By Kyle, Investment Manager@Bing Ventures
It is now widely believed that the fourth industrial revolution will be driven by data. Blockchain technology, which makes data self-aware, has become a new asset class. The data of today’s world is already large enough to increase the digital dependence of humans and thus generate more data. So the world is scrambling to regulate the use, storage and privacy of data. The data DAO is born from this.
Data DAOs represent a post-industrial opportunity. With the ubiquitous decentralized communication infrastructure of the future, personal data assets will emerge as highly reliable, secure and usable infrastructure in the social graph, enabling powerful innovations through edge computing and more. Data DAOs are definitely the next step in the evolution of decentralized data.
The dilemma of data DAO
The DAO-oriented process of the data market is more like the orthodox continuation of Web2 Internet play, especially the demand of retail investors for personalised and labeled data processing is higher. Compared with the feeding mode of the current centralized data platform, users prefer to have data pages with higher degrees of freedom and experience, and participate in the construction of DAOs including visual analysis tools.
However, due to a number of reasons, the current data cannot be entirely put in the blockchain, mainly limited by the following dilemma:
1. Cost of on-chain data storage;
2. Data privacy, anonymity and specific confidentiality terms;
3. Islands of users’ past behaviour labels;
Source: getdbt
A necessary condition for the success of a data DAO project is that the user continues to expand the reproduction of data. At the same time, data DAOs should prioritise decentralized governance to limit data tampering and maintain transparency.
As data DAOs generate more continuous data streams, such as users’ browsing data or social graphs, the more members and data providers the DAO will have, and the more valuable it will be to potential data buyers and data subscribers. The revenue earned by the DAO should be used to maintain and develop the organisation and its members, and should have an open API to save construction costs for the members.
The feasibility of data-to-earn mode
A data DAO should consist of two key elements. First, it must have a D2E (data-to-earn) model that aggregates users’ favourite Data and provides tools for users who want to tap the potential of their Data through Data marketplace capabilities to more accurately match users’ Data. Second, it must have a plug-and-play data API system to build D2E’s interwoven ecosystem.
The core of a data-like DAO is to provide support for motivating people to participate in the reproduction of valuable data so that they can monetise their data. Predictive machines, smart contracts, and decentralized storage and computing networks are used to exchange tokens and data to build the infrastructure for data-like DAOs. The main sources of value are:
-Prediction machine based on price data;
- Data management fees, especially royalties in the form of NFTs;
- Subscription fees for data streams, currently in the form of membership fees;
Source: Chainlink
In theory, anyone with access to the Internet has the opportunity to participate in a data-like DAO. Users can choose “free mode” to create data assets and receive rewards in the form of network tokens. Tokens for data-like DAOs open up more imagination and can represent any digital asset that is fungible or irreplaceable, including cryptocurrencies. Once users become holders of the tokens, they will be able to vote to influence their governance decisions.
Operation logic of veData(3,3)
The data DAO space is a growing pie. The more people involved in a data-class DAO, the better for each member. From the beginning, most people started to get into the cryptocurrency price data market through the APIs of central exchanges, slowly started to get into CoinMarketCap, CoinGecko, and finally into sophisticated analytics tools for on-chain data like Glassnode and Nansen.
Similarly, there is considerable scope for business spin-offs from data-class DAOs. The sheer volume of data makes it easy to create proprietary consulting models for other projects. It’s a very organic way to create business. Demand is where data is, and that’s a great way to build a business.
To be a qualified member of a data-class DAO, you need to have an open ideology about how you get your data, and you can run it however you want. You can have your own database of many on-chain transactions in the DAO, customise it, and use it to do some interesting visualisations.
Source: Ocean Protocol
The core competency of the current dat-class DAO is the use of machine learning to on-chain data. If you think of tokens as objects, and then wallets as users, you can use very standard algorithmic recommendation techniques, like collaborative filtering, to build predictable models.
The data DAO Token mechanism should follow the path of DeFi and pledge the product Token to obtain veData with influence on the interest rate and rights of the data. The issuance of the Token is decreasing every week and will be determined by the number of veData.
The larger the number of veData, the smaller the Token issuance. Meanwhile, the amount of veData is also affected by the social activity within the DAO, which is determined by the social pedigree structure of the DAO. In addition, veData can be traded as an NFT in the secondary market to solve the liquidity problem of lock-up assets.
Source: Crust Network
The feature of this Data(3,3) is that users are encouraged to pledge and lock their tokens, which will lead to an overall reduction in Token issuance. At the same time, veData is not only affected by the liquidity pledge of tokens, but also linked to the interactive use of data in DAO, eliminating the liquidity factor of disloyalty. Users need to further improve data production and utilisation within the DAO, and the longer users pledge their tokens, the more rewards they will receive.
The DAO can be super open and transparent about all the failures and things that didn’t go exactly the way we wanted from the start. The DAO structure is inherently challenging. Incentivising users to participate and vote, and to drive new proposals, requires a solid long-term token mechanism. I encourage everyone not to be rigid about data-like DAOs. DAO is both a scientific institution and a religious soul. At the very least, building a long-term organisation based on agnosticism is no less difficult than building a religion. There is still plenty of room for development and exploration.