londons-pulse-moh / README.md
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Fix table-to-scan alignment and preserve unresolved exports
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---
language:
- en
license: cc-by-nc-4.0
task_categories:
- image-to-text
- image-classification
pretty_name: 'London''s Pulse: MOH Reports (page images + OCR text)'
tags:
- archives
- glam
- historical
- iiif
- lam
- libraries
- medical-officer-of-health
- ocr
- public-health
- table-extraction
- tables
- wellcome-collection
dataset_info:
config_name: tables
features:
- name: image
dtype: image
- name: page_type
dtype: string
- name: table_ground_truth
dtype: string
- name: n_tables_on_page
dtype: int32
- name: b_number
dtype: string
- name: page_index
dtype: int32
- name: printed_page
dtype: int32
- name: source_collection
dtype: string
- name: label_source
dtype: string
- name: split
dtype: string
- name: signals
dtype: string
splits:
- name: train
num_bytes: 448527779
num_examples: 2520
- name: validation
num_bytes: 52884161
num_examples: 302
- name: test
num_bytes: 56707410
num_examples: 327
download_size: 554397290
dataset_size: 558119350
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- config_name: tables
data_files:
- split: train
path: tables/train-*
- split: validation
path: tables/validation-*
- split: test
path: tables/test-*
---
# London's Pulse: Medical Officer of Health reports (page images + OCR text)
Page-level scans of the Wellcome Collection [**London's Pulse**](https://wellcomelibrary.org/moh/)
Medical Officer of Health (MOH) reports (1848–1972), paired with OCR text, per-report
licence, and full provenance. Built for **OCR / VLM / document-understanding** work on real
historical public-health records — dense statistical tables, mixed layouts, century-old print.
## Configs
| config | rows | what |
|---|---|---|
| `default` | 391,964 pages / 4,886 reports | every **page image** + its report's OCR text + licence |
| `tables` | 3,149 pages / 288 reports | selected page images paired with 3,980 machine-extracted tables; silver labels for page-type training and exploratory table-extraction evaluation |
```python
from datasets import load_dataset
# full corpus (stream — it's ~110 GB)
ds = load_dataset("biglam/londons-pulse-moh", split="train", streaming=True)
# tables subset (small; image + silver table targets)
tab = load_dataset("biglam/londons-pulse-moh", "tables", split="test")
```
## `default` config — columns
| column | type | description |
|---|---|---|
| `image` | `Image` | the page scan (full native resolution) |
| `b_number` | `string` | Wellcome report id (join key) |
| `page_index` | `int32` | 1-based page (scan) number within the report |
| `n_pages` | `int32` | total pages in the report |
| `report_text` | `string` | OCR text of the **whole report** (see caveat) |
| `license` | `string` | normalised image licence (all `cc-by-nc` here) |
| `table_ground_truth` | `string` | reserved (empty in `default`; populated in the `tables` config) |
| `signals` | `string` | JSON provenance (`manifest_url`, `image_service_id`, size/format, `license_raw`, multi-volume linkage) |
> [!IMPORTANT]
> **`report_text` is report-level, not page-aligned** — the source OCR is a flat per-report
> dump with no reliable page boundaries, so the same full-report text repeats across every
> page of that report. Group/dedupe by `b_number`.
## `tables` config — columns
One row per scan with at least one matched table from Wellcome's machine-extracted
export. The attached tables are a **selected subset**, not an exhaustive annotation of
every table visible on the page. The CSV content remains uncorrected silver data.
Use for `table` page-type training or exploratory OCR/VLM evaluation with that limitation.
| column | type | description |
|---|---|---|
| `image` | `Image` | the page scan |
| `page_type` | `string` | `"table"` |
| `table_ground_truth` | `string` | JSON list of `{table_id, csv}` — the extracted table(s) on that page |
| `n_tables_on_page` | `int32` | number of attached export tables; may be fewer than the tables visible on the page |
| `b_number`, `page_index`, `printed_page` | | report id, 1-based scan index, original numeric printed-page value (nullable when regrouped values differ); exact export labels are in `signals.export_page_labels` |
| `source_collection`, `label_source`, `split`, `signals` | | provenance (`label_source="table-export"`) |
The original selection spans all 12 decades. Train/validation/test assignments remain
grouped by report, with no report shared across splits. After the September 2026 alignment
repair there are 2,520 / 302 / 327 rows respectively. Page counts increased because tables
previously conflated by repeated printed-page numbers now occupy separate scans.
Alignment uses each table's content against **every page's ALTO in its report**;
numeric canvas labels alone do not decide the match. The automated rule requires
IDF-weighted token containment ≥0.70, a margin ≥0.10 over the next-best scan, and at least
eight distinct content tokens. Two low-margin matches were retained after explicitly
recorded agent visual checks. These scores measure agreement with source OCR, not the
probability of a correct annotation. Limited image checks supplement the automated pass;
the entire dataset has not been manually verified.
The [alignment audit](audits/table-alignment-2026-09-09/README.md) accounts for all 4,086
original table items: 3,529 retained on their original scan, 451 moved, and 106 unresolved.
Unresolved items are excluded from the image/table config and preserved with their original
CSV content in [unresolved.jsonl](audits/table-alignment-2026-09-09/unresolved.jsonl).
Table IDs, CSV strings and original report split assignments are conserved across the
config and that side artifact. The `default` corpus is unchanged.
> [!NOTE]
> **Target quality — silver, not gold.** These tables were extracted by OCR/table recognition,
> not hand-transcribed. Known errors include incorrect digits, lost fractions, noisy captions
> and labels, flattened headers, shifted or missing cells, and inconsistent nil markers.
> Correcting the scan association does **not** correct those errors. Neither exact numeric
> scoring nor fuzzy text matching by itself accounts for this noise. Use an independently
> reviewed reference set for headline evaluation results. The original CSV strings, including
> any literal escaped line endings, are preserved; the repair script interprets those escapes
> only when parsing content for alignment.
## Provenance & reproducibility
- **Images**: Wellcome [IIIF Presentation v2 API](https://iiif.wellcomecollection.org/),
keyed on each report's b-number. `default` uses native resolution; `tables` retains the
existing approximate 800/1,000-pixel width convention, including for replacement scans.
Actual dimensions (including IIIF rounding differences) are recorded in `signals.image_size`.
- **Text** (`default`): the bulk `Fulltext.zip` corpus from
[wellcomelibrary.org/moh](https://wellcomelibrary.org/moh/), joined on b-number.
- **Tables** (`tables`): Wellcome's `All_Report_Tables` export (~275k machine-extracted
tables). The original numeric-label resolver conflated duplicate and irregular printed
page labels. The [repair script](scripts/repair_table_alignment.py) performs report-wide
ALTO content matching and preserves the original export payloads.
- `signals` records the manifest and image service for each page. In `tables` it also
records the canvas label, export-page labels, image dimensions, source dataset revision
and alignment audit location. Per-table decisions and source checksums are in the audit.
## Licence
Page **images** are **CC-BY-NC 4.0** (per Wellcome's IIIF manifests; per-row `license` +
`signals.license_raw`). The OCR **text** corpus is CC-BY 4.0; the extracted-tables export is
CC-BY 4.0. Reports whose image licence was not open were excluded. **Reuse is
non-commercial**, with attribution to **Wellcome Collection**.
| licence | pages (`default`) |
|---|---|
| cc-by-nc | 391,964 |
## Source & attribution
Wellcome Collection, *London's Pulse: Medical Officer of Health reports 1848–1972*.
Images: `iiif.wellcomecollection.org` · Text/tables: `wellcomelibrary.org/moh`.
## Intended uses
Historical OCR/VLM evaluation, document layout analysis, page-type classification, and
structured extraction from century-old public-health tables (disease incidence, mortality).
The `tables` config provides candidate material for image→table extraction evaluation;
reliable headline results require independently reviewed references.