Apibara: Open Source Data Platform | limits | This project aims to add Ethereum data (execution + consensus layer) to Apibara, an open source data platform. Apibara allows developers and researchers to sync any on-chain data to a target database or API. It currently supports PostgreSQL, MongoDB, Parquet, and webhooks. It is easy to add support for more integrations. Apibara focuses on “online” usage. It backfills the data first, then syncs it as the chain progresses. Developers can access the data using tools they already know. Our data sync protocol is chain independent. This allows us to support execution layer and consensus layer data indexing. |
DotPix | Anton Barstetter | DotPics is a collection of dashboards, data, and tools for Ethereum. In terms of dashboards, I also plan to create a dashboard that focuses on the 4844 blobs, their usage, and integrating them into mevboost.pics. There is also an open source dataset that I maintain. Finally, the parser that parses CL, EL, MEV-Boost (bids and payloads), and other items will soon be open sourced. It is currently in the final testing phase. The final parser will have a simple GUI that makes it as simple as possible for anyone to parse the data they want. The parser will also directly label the entities (Lido, Coinbase, etc.) to validators, and flag potentially censorable transactions and ETH2 deposits. The parser can be plugged into a node and is ready to use. |
Healthy network baseline | Metric system | The problem we are trying to solve is to establish clear metrics and thresholds to define a healthy Ethereum network. Given the dynamic and distributed nature of Ethereum, the responsibility for monitoring and preserving the health of Ethereum lies with the entire community. To achieve this, the community must agree on network health metrics. These include specific metrics to track and corresponding thresholds that indicate potential problems when the network is tipping toward an unhealthy state. We will leverage Xatu to establish robust health metrics for Ethereum’s peer-to-peer (P2P) network layer. Our goal is to document our findings, rationale, and detailed explanations for the metrics we have chosen, so that the community can gain the knowledge to protect the stability and well-being of Ethereum. |
MigaLabs Data Collection | migalaps | The Ethereum blockchain is constantly evolving. It has changed dramatically in the past with the transition from Proof-of-Work to Proof-of-Stake, and it will change even more in the future with the introduction of EIP 4844 and others. Understanding these changes and anticipating potential bottlenecks is a major task for blockchain researchers. However, this requires a wide range of tools to collect massive amounts of data, extract information from it, analyze observed patterns, and visualize them in an intuitive way. The goal of this ambitious project is to develop and improve tools to monitor Ethereum nodes, track data propagation, discover nodes on the network, reveal patterns in MEV, explore the limitations of DVT technology, monitor Devnet and fork functionality, track validator performance, and visualize all of this data in a clear and insightful way. |
Allow validators to provide client information privately | Nethermind | Understanding the distribution of Ethereum execution layer and consensus layer clients used by validators is essential to ensuring a resilient and diverse network. While there are currently methods to estimate the client distribution of the beacon chain between validators, the same cannot be said for the execution client distribution. Furthermore, there is no standard means to anonymously show which ELs and CLs are being used. This proposal aims to study and design a method to submit and extract this important data without potentially compromising user anonymity and network performance. |
Anonymous Verifier Data Collection Using ZK | Abhishek Kumar | There are close to 900,000 validators on the Ethereum mainnet. This means that there is a lot of data waiting to be collected about validators. This data can help us understand their problems and better design the Ethereum protocol. However, the truth is that there is not enough data about these validators. Sure, there are data dashboards like rated.network, but they are incomplete. For example, there is no information about what clients (reth, nimbus, teku) Ethereum nodes are using, what machines (arm64/linux) they are using, etc. Validator operators do not want to reveal too much information about their staking settings. This is exactly the problem we are trying to solve. We plan to use ZK to collect data that allows validator operators to provide information while remaining anonymous. |
Core Platform Extension | Gross Epi | growthepie has a solid foundation of providing trusted Layer 2 data, block space analytics, and content for end users, developers, and investors. Our goal is to provide users with the most neutral and fully curated metrics, tools, and knowledge to understand the ever-growing L2 space and make the ecosystem more transparent. To do this, we aim to expand the feature set of the platform, list more Ethereum Layer 2s, and include more metrics, block space analytics, and knowledge content. All while being funded by the public good, maintaining a reliable infrastructure for high demand, and maintaining a responsive and fast user experience. |
Standardized and crowdsourced smart contract labels and ABIs | Gross Epi | This proposal addresses the problem of isolated and non-standardized contract labeling datasets within the blockchain data community. By introducing a standardized data model for smart contract labels, including ABIs, we advocate for unifying diverse data providers into a single, universally accessible database. Our solution goes beyond standardization to add the community as a key player in the labeling effort. We find that the long-term success of a comprehensive label database depends on community crowdsourcing, which is achieved by lowering the barrier to entry with a more user-friendly front-end and open API endpoints for seamless integration. This approach represents a significant turning point for smart contract labels to become a community-driven, standardized, and ultimately decentralized public good. |
Economic Analysis of L2 | Nethermind | The rapid adoption of Layer 2 solutions (L2) requires a clear understanding of the profitability and data requirements of new chains. We aim to develop tooling that provides data on the cost of call data in L2 and the fees paid by L2 networks for L1 security. The magnitude of call data costs will also help us study the dynamics of 4844. We aim to provide insight into the data requirements of the largest expected blob space consumers. Analysis of rollup profitability and current costs will provide critical information for designing a competitive gas market for all rollups and increasing the information available to rollup consumers so that they can make informed choices about the architecture they rely on. This, combined with other proposals for rollup security, will provide consumers with a strong basis for choosing rollup services with known costs and risks. This data will also be effective in modeling and predicting the behavior of the data blob market on Ethereum. Paper by Offchain Labs and Ethereum Foundation We assume that the top 5 rollups by TVL will be classified as ‘large rollups’ in the near future, and that their data publishing strategy will be to use EIP-4844. We can calculate what the historical cost of 4844 would have been assuming that the rollups used 4844 at genesis, and try to predict the market dynamics of 4844 in the near future based on current and expected usage of rollups. Finally, we will propose a standard to compare and benchmark computational capacity between EVM and non-EVM chains. |
Economic Analysis of L2 Finality and L2 Security | Nethermind | The rapid adoption of Layer 2 solutions (L2) requires a clear understanding of the associated risks for both developers and users. We aim to develop a tool that provides real-time data and assesses these risks across multiple L2s. The tool addresses the risk that L2 networks diverge from the L1 standard chain and that L2 blocks are not finalized on L1. Real-time asset risk tracking also quantifies and displays assets at risk, providing a clear picture of financial exposure. Through this tool and its associated dashboards, we aim to improve transparency and understanding of the L2 ecosystem, fostering a more secure and informed community while encouraging L2 to drive the economic security it needs. |
Wallet Label – Standardizing and strengthening Ethereum account labels for transparency and usability | Function03 Labs | WalletLabels is a platform that simplifies the identification of on-chain wallets through custom labels. The need for clear, accessible, and actionable insights into wallet behavior is becoming increasingly important as the space grows and matures. Through an intuitive interface, users can easily search and categorize wallet addresses by name, label, or entity type, transforming anonymous hashes into meaningful insights. Whether it’s a block explorer, wallet service, or consumer-facing application, we aim to provide a labeling infrastructure that scales value across a wide range of platforms. |