dataforge-labs/ethereum-attestation-pool

Ethereum attestation pool

Slot-level observations comparing attestations visible in a consensus client's pending pool with attestations subsequently included in blocks. The panel supports analysis of local pool coverage and inclusion counts.

Contents

Table	Record
ethereum_attestation_observations	Attester-slot counts observed pending and included, with their difference and collection coverage

Using the data

attesters_seen_in_pool counts attester slots observed in the pending pool. attesters_included counts those included in blocks. attesters_net_never_included is the signed difference between these counts.

Negative differences can occur because blocks contain attestations the observed client did not hold during polling. Despite its name, attesters_net_never_included does not identify individual attestations that permanently failed to reach the chain.

Filter on window_closed when an analysis requires a fully observed inclusion window. Use n_polls_seen to assess observation coverage, and examine the distribution across slots before combining counts.

Limitations

• The panel observes one consensus client's pool. Absence from this client does not imply absence from the network.
• Counts represent attester slots, not identified validators. They cannot establish the performance of a particular validator.
• Attestations that arrive and are included between polls may be missed.
• Slots near the end of a collection window may have incomplete inclusion counts and window_closed = false.

Files and access

Data is stored as Parquet files under table_name/YYYY/MM/, with partitions for collection windows. Each measurement table has a fixed 7-day sample beginning at its configured collection start date. The sample windows in this repository span 2026-08-28 to 2026-09-03. Availability within each window depends on successful collection. The public sample dates remain fixed as additional history accumulates privately. Contact DataForge through the discussions tab to enquire about additional history.

Load a table

Install datasets and pandas to run this example. The train split contains all observations in the selected table; it is not a predefined modelling split.

from datasets import load_dataset

data = load_dataset("dataforge-labs/ethereum-attestation-pool",
                    "ethereum_attestation_observations", split="train")
df = data.to_pandas()

Coverage

collection_runs records collection windows, poll counts and failures. It is published in full and may cover dates beyond the fixed data sample. Collection gaps are not interpolated. Use this table together with measurement timestamps and error fields to assess coverage.

License and contact

The public sample is published under ODC-BY. Attribute it to "DataForge (dataforge-labs)". For questions about the data or access to additional history, open a discussion in this repository.

Earlier file paths

Each table is stored under a directory with the same descriptive name. The file contents and date partitions are unchanged. Scripts using an earlier directory name should use the corresponding table name below, or pin downloads to revision before-folder-rename-20260915 to access the original layout. Internal collector IDs are retained in the private archive and may appear in raw coverage records.

Current table and directory	Earlier directory
ethereum_attestation_observations	e18_attestation_pool/
collection_runs	e0_run_manifest/