| Stat | Value |
|---|---|
| Ticker | OCEAN |
| Price | $0.14 |
| Market Cap | $28.98M |
| 24h Change | -0.0% |
| Circulating Supply | 200.08M OCEAN |
| Max Supply | 1.41B OCEAN |
| All-Time High | $1.93 |
| Contract (Ethereum) | 0x967d...9f48 |
| Contract (Energi) | 0x99a1...5d2b |
| Contract (Sora) | 0x002c...76b9 |
| Contract (Polygon Pos) | 0x282d...a1a1 |
| Contract (Optimistic Ethereum) | 0x2561...9f9e |
What Is Ocean Protocol?
Ocean Protocol is an open-source data marketplace that allows data owners to monetize their data assets while retaining control over access and privacy. By tokenizing datasets as NFTs (Data NFTs) and selling access via datatokens, Ocean creates a decentralized economy for AI training data, research datasets, and enterprise data exchange.
How Data Tokenization Works
Data NFTs: Each dataset published on Ocean is represented as an ERC-721 NFT. The NFT owner controls who can publish, sell, or update access to the data.
Datatokens (ERC-20): For each Data NFT, the owner mints ERC-20 “datatokens” that function as access keys. Holding 1 datatoken grants access to consume (download or compute on) the dataset. Datatokens can be traded on any DEX, creating a market for data.
Compute-to-Data (C2D): A privacy-preserving feature where algorithms are sent to the data rather than data sent to the algorithm. This allows model training on sensitive data (medical records, financial data) without exposing raw data to the algorithm operator.
OCEAN Token
OCEAN is the medium of exchange and governance token:
- Data purchases: Used to buy datatokens granting access to datasets
- Liquidity provision: OCEAN/datatoken pools on Ocean Market and integrated DEXes
- Governance: OCEAN holders vote on Ocean DAO proposals and treasury allocation
- Veocean (staking): Locking OCEAN grants veOCEAN, which earns passive data farming rewards
AI Data Economy
Ocean Protocol targets the growing AI training data market. As demand for quality AI datasets increases, Ocean provides infrastructure for data providers to monetize their datasets without losing control — addressing the data privacy concerns of centralized AI training pipelines.