Datasets:
license: other
license_name: bsd-4-clause
license_link: LICENSE
language:
- en
task_categories:
- object-detection
tags:
- table-detection
- table-structure-recognition
- historical-documents
- weather-records
- scanned-documents
size_categories:
- n<1K
configs:
- config_name: coarse
data_files:
- split: train
path: coarse/train-*.parquet
- split: test
path: coarse/test-*.parquet
- config_name: fine
data_files:
- split: train
path: fine/train-*.parquet
- split: test
path: fine/test-*.parquet
GloSAT Table Dataset
Table structure recognition annotations for scanned historical meteorological logbook pages from the GloSAT project. Images are scanned pages from 9 archival sources spanning the 19th and early 20th centuries. Each image is annotated with table bounding boxes and per-cell bounding boxes with row/column indices and header flags.
This dataset supports table detection and table structure recognition (TSR) tasks on historical document images.
No transcribed cell content is included. This is a structure-only dataset: it provides spatial layout (bounding boxes and grid topology) but not the text values inside cells.
Configs
| Config | Description | Cells per table (mean) | Cells per table (max) |
|---|---|---|---|
coarse |
Merged cells treated as single units | 156 | 476 |
fine |
Each physical cell annotated individually | 488 | 2737 |
The two configs cover the same 499 images with the same train/test split. Use coarse for tasks that treat spanning cells as atomic units; use fine for tasks that require individual cell boundaries.
Splits
| Split | Images |
|---|---|
| train | 371 |
| test | 129 |
Schema
Each row represents one scanned page image.
| Field | Type | Description |
|---|---|---|
image_id |
string | Numeric image identifier (matches original Zenodo filenames) |
image |
Image | Embedded JPEG bytes |
width |
int32 | Image width in pixels |
height |
int32 | Image height in pixels |
source |
string | Source archive name (see provenance table below) |
tables |
Sequence | List of annotated tables on the page |
tables.bbox |
Sequence[int32] | Table bounding box: [xmin, ymin, xmax, ymax] in image pixel coordinates |
tables.type |
string | Table border style (e.g., semi-bordered) |
tables.cells |
Sequence | List of annotated cells within the table |
tables.cells.bbox |
Sequence[int32] | Cell bounding box: [xmin, ymin, xmax, ymax] |
tables.cells.row_start |
int32 | Zero-indexed start row |
tables.cells.row_end |
int32 | Zero-indexed end row (exclusive) |
tables.cells.col_start |
int32 | Zero-indexed start column |
tables.cells.col_end |
int32 | Zero-indexed end column (exclusive) |
tables.cells.header |
bool | True if the cell is a header cell |
All coordinates are in original image pixel space. 39% of train images contain more than one table per page.
Source provenance
| Source | Images | Description |
|---|---|---|
DWR |
93 | Daily Weather Reports |
Ben_Nevis |
97 | Ben Nevis Observatory records |
WR_10_years |
97 | 10-year weather registers |
WesTech_Rodgers |
82 | WesTech / Rodgers logbooks |
WR_Devon_Extern |
33 | Devon external weather registers |
20cr_Natal_Witnes |
26 | 20th Century Reanalysis: Natal Witness |
20cr_DWR_MO |
24 | 20th Century Reanalysis: DWR (Met Office) |
20cr_DWR_NOAA |
24 | 20th Century Reanalysis: DWR (NOAA) |
20cr_Kubota |
24 | 20th Century Reanalysis: Kubota |
Usage
from datasets import load_dataset
# Fine-grained cell annotations
ds = load_dataset("rootsautomation/GloSAT", "fine")
row = ds["train"][0]
print(row["image_id"], row["source"], row["width"], row["height"])
# Access table annotations
for i, bbox in enumerate(row["tables"]["bbox"]):
cells = row["tables"]["cells"][i]
print(f"Table {i}: bbox={bbox}, {len(cells['bbox'])} cells")
License
This dataset is released under a BSD 4-Clause license (see LICENSE). The 4-Clause variant includes an advertising clause: any materials or publications that use or reference this dataset must acknowledge the GloSAT project in their advertising or documentation.
Original data source: Zenodo record 5363457.
Citation
If you use this dataset, please cite the original GloSAT paper:
@inproceedings{glosat2021,
title = {GloSAT Historical Measurement Table Dataset: End-to-End Table Processing with Columns Delimited at Run-Time},
author = {Middleton, Stuart E. and Kordopatis-Zilos, Giorgos and Sheridan, Iain},
booktitle = {Proceedings of the 4th International Workshop on Historical Document Imaging and Processing (HIP)},
year = {2021},
doi = {10.5281/zenodo.5363457}
}