Data Collection Grant Round | Ethereum Foundation Blog

Apibara: Open Source Data Platform Boundaries This project aims to add ethereum data (execution and 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. Currently, we provide support for PostgreSQL, MongoDB, Parquet, and webhooks. It's easy to add support for more integrations. Apibara focuses on “inline” usage: it populates data first, then syncs it as the chain progresses. Developers can access data using the tools they already know. Our data sync protocol is chain-agnostic. For this reason, we can support indexing data from both the execution layer and the consensus layer. Dot images Anton Wahrstätter DotPics is a collection of dashboards, data, and tools for ethereum. On the dashboard side, I plan to build one that focuses on 4844 blobs, blob usage, as well as incorporating blobs into mevboost.pics. Additionally, there are open source datasets that I maintain. Lastly, my analyzer for analyzing CL, EL, MEV-Boost (bids and payloads), as well as other things, will soon be open sourced. It is currently in the final stage of testing. The final analyzer will have a simple graphical user interface that will allow everyone to analyze the desired data in the simplest way 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 connected to a node and is ready to go. ethereum/dashboard/network/network-health?tr=1w”>Baselines of a healthy network Metric The problem we aim 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 for monitoring and preserving 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 drifting into 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, rationales, and detailed descriptions of the selected metrics, empowering the community with the knowledge to safeguard the stability and well-being of ethereum. MigaLabs Data Collection MigaLabs 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 substantially in the future, with the arrival of EIP 4844 and others. Understanding those changes and anticipating potential bottlenecks is the main job of blockchain researchers. But for that we need a wide range of tools, in order to collect massive amounts of data, extract insights 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 nodes in the network, reveal 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 client information privately Hellish Mind Understanding the distribution of ethereum execution layer and consensus layer clients used by validators is vital 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 about the distribution of execution clients. Furthermore, there is no standard means to anonymously show which EL and CL are being used. This proposal aims to investigate and design a way to send and extract this crucial data while avoiding compromising user anonymity and network performance. Collecting anonymous validation data using ZK Abhishek Kumar There are close to 900,000 validators on the ethereum mainnet. This translates to a treasure trove of validator data that is just waiting to be captured. This data would allow us to better design the ethereum protocol by understanding the pain points. But the harsh reality 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 to allow validator operators to provide information while remaining anonymous. Expansion of the central platform Foot growth growthepie has a solid foundation providing reliable Layer 2 data and block space analysis as well as content for end users, developers, and investors. Our goal is to provide our users with the most comprehensive and neutral set of metrics, tools, and insights to understand the ever-growing L2 space and make the ecosystem more transparent. To do so, we aim to expand the platform’s feature set, include more Layer 2 ethereum, include more metrics, block space analysis, and knowledge content. All of this while maintaining public good funding, maintaining a reliable infrastructure for high demand, as well as a responsive and fast user experience. Standardized and collaborative smart contract tags and ABIs Foot growth This proposal addresses the issue of siloed and non-standardized contract tagging datasets within the blockchain data community. By introducing a standardized data model for smart contract tags, including ABI, we advocate for consolidation into a single, universally accessible database used by multiple data providers. Our solution goes beyond standardization, adding the community as a key entity in the tagging effort. We have identified that the long-term success of a comprehensive tag database depends on community crowdsourcing, achieved by lowering barriers to entry with more user-friendly interfaces and open API endpoints for seamless integration. This approach marks a fundamental shift for smart contract tags towards a community-driven, standardized, and ultimately decentralized public good. Economic analysis of L2 Hellish Mind The rapid adoption of Layer 2 (L2) solutions requires a clear understanding of the cost effectiveness and data requirements of new chains. We aim to develop tools to provide data on L2 call data costs and the fee that L2 networks pay for L1 security. The size of call data costs will also help study the dynamics of 4844. We hope to provide insight into the data requirements of the largest expected consumer of blob space. Analyzing the current cost effectiveness and costs of rollups will give all rollups vital information for designing competitive gas markets and increase the information available to rollup consumers to enable them to make informed decisions about the architectures they rely on. This, along with our other proposal on rollup security, will give consumers 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 on ethereum. According to The article by Offchain Labs and the ethereum Foundation We assume that the top 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 the rollups used 4844 since their genesis and attempt to predict the market dynamics of 4844 in the near future, according to the current and expected uses of the rollups. Finally, we will propose a standard to compare and evaluate computational capacity between EVM and non-EVM chains. Analysis of L2 purpose and economics of L2 security Hellish Mind The rapid adoption of Layer 2 (L2) solutions requires a clear understanding of the associated risks for both developers and users. Our goal is to develop tools to provide real-time data and assess these risks across multiple L2s. The tools will address the risk of L2 networks forking from their canonical L1 chain and L2 blocks not finalizing on L1. A real-time asset risk monitoring feature will also quantify and display assets at risk, providing a clear view of financial exposure. Through these tools and the associated dashboard, we strive to improve transparency and understanding across the L2 ecosystem, fostering a more secure and informed community and encouraging L2s to drive the economic security they need. Wallet Tags – Standardization and enrichment of ethereum account labels for transparency and utility Function03 Laboratories WalletLabels is a platform that simplifies on-chain wallet identification through custom labels. The need for clear, accessible, and actionable insights into wallet behavior becomes 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 delivering a labeling infrastructure that extends its value to a broad spectrum of platforms, be it block explorers, wallet services, or consumer-facing applications.