docs/source_one_dome.md

# Source One: DOME Baseline Data

Prepared: 2026-07-02 UTC

## Purpose

DOME is the existing local market-data corpus and remains the audit/baseline source for the strategy stack. It is not being replaced. It gives us continuity with the already-built reconstructed windows, Binance and Chainlink joins, labels, and older research artifacts.

Canonical local root:

```text
/home/Binance_Chainlink_Data/isolated_balanced_pm2s
```

## Local Layers Observed

The current DOME corpus has three relevant layers:

- `reconstructed/{ASSET}/date=YYYY-MM-DD/window_*.jsonl.gz`
- `raw/orderbooks/{ASSET}/date=YYYY-MM-DD/window_*_{yes,no}.json.gz`
- `raw/trades/{ASSET}/date=YYYY-MM-DD/window_*_{yes,no}.json.gz`

Observed inventory from the local filesystem:

| Layer | Assets | Date coverage | Shape |
|---|---|---|---|
| `reconstructed` | BTC, ETH, SOL, XRP | BTC starts `2026-02-13`; ETH/SOL/XRP start `2026-02-19`; all extend to `2026-05-31` locally | 1 Hz window files, usually up to 288 five-minute windows per day |
| `raw/orderbooks` | BTC, ETH, SOL, XRP | `2026-03-16` through `2026-05-31` locally | YES and NO raw orderbook files per market window |
| `raw/trades` | BTC, ETH, SOL, XRP | `2026-03-16` through `2026-05-31` locally | YES and NO raw trade files per market window |

Exact generated counts are maintained in:

```text
/home/Data_Collection_v2/catalog/dome_inventory.csv
/home/Data_Collection_v2/catalog/market_data_catalog.json
```

## Strengths

DOME is strong for baseline research and cross-checks:

- It already matches the existing strategy research code and reconstructed-frame loaders.
- It covers multiple assets: BTC, ETH, SOL, XRP.
- It includes reconstructed 1 Hz five-minute windows for large historical ranges.
- It includes raw YES and NO books for many March-May windows, which is important for validating two-leg YES/NO parity.
- It is integrated with the older Binance/Chainlink feature and resolution workflows.
- It is useful as a fallback when another source has missing archives or questionable transforms.

## What DOME Is Good For

Use DOME for:

- Baseline backtests where the old 1 Hz frame interface is expected.
- Validating PMData-derived YES/NO ladders against real DOME YES/NO books.
- Checking top-of-book agreement across sources.
- Comparing reconstructed 1 Hz behavior with sub-second PMData behavior.
- Maintaining compatibility with older Binance/Chainlink and resolution labels.
- Fallback or patching for isolated PMData archive gaps.

## Limitations

DOME is weaker than PMData for execution-grade maker/taker fill simulation:

- Reconstructed windows are 1 Hz, while the strategy plan needs sub-second book and trade-event replay.
- The reconstructed NO side can be synthetic in some corpus products; two-leg math must validate against raw real NO books.
- Raw trade quality and temporal density vary by date; some periods are tape-dense and some are patchy.
- Queue position cannot be known exactly from DOME alone.
- It is not as cleanly packaged for date-range archival and re-download as the PMData daily ZIP structure.

## Strategy Role

DOME should remain the audit and baseline source.

Recommended uses in the V3 plan:

- `data/twosided.py`: compatibility layer for 1 Hz frames.
- Source validation: compare PMData top-of-book and derived YES/NO ladders against DOME raw books.
- Acceptance testing: confirm PMData adapter output agrees with DOME on overlapping windows.
- Fallback: use DOME only where PMData is missing and the fallback is explicitly marked.

Do not use DOME alone as the final execution-quality source for maker queue-fill simulation unless the test is explicitly a baseline or compatibility run.