Unveiling Opportunities: The Ethereum Foundation’s Data Collection Grants Initiative

Apibara: open-source data platform Apibara This initiative aims to integrate Ethereum data (Execution + Consensus Layer) into Apibara, a publicly available data platform. Apibara enables developers and analysts to synchronize any onchain data with a target database or API. At present, we offer compatibility with PostgreSQL, MongoDB, Parquet, and webhooks. It’s straightforward to include support for additional integrations. Apibara emphasizes “real-time” utilization: initially, it backfills data, and subsequently, it synchronizes as the blockchain progresses. Developers can utilize the data with familiar tools. Our data synchronization protocol is independent of chains. Hence, we can support indexing both Execution Layer and Consensus Layer data. DotPics Anton Wahrstätter DotPics is an assortment of dashboards, data, and tools tailored for Ethereum. From a dashboard perspective, I also intend to develop one centered on 4844 blobs, their utilization, and the integration of blobs into mevboost.pics. Furthermore, I maintain several open-source data sets. Finally, my parser, designed for analyzing the CL, EL, MEV-Boost (Bids and Payloads), along with other elements, will soon be open-source. It is currently in the final testing phase. The ultimate parser will feature an intuitive GUI, enabling users to parse desired data as effortlessly as possible. Additionally, the parser directly tags validators with their corresponding entities (Lido, Coinbase, etc.), identifies potentially censorable transactions, and marks ETH2 deposits. The parser can be connected to a node and is ready for immediate use. Healthy Network Baselines Metrika The challenge we seek to address is the establishment of clear metrics and thresholds for defining a healthy Ethereum network. Given Ethereum’s dynamic and decentralized character, the entire community bears the responsibility for monitoring and maintaining its health. To achieve this, there must be consensus within the community regarding network health indicators, which includes the specific metrics to be tracked and the respective thresholds that indicate potential problems when the network approaches an unhealthy state. By utilizing Xatu, we will set strong health baselines for Ethereum’s peer-to-peer (P2P) network layer. Our objective is to document our discoveries, rationale, and in-depth descriptions of the selected metrics, thereby equipping the community with the insights necessary to protect Ethereum’s stability and health. MigaLabs Data Collection MigaLabs The Ethereum blockchain is in a constant state of transformation. It has undergone significant changes in the past, particularly with the shift from Proof of Work to Proof of Stake, and it is poised for substantial alterations in the future with the introduction of EIP 4844 and others. Grasping these changes and foreseeing potential bottlenecks is the primary task of blockchain researchers. For this purpose, we require a comprehensive suite of tools to collect large volumes of data, distill information from it, analyze observed trends, and represent them intuitively. The ambition behind this project is to create and refine tools aimed at: monitoring Ethereum nodes, tracking data propagation, identifying nodes within the network, revealing patterns in MEV, exploring DVT technology limits, overseeing devnets and feature forks, evaluating validator performance, and visually representing all this data in a clear and insightful manner. Enabling validators to share client information confidentially Nethermind Understanding the distribution of Ethereum’s execution-layer and consensus-layer clients utilized by validators is crucial for ensuring a resilient and varied network. While methods currently exist to estimate the Beacon Chain’s client distribution among validators, the same is not applicable for the execution client distribution. Additionally, no standardized approach exists for anonymously presenting which ELs and CLs are in use. This proposal aspires to research and design a method for submitting and retrieving this essential data while aiming to preserve user anonymity and maintain network performance. Confidential Validator Data Collection utilizing ZK Abhishek Kumar There are nearly 900k validators on the Ethereum mainnet. This represents a valuable reservoir of data regarding validators that is ready to be harnessed. This information would enable us to enhance the Ethereum protocol by identifying pain points. However, the stark reality is that we lack sufficient data on these validators. While data dashboards like rated.network exist, they are not comprehensive. For instance, we lack insights on the clients that the Ethereum node is operating (reth, nimbus, teku), and the type of machine (arm64/linux), etc. Validator operators prefer not to disclose extensive information about their staking configurations. This is the issue we are aiming to resolve. We intend to leverage ZK for data collection, allowing validator operators to provide insights while maintaining their anonymity. Core Platform Expansion Growthepie growthepie has a solid foundation offering dependable Layer 2 data and blockspace analysis, alongside content for end-users, developers, and investors. Our goal is to provide users with the most neutral and expansive set of curated metrics, tools, and information to comprehend the continually evolving L2 ecosystem and enhance its transparency. To achieve this, we plan to broaden the platform’s feature set, list additional Ethereum Layer 2s, incorporate more metrics, blockspace analysis, and knowledge content. Throughout this process, we will remain publicly funded for goods, ensuring a dependable infrastructure for high demand along with a swift and responsive user experience. Standardized and Crowdsourced Smart Contract Labels & ABIs Growthepie

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This proposition tackles the challenge of segregated and non-standardised contract labeling datasets within the blockchain data ecosystem. By implementing a uniform data model for smart contract labels, inclusive of ABI, we promote the amalgamation into a singular, universally reachable database employed by diverse data providers. Our approach transcends mere standardisation, incorporating the community as a crucial contributor in the labeling initiative. We have recognised that the sustained success of an extensive label database hinges on crowdsourcing from the community, accomplished by reducing entry barriers with more user-friendly interfaces and open API endpoints for effortless integration. This methodology signifies a fundamental transformation for smart contract labels towards a community-driven, standardised, and ultimately decentralised public asset. Economic evaluation of L2s Nethermind The swift uptake of Layer 2 solutions (L2s) demands a lucid comprehension of the profitability and data needs of the new chains. We aspire to develop tools to supply data for the calldata expenses of L2s and the fees that the L2 networks incur for L1 security. The volume of the calldata expenses will also facilitate the examination of the dynamics of 4844. We aim to present insights into the data necessities of the anticipated largest user of blob space. The analysis of the profitability and current costs of the rollups will furnish all rollups with essential information to design competitive gas markets and enhance the information accessible to consumers of the rollups to enable them to make well-informed decisions about the architectures they depend on. This, combined with our other proposal concerning rollup security, will provide consumers with a robust foundation to choose rollup services at a known expense and risk. Moreover, the data will also be advantageous for modelling and forecasting the behaviour of the data blob market within Ethereum. According to the article by Offchain Labs and the Ethereum Foundation, we presume that the top five rollups by TVL will soon be categorised as a ‘large roll-up’ and that their data posting strategy will involve EIP-4844. We can calculate what the historical cost of 4844 would have been, assuming the rollups employed 4844 from their inception and attempt to predict the market dynamics of 4844 in the forthcoming period, based on the rollups’ present and projected usages. Lastly, we will propose a standard for evaluating and benchmarking the computational capabilities between EVM and non-EVM chains. Examination of L2 Finality and the Economics of L2 Security Nethermind The swift implementation of Layer 2 solutions (L2s) necessitates a clear understanding of the associated hazards for both developers and users. We intend to create tools that provide real-time data and evaluate these risks across different L2s. The tools will address the potential for L2 networks to diverge from their L1 canonical chain, as well as the non-finalisation of L2 blocks on L1. A real-time asset risk tracking feature will also quantify and display the assets at stake, offering a transparent view of financial exposure. Through this tooling and its accompanying dashboard, we strive to enhance transparency and comprehension within the L2 ecosystem, fostering a safer and more informed community while motivating L2s to strive for the economic security they need. WalletLabels – Standardizing & Enriching Ethereum Account Labels for Clarity and Functionality Function03 Labs WalletLabels functions as a platform that streamlines the identification of on-chain wallets via custom labels. The necessity for clear, accessible, and actionable insights into wallet behaviour grows increasingly crucial as the space expands and evolves. Our user-friendly interface allows individuals to effortlessly search and classify wallet addresses by name, label, or entity type, transforming anonymous hashes into significant insights. We foresee providing a labeling infrastructure that enhances its value across a wide range of platforms—whether block explorers, wallet services, or consumer-focused applications.