Datasets:
Download deposit/NOTICE.md from msolarz/StatMapCorpus: direct link, hf CLI and curl.
- Browser
- Download file 3.97 kB
-
https://huggingface.co/datasets/msolarz/StatMapCorpus/resolve/main/deposit/NOTICE.md
- Command line
-
hf download hf://datasets/msolarz/StatMapCorpus/deposit/NOTICE.md
-
curl -L -o NOTICE.md https://huggingface.co/datasets/msolarz/StatMapCorpus/resolve/main/deposit/NOTICE.md
NOTICE
StatMapCorpus distributes annotations, identifiers and image embeddings only. It does
not contain, mirror or redistribute any images. Each record points to an image hosted by a
third party (url). It also carries verification surrogates (sha256, phash,
image_width, image_height) that let a user confirm that a file retrieved later is the
file that was annotated.
Provenance
Common Crawl → CommonPool / DataComp → MapPool → StatMapCorpus
- MapPool: 75,890,407 map-like images identified in CommonPool, released under
CC BY 4.0.
- Reference: Schnürer, R. (2024). MapPool – bubbling up an extremely large corpus of maps for AI. Abstracts of the ICA 8, 22. https://doi.org/10.5194/ica-abs-8-22-2024
- Available at https://huggingface.co/datasets/sraimund/MapPool
- StatMapCorpus takes
uid,urland the CLIP ViT-L/14 image embeddings from MapPool, which carries them from CommonPool. - Modified: a subset was selected and annotated anew.
- CommonPool / DataComp: an index of image–text pairs from Common Crawl.
- Reference: Gadre, S. Y. et al. (2023). DataComp: in search of the next generation of multimodal datasets. Advances in Neural Information Processing Systems 36, 27092–27112.
- Its authors distribute the url–text samples and metadata under CC BY 4.0. They state that the individual images remain under their own copyrights, that the index is provided as is, and that any content downloaded from it is used at the user's own risk and subject to the terms or copyright limitations accompanying that content.
Like the collections it derives from, StatMapCorpus stores links rather than images, for copyright reasons.
Neither the author of MapPool nor the DataComp authors are affiliated with StatMapCorpus or endorse it.
Licensing
| Component | Licence |
|---|---|
Annotations, metadata, documentation (including candidates.parquet and validation.csv) |
CC BY 4.0: https://creativecommons.org/licenses/by/4.0/legalcode |
download_images.py |
MIT: see the licence header in the file |
| CLIP embeddings | derived from MapPool, CC BY 4.0 (attribution to MapPool required) |
| Source images | Rights remain with their original owners. Not redistributed and not licensed here. |
Downloading images retrieves files directly from their original hosts. Whether a given image may be used for a given purpose depends on that image's own copyright status, not on this dataset's licence. Users are responsible for their own compliance.
Removal requests
Rights holders. Removal requests are honoured.
- Write to Marta Solarz, m.solarz2@uw.edu.pl, Faculty of Geography and Regional
Studies, University of Warsaw, giving the
uidorurlof the affected record. - Requests are acknowledged within 30 days.
- The affected records are removed and a corrected version of the dataset is published, without waiting for a scheduled release.
Personal data. The images were collected by CommonPool from the public web, and an audit of CommonPool found personal information in the wider collection (Hong et al. 2025, https://arxiv.org/abs/2506.17185). StatMapCorpus does not redistribute images and consists of maps rather than photographs of people. Even so, a linked image may contain personal data. Data subjects may request erasure of a record under Art. 17 GDPR, either at the address above or through the University of Warsaw Data Protection Officer at iod@adm.uw.edu.pl.
Because the dataset contains no images, removal means deleting the identifier, its annotations and its embedding from the dataset. The image itself remains under its owner's sole control at all times.
Citation
Solarz, Marta, 2026, "StatMapCorpus: 23,549 English-language statistical maps from MapPool, annotated by thematic map type using vision-language models", https://doi.org/10.58132/FSJGSP, Dane Badawcze UW, V2.