This project aims to add Ethereum data (execution layer + consensus layer) to Apibara, an open source data platform. Apibara allows developers and researchers to sync all onchain data to a target database or API. Currently, we provide support for PostgreSQL, MongoDB, Parquet, and webhooks. It is easy to add support for more integrations. Apibara focuses on “online” usage: first it populates the data, then syncs it as the chain moves forward. Developers can access the data using the tools they are already familiar with. Our data synchronization protocol is chain-agnostic. Because of this, we can support indexing of both execution and consensus layer data.
DotPics
Anton Wahrstatter
DotPics is a collection of dashboards, data, and tools for Ethereum. On the dashboard side, I also plan to create one focused on 4844 blobs, blob usage, and embedding blobs in mevboost.pics. Additionally, there are open source datasets that I maintain. Finally, my analyzer for analyzing CL, EL, MEV-Boost (Bids and Payloads), and other stuff will be open source soon. Currently in final testing. The final analyzer will have a simple GUI that allows anyone to analyze the desired data as easily as possible. Additionally, the analyzer directly tags validators with their respective entities (Lido, Coinbase, etc.), flags potentially censorable transactions, and ETH2 deposits. The analyzer can be plugged into a node and is ready to go.
Health Network Reference Bases
Metric
The problem we seek to solve is to establish clear metrics and thresholds to define a healthy Ethereum network. Given the dynamic and decentralized nature of Ethereum, the responsibility to monitor and maintain its health falls on the entire community. To achieve this, the community must agree on network health indicators, including specific metrics to track and corresponding thresholds that signal potential issues when the network is moving toward an unhealthy state. By leveraging Xatu, we will establish robust health baselines for Ethereum’s peer-to-peer (P2P) network layer. Our goal is to document our findings, rationale, and detailed descriptions of the selected metrics, equipping the community with the knowledge needed to maintain the stability and well-being of Ethereum.
MigaLabs Data Collection
MigaLabs
The Ethereum blockchain is constantly evolving. It has changed significantly in the past, with the transition from Proof-of-Work to Proof-of-Stake, and it will change significantly in the future, with the arrival of EIP 4844 and others. Understanding these changes and anticipating potential bottlenecks is the main job of blockchain researchers. But for this, we need a wide range of tools, in order to collect massive amounts of data, extract information from it, analyze the 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 network nodes, uncover patterns in MEV, explore the limits of DVT technology, monitor devnets and feature forks, track validator performance and visualize all this data in a clear and insightful way.
Allow validators to provide customer information privately
Nothing
Understanding the distribution of Ethereum execution layer and consensus layer clients used by validators is critical to ensuring a resilient and diverse network. While there are currently methods to estimate the distribution of Beacon Chain clients across validators, the same cannot be said for the distribution of execution clients. Additionally, there is no standard way to anonymously present the ELs and CLs used. This proposal aims to research and design a way to submit and extract this crucial data while potentially avoiding compromising user anonymity and network performance.
Validator-based anonymous data collection using ZK
Abhishek Kumar
There are nearly 900,000 validators on the Ethereum mainnet. This translates to a treasure trove of validator data just waiting to be captured. This data would allow us to better design the Ethereum protocol by understanding the pain points. But the fact is that we don’t have enough data on these validators. Sure, we have data dashboards like rated.network but they are incomplete. For example, we don’t have information on which clients the Ethereum node is using (reth, nimbus, teku), on which machine (arm64/linux), etc. Validator operators don’t want to expose too much information about their staking setups. This is the problem we are trying to solve. We plan to use ZK for data collection which allows validator operators to provide information while remaining anonymous.
Main platform extension
Growth
growthepie has a solid foundation providing reliable layer 2 data and block space analytics as well as content for end users, developers and investors. Our goal is to provide our users with the most neutral and comprehensive set of metrics, tools and knowledge to understand the ever-growing L2 space and make the ecosystem more transparent. To achieve this, we aim to expand the platform’s feature set, list more Ethereum layer 2s, include more metrics, block space analytics and knowledge content. All this while remaining funded by public goods, maintaining a reliable infrastructure for high demand as well as a responsive and fast user experience.
Standardized and participatory smart contract labels and ABIs
Growth
This proposal addresses the issue of isolated and non-standardized contract labeling datasets within the blockchain data community. By introducing a standardized data model for smart contract labels, including the ABI, we advocate for consolidation into a single, universally accessible database used by diverse data providers. Our solution goes beyond standardization, adding the community as a key entity in the labeling effort. We have identified that the long-term success of a comprehensive label database relies on community crowdsourcing, achieved by lowering the barriers to entry with more user-friendly interfaces and open API endpoints for seamless integration. This approach marks a decisive shift for smart contract labels towards a community-driven, standardized, and eventually decentralized public good.
Economic analysis of L2
Nothing
Rapid adoption of Layer 2 (L2) solutions requires a clear understanding of the cost-effectiveness and data needs of new chains. We aim to develop tools to provide data on L2 call data costs and the fees that L2 networks pay for L1 security. The magnitude of call data costs will also help study the dynamics of 4844. We hope to provide insight into the data needs of the largest expected consumer of blob space. Analyzing the current cost and profitability of rollups will provide all rollups with vital information to design competitive gas markets and increase the information available to rollup consumers to enable them to make informed choices about the architectures they rely on. This, combined with our other proposal on rollup security, will provide consumers with a solid basis for selecting rollup services at a known cost and risk. The data will also be effective in modeling and predicting the behavior of the data blob market in Ethereum. According to the document from Offchain Labs and the Ethereum Foundation We assume that the first five rollups by TVL will be classified as a “large rollup” in the near future and that their data release strategy will be to use EIP-4844. We can calculate what the historical cost of 4844 would have been assuming that rollups used 4844 from the outset and try to predict the market dynamics of 4844 in the near future, based on current and expected rollup usage. Finally, we will propose a standard to compare and evaluate compute capacity between EVM and non-EVM chains.
Analysis of the purpose of L2 and the economics of L2 security
Nothing
Rapid adoption of Layer 2 (L2) solutions requires a clear understanding of the associated risks for developers and users. We aim to develop tools to provide real-time data and assess these risks across different Layer 2 tiers. These tools will help manage the risk of Layer 2 networks forking from their canonical Layer 1 chain and Layer 2 blocks being blocked on Layer 1. A real-time asset risk tracking feature will also quantify and display assets at risk, providing a clear view of financial exposure. Through these tools and the associated dashboard, we aim to improve transparency and understanding of the Layer 2 ecosystem, fostering a safer and more informed community while encouraging Layer 2 tiers to push for the economic security they need.
Wallet Tags – Standardization and enrichment of Ethereum account labels for more transparency and utility
Function03 Laboratories
WalletLabels is a platform that simplifies the identification of on-chain wallets through custom labels. The need for clear, accessible, and actionable information about wallet behaviors is becoming increasingly important as the space grows and matures. Our intuitive interface allows users to easily search and categorize wallet addresses by name, label, or entity type, transforming anonymous hashes into meaningful information. We envision offering a labeling infrastructure that extends its value to a wide range of platforms, from block explorers to wallet services to consumer-facing applications.
