In the field of on-chain data collaboration in Web3, there have long been three core pain points: data is presented in an isolated distribution state, scattered across different public chains and application systems, making it difficult to form a cohesive whole with collaborative value; when collaborating across scenarios and public chains, data formats and processes need to be repeatedly adapted, resulting in significant overall efficiency loss; the value of data is mostly limited to single collaboration scenarios, lacking clear reuse paths and long-term sedimentation mechanisms. Bubblemaps breaks out of the positioning of 'single data tools' and builds a complete system centered on on-chain data interconnection and structuring, with 'technology foundation - scenario adaptation - ecological symbiosis' as its core capability, transforming isolated data into a collaborative network that is interconnected, transferable, and value-added, redefining the underlying logic and value boundaries of Web3 data collaboration.
1. Core Technology: Building the underlying capabilities for on-chain data interconnection and structuring
Bubblemaps' technological innovation focuses on three major goals: 'data interconnection, collaborative circulation, and value accumulation.' By breaking through traditional collaboration bottlenecks with self-developed technology modules, it transforms on-chain data from 'isolated existence' to 'interconnected symbiosis,' providing solid technical support for efficient collaboration.
1. Multi-dimensional interconnection and structuring engine
To address the pain point of 'data isolation and dispersion,' this engine adopts a dual-core design of 'three-dimensional attribute coding + dynamic association algorithm': each type of on-chain data (including but not limited to DeFi liquidity data, NFT user behavior data, DAO governance data) is assigned a three-dimensional attribute coding of 'scenario attributes, quality dimensions, and reuse potential,' clearly defining the data's scenario adaptability, quality standards, and subsequent reuse space; then, by real-time calculating the interaction correlation, value overlap, and scenario fit of data, it generates a dynamic correlation coefficient, automatically weaving high-correlation-value data into a multi-level interconnection network. The engine supports millisecond-level real-time updates, ensuring that the data network is always synchronized with the latest on-chain dynamics, significantly improving data association efficiency and avoiding the inefficiencies of manual screening and integration.
2. Cross-scenario collaboration circulation layer
To solve the limitations of 'inefficient cross-scenario collaboration,' the circulation layer is designed with a flexible mechanism of 'predefined template library + smart link assembly': it includes high-frequency collaboration templates covering the four core scenarios of DeFi, NFT, DAO, and Metaverse, encompassing key collaboration links such as data processing, format conversion, and demand matching; when a cross-scenario or cross-public chain collaboration need arises, the circulation layer automatically reads the three-dimensional attribute coding of the data and extracts adaptable modules from the template library, quickly assembling them into customized collaboration links, and clearly delineating the roles and divisions of labor of each participant through smart contracts. This circulation layer is compatible with mainstream public chain systems, significantly shortening the process adaptation time for cross-scenario collaboration and lowering the technical thresholds and time costs of multi-ecosystem linkage.
3. Value reuse accumulation mechanism
To break the predicament of 'single consumption of data value,' the mechanism constructs a full-cycle value chain of 'initial collaboration - subsequent reuse - iterative value addition': when data first participates in collaboration, a preset proportion of the value is distributed to data providers and collaboration organizers; when data is reused in other scenarios, the original data provider can still receive a corresponding proportion of reuse income, while the reuser gains part of the profit to incentivize their participation in value flow; if data is optimized and iterated (such as adding new dimensions or improving data accuracy) to create new value, the original provider and the iterator will share the added value. All value distribution rules are automatically executed through smart contracts, ensuring that the data value continues to accumulate throughout its lifecycle, avoiding value loss at the end of a single collaboration.
2. Scenario adaptation: The implementation of interconnection and structuring capabilities in the core fields of Web3
Bubblemaps' scenario adaptation does not rely on fictitious cases but is based on the common collaborative needs in the core areas of Web3, integrating 'data interconnection and structuring' capabilities into actual collaboration processes to solve common pain points in various fields and release the value of data collaboration.
1. DeFi field liquidity interconnection collaboration
The core collaborative pain point in the DeFi field is the dispersion of liquidity across multiple public chains, making it difficult to efficiently match supply and demand. Bubblemaps uses a multi-dimensional interconnection and structuring engine to weave liquidity data, user preference data, and asset fluctuation data from different public chains into a cross-chain interconnection network; when a certain public chain experiences an imbalance in liquidity supply and demand, the cross-scenario collaboration circulation layer can quickly build a liquidity collaboration link to achieve efficient allocation of liquidity between different public chains. Meanwhile, the value reuse accumulation mechanism ensures that roles contributing liquidity data can continue to earn profits during subsequent data reuse, enhancing data contribution motivation and optimizing overall liquidity collaboration efficiency.
2. NFT field creation data interconnection reuse
NFT creators generally face high data research costs and difficulties in reusing historical creation data. Bubblemaps constructs a creative data interconnection and structuring pool for the NFT field, incorporating creators' user preference data, style adaptation data, and operational feedback data into the interconnection network, allowing creators to reuse related data from the network through authorization, reducing research costs; simultaneously, data providers can obtain continuous income from the multiple reuses of data through the value reuse accumulation mechanism, forming a virtuous cycle of 'data contribution - reuse value addition - profit sharing,' helping creators optimize their creative strategies and operational directions.
3. DAO governance data interconnection linkage
DAO governance often suffers from isolated governance data, leading to proposal designs that deviate from actual needs, and governance experiences that are difficult to reuse across organizations. Bubblemaps weaves voting tendency data, proposal execution feedback data, and member collaboration data from different DAOs into a governance data interconnection network, enabling DAO organizations to call on related data from the network through the cross-scenario collaboration circulation layer to provide references for proposal design; the value reuse accumulation mechanism incentivizes contributors of governance data, promoting the entry of more high-quality governance data into the interconnection network, enhancing the scientificity and efficiency of DAO governance, and facilitating the cross-organizational flow of governance experiences.
3. Ecological construction: Ensuring the sustainable evolution of the data interconnection and structuring ecosystem
Bubblemaps' ecological design revolves around three major principles: 'encouraging participation, autonomous iteration, and technological co-construction,' through mechanism design to involve more roles in 'data interconnection and structuring,' ensuring the ecosystem possesses long-term vitality and evolutionary capabilities.
1. Layered contribution incentive mechanism
Based on 'data correlation coefficients + value reuse frequency,' the incentive system is designed to distribute ecological revenue in layers according to 'core structurers - auxiliary contributors - ecological maintainers': core structurers refer to roles providing high correlation coefficients and high reuse frequency data, with earnings calculated based on the aggregation of data's correlation coefficients and reuse frequencies; auxiliary contributors refer to those participating in data annotation, link verification, and other basic tasks, with earnings tied to actual contribution levels; ecological maintainers are responsible for optimizing technical modules and updating collaboration templates, with earnings extracted from the total ecological revenue at a fixed proportion. This mechanism ensures that different types of participants can receive rewards commensurate with their contributions, stimulating the vitality of ecological participation.
2. Community co-governance iteration mechanism
To adapt to the rapid changes in the Web3 ecosystem, a community governance process of 'proposal-voting-execution' is established: ecosystem participants can submit proposals for technical optimizations (such as adding new data dimension), scenario adaptations (such as expanding new collaboration scenario templates), incentive adjustments, etc. Proposals require staking a certain amount of 'contribution value' (obtained through data contribution and community participation); once proposals are approved by community voting, the system automatically updates the rules in the smart contract without centralized intervention, ensuring that the direction of ecosystem iteration aligns with the needs of most participants and enhances ecosystem adaptability.
3. Technology open-source co-construction mechanism
Establishing an 'on-chain data interconnection and structuring technology open-source community' to open up core technology modules (including the correlation algorithms of the interconnection and structuring engine and the template logic of the collaboration circulation layer) to global developers: developers can submit technical optimization proposals, which will be reviewed and approved by the ecological technology committee before being incorporated into the project's technical architecture iteration, and receive 'structuring contribution value' rewards, which can be exchanged for ecological revenue sharing or technical permissions. Through open-source co-construction, the wisdom of global developers is gathered to provide continuous momentum for project technological iteration, ensuring that the 'data interconnection and structuring' capabilities remain industry-leading.
Summary and Future Outlook
Bubblemaps' core value lies in centering 'on-chain data interconnection and structuring' to establish itself as the central hub of Web3 collaboration—it's not simply about integrating scattered data but about using technological means to allow data to proactively form interconnected networks; it’s not limited to single collaboration services, but builds an ecosystem where data value continues to flow and accumulate; it does not rely on external ecological empowerment, but forms an independent and sustainable collaborative system through self-developed technology and mechanisms. It redefines the value logic of on-chain data: transforming from 'isolated information units' to 'interconnected value nodes,' from 'resources consumed in a single instance' to 'assets with long-term appreciation.'
In the future, Bubblemaps will continue to deepen its 'data interconnection and structuring' capabilities: introducing AI technology to predict and optimize data associations, enhancing structuring efficiency; developing multi-chain structuring intercommunication protocols to break the barriers of different public chain data structuring networks; exploring the 'linkage between interconnected structured data and real scenarios' to expand the boundaries of data value. Ultimately, the project will be based on 'on-chain data interconnection and structuring' to become a key infrastructure for the Web3 collaboration ecosystem, allowing every piece of on-chain data to release long-term value in interconnection and enabling every participant to share in the ecological growth dividends during collaboration.
