---
license: odc-by
pretty_name: "OP Stack unsafe-head observations and canonical-chain checks"
tags:
  - layer-2
  - rollup
  - sequencer
  - ethereum
  - reliability
  - blockchain
  - time-series
task_categories:
  - time-series-forecasting
size_categories:
  - 100K<n<1M
configs:
- config_name: l2_preconfirmation_checks
  data_files:
  - split: train
    path: e14_l2_preconf/**/*.parquet
  default: true
- config_name: collection_runs
  data_files:
  - split: train
    path: e0_run_manifest/**/*.parquet
---

# L2 sequencer preconfirmation observations

Periodic observations of unsafe and safe heads on selected OP Stack networks, with subsequent checks of sampled unsafe block hashes against the chain reported by the endpoint. The panel records coverage and detected changes to previously observed blocks.

## Contents

| Table | Record |
|---|---|
| `l2_preconfirmation_checks` | A heartbeat with head and check statistics, or a detected violation |

## Using the data

`row_type` separates heartbeats from violations. Use `n_checked` and `n_failed` to assess how many checks completed before interpreting a period with no detected violations.

`lag_blocks` measures the reported gap between unsafe and safe heads. Use it only where `safe_tag_plausible` is true. Some endpoints have returned stale or inconsistent safe tags, which can produce implausibly large lags.

Compare lag with each chain's own history. Different sequencer and batch-publication policies can produce different normal levels across networks.

## Limitations

- The configured coverage includes nine OP Stack chains. Results do not establish behaviour across other rollup architectures.
- Sampling can miss a block that is proposed and replaced between observations.
- Observations depend on public endpoint responses. A mismatch warrants investigation and is not, by itself, proof of a sequencer failure or an L1 finality failure.
- An unsafe head is an early chain view, not a universal transaction-level confirmation guarantee.
- No detected violations means none were found in completed checks; it does not establish uninterrupted reliability outside those checks.

## Files and access

Data is stored as Parquet files under `dataset/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 2026-08-26 to 2026-09-01. 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.

```python
from datasets import load_dataset

data = load_dataset("dataforge-labs/l2-preconfirmation-reliability",
                    "l2_preconfirmation_checks", 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.

<details>
<summary>File paths and compatibility</summary>

The table names above are Hugging Face dataset configurations. Each configuration reads the original Parquet files, whose paths remain unchanged for existing downloads and scripts. No records are copied, moved or renamed.

| Table name | Storage directory |
|---|---|
| `l2_preconfirmation_checks` | `e14_l2_preconf/` |
| `collection_runs` | `e0_run_manifest/` |

</details>