It rewards OCEAN to liquidity providers (stakers) as a function of consume volume and liquidity. It’s like DeFi liquidity mining, but tuned for data consumption. DF’s aim is to achieve a minimum supply of data for network effects to kick in, and once the network flywheel is spinning, to increase growth rate.
Please [follow this tutorial](../tutorials/veOcean-Data-Farming-Tutorial.md) to learn how the Ocean Protocol reward programs work, and how to access them.
Data assets for DF may published in any [network where Ocean’s deployed in production](https://docs.oceanprotocol.com/core-concepts/networks): Eth mainnet, Polygon, etc.
This behavior is inherited from [veCRV](https://curve.readthedocs.io/dao-fees.html); [here’s the code](https://github.com/oceanprotocol/contracts/blob/main/contracts/ve/veFeeDistributor.vy#L240-L256).
DF Main started Mar 16, 2023 in DF Round 29. DF29 has 150K OCEAN rewards available (a 2x increase from DF28). As DF Main progresses, rewards will increase to 300K (another 2x), then 600K (another 2x), then beyond 1.1M OCEAN/week (near 2x) then decaying over time.
In DF23 Ranked Rewards were introduced and smooth the reward distribution by using a logarithmic function.
**Since rewards are distributed across the Top 100 assets (current tuning Mar — 2023), all participants (Publishers & Curators) are now incentivized to support a broader range of assets rather than optimizing on a single asset.**
At the top-end, this helps increase quality and diversification of inventory.
At the bottom-end, this eliminates some potential free-rider issues and smooths out the reward distribution.
You can read more about the implementation [in this blog post](https://blog.oceanprotocol.com/data-farming-df22-completed-df23-started-reward-function-tuned-ffd4359657ee) and find the full study [in these slides](https://docs.google.com/presentation/d/1zZdWfywruMPt6r7vfl0nQD8Fgj4wkfuMslZcWJmy3GE/edit?usp=sharing).
As part of our efforts to increase the efficiency of the Reward Function, we researched a broad range of improvements that could be implemented and discussed their many outcomes.
One particular improvement was noted, how to structure incentives to also align publishers.
We explored dozens of possible ways to do it. In the end, we arrived at this approach. It was chosen for it’s simplicity and ease of understanding.
For Data Farming, we want to incentivize publishers to create more data sets, build more token-gated product, innovate how builders can consume Data-tokens.
