collectives on Vana, which aggregate user data of similar categories. These data collectives are called DataDAOs, which can negotiate with AI model training researchers or application developers to agree on payment for data usage. When external developers purchase data, data contributors in the pool will receive corresponding rewards.
DataDAOs and data tokens
Data liquidity pools are a coordination mechanism that transforms personal data into a new asset class by mapping non-fungible data to fungible data tokens. It instantiates DataDAOs through smart contracts, representing contributors, developers, and researchers around specific data ecosystems. When users contribute data, they receive specific DLP tokens based on the Proof of Contribution from the DataDAO.
Each DataDAO sets different contribution proof standards based on data type. For example, a financial data DLP may focus on transaction accuracy and record completeness, while a social media DLP emphasizes user interaction and account longevity. Health data DLP prioritizes data efficacy and device accuracy.
The Vana protocol provides a standardized certification framework that stores data proofs and metadata on-chain while preserving data privacy. Data validation is conducted through Trusted Execution Environments (TEEs) within the Satya network to ensure data quality certification while protecting privacy. Some DLPs also employ zk technology to enhance data validation, including zk emails and zk-tls.
DLPs serve as the core coordination mechanism for collective data assets within the Vana network, differing from traditional DeFi liquidity pools that coordinate fungible token pairs, as DLPs coordinate non-fungible personal contribution data while maintaining data privacy and sovereignty.
The Vana Foundation is currently collaborating with 12 high-quality DataDAOs to conduct accelerator programs and has received 300 new applications. Current DataDAO teams consist of 2 to 5 members dedicated to building DLP around specific data sources, including Twitter data, synthetic data, genomic data, and browser data. Each DataDAO will issue its own exclusive dataset tokens. Users can learn more about DataDAOs here.
The advantage of DLPs lies in their permissionless nature—anyone can create a DLP without needing approval from the data source platform. This is because DLPs leverage existing data privacy regulations to ensure individual users can export and control their personal data.
When AI researchers and model developers wish to access these aggregated data, they can interact directly with the governance system of the DataDAO, rather than negotiating with thousands of individual users. This collective negotiation approach is transformative: data contributors receive governance tokens based on their contributions, granting them economic rights and decision-making power to determine how their data is used. The end result is a virtuous cycle where high-quality data contributions are rewarded, market forces determine fair access pricing, and users are motivated to continue contributing data.
For instance, an AI researcher might propose a phased access plan to a DataDAO, first accessing 10% of the dataset for quality control, then using the complete dataset for model training—all while keeping the data encrypted and secure. In exchange, they will destroy a certain number of DLP tokens, distributing value back to data contributors. Thus, as the value of the dataset grows, the returns will be directly shared with the contributors.
DataDAOs and VANA tokens
The launch of the Vana mainnet will break the monopoly of big tech companies on data. In the past, AI companies could only collaborate with centralized platforms like Meta and Google, which controlled vast amounts of data and limited developers' access. This situation persisted because coordinating data access for millions of users is a technical and social challenge.
The Vana mainnet fundamentally changes this landscape by establishing data sovereignty infrastructure. Millions of users can aggregate data into a liquidity market, competing with big tech companies while cryptographically protecting personal information. The Vana mainnet creates a data economy driven by market forces rather than platform monopolies.
We lay the foundation for ownership of user data: users control it through non-custodial wallets, and the data can be carried with them in their online activities.
VANA tokens realize this vision through several key features:
· Ensuring network security through validator staking
· Pay transaction fees for network operations
· DLP staking determines the issuance rewards of different DataDAOs
· Data access rights for purchasing all DLPs
When AI companies want to access DLP data, they must use VANA to purchase and destroy DLP tokens. This establishes a direct economic link between network usage and token value. As more AI companies need access to user data, the demand for VANA and DLP tokens increases. The burn mechanism ensures that value is returned to the network and data contributors.
The top 16 DataDAOs will receive rewards based on the amount of VANA tokens held to reward those early users who contributed data to the network. The top 16 will be selected every 3 weeks, with rewards distributed according to Vana DAO's performance metrics. For more information on DataDAO rewards, please click here.
In this way, VANA serves as both the economic foundation of data trading and represents the total value of data assets in the network. As more AI companies access DLP data, VANA's buying and burning mechanisms create a sustainable economic system that rewards data contributors and network participants.
A new era of open data economy
The launch of the Vana mainnet marks a fundamental shift in power within the AI economy. Users can collectively challenge the data monopoly of big tech companies, transforming personal data into assets that they control. This is not just about rewards; it is about redefining who builds, controls, and benefits from AI.
This opportunity is both urgent and immense. AI companies are facing a data bottleneck and urgently need new training data. Through Vana, users can aggregate data into datasets that compete with large platforms while maintaining encrypted control. As each new user joins, the Vana network becomes stronger, supporting cross-platform datasets and empowering users with data sovereignty.
We are building an AI economy that serves users and open-source developers, not Web2 giants. In this era, data flows freely, sovereignty is maintained absolutely, and the next generation of AI models will be trained on data owned by users, with benefits returning to data contributors. Top AI developers can access ideal datasets. Join us in creating a new open data economy.
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