What are the highlights of Vana's data ownership solution?
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What are the highlights of Vana's data ownership solution?
Vana's solution,即将 launching on mainnet, primarily addresses two major issues: "data double-spending" and "privacy protection."
Navigating Web3 tides with focused insightsBy Haotian
"Let users own their data sovereignty" — this slogan once carried the grand vision of the entire web3 era. However, due to persistent challenges such as high on-chain data storage costs and privacy concerns, it has yet to see real-world application. Recently, fueled by the massive demand for data sources in the AGI model training market, @withvana — soon to be listed on Binance — has introduced a novel solution combining DLP (Data Liquidity Pool) with TEE technology to address data ownership. What are its key innovations?
1) Data sovereignty and personal data dividend have long been debated topics. In the web2 era, personal data exploded in volume but led to platform monopolies and severe breaches of data privacy. In early web3, many projects attempted to realize data ownership through smart contracts, decentralized storage, and on-chain provenance, only to encounter obstacles such as prohibitively high storage costs and the inherent transparency of blockchain, which complicates privacy protection.
As a result, efforts to achieve "data ownership" via blockchain have remained stalled due to technical bottlenecks.
2) With the arrival of the AI era, diverse use cases — including AGI model training, multimodal learning, data reasoning, and fine-tuning — especially in vertical domains and specialized machine learning, require vast amounts of high-quality, non-public data. This makes private data held by individuals and institutions a critical resource for AI advancement, creating a large-scale "demand side" for data utilization.
This forms the foundation of Vana’s governance framework: while awareness around data ownership and privacy remains low in most web2 environments, the AI era treats data as a strategic asset — a fundamentally different context.
3) Vana,即将 launching its mainnet, targets two core issues: "data double-spending" and "privacy protection." Specifically, when data is made public on-chain, unrestricted copying and storage can undermine its scarcity and erode its value-capture potential.
Vana establishes a data marketplace using DLP (Data Liquidity Pool), powered by a unique Proof of Contribution mechanism that underpins the system's operations.
Data owners can stake the usage rights of their data into domain-specific pools — such as medical records or financial transaction pools — and receive DataDAO tokens and data-backed tokens as proof of权益. Fees paid by AI training parties accessing these pools are automatically distributed proportionally to token holders. Data owners also participate in DataDAO governance, jointly deciding on DLP operational rules, pricing strategies, and more.
The data liquidity pool functions similarly to common DeFi trading pools, with smart contracts managing validation of data authenticity, access permissions, token distribution, and other orchestration tasks. This is key to solving the "data double-spending" problem: tokenizing data enables clear ownership attribution, while smart contracts ensure full traceability of data usage and automated revenue distribution.
To address privacy, Vana leverages TEE (Trusted Execution Environment) secure enclaves. TEE technology enables controlled "usage rights" while preserving data privacy. From user servers to DLP pool access and subsequent AI training, the entire process benefits from end-to-end security within the TEE environment.
For example, when a user authorizes part of their data to a DLP pool, that data resides within a TEE-protected space. Clients granted access may use it for training but cannot copy or exfiltrate it.
The TEE provides full audit logs and isolated processing throughout, ensuring data remains private even during active use. Its "usable but not visible" characteristic elegantly resolves the privacy dilemma. Beyond these two core features, Vana grants data owners full control: users can revoke or modify data usage permissions at any time.
Furthermore, Vana employs a clear layered architecture: at the base layer, users can flexibly store data via lightweight self-custody or proxy custody; at the middleware layer, DLP acts as the protocol layer, using smart contracts for granular orchestration — including data flow management, permission controls, and revenue distribution; at the top layer, standardized interfaces connect to various AI applications, serving needs like large-model training and data analytics.
This layered design ensures both data sovereignty and scalability across use cases.
That’s all.
Finally, one additional perspective: Vana’s solution for data ownership in the AI era represents a revival of an old narrative, now catalyzed by AI use cases — making it a crucial component of the broader AI narrative wave.
Vana’s potential moat lies in the network effect: once its data collection, usage, and权益chain is fully operational, it could expand into broader domains and scenarios. Don’t forget — the grand vision of data ownership may ultimately span the entire blockchain and web3 landscape.
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Haotian | CryptoInsight
