Places · Public data

Places of interest in Europe

Shops, schools, hospitals, stations and cafés, with a category and a point.

Overture Maps Foundation, places theme · CDLA-Permissive-2.0 · commons_pubdata.places.places

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• 7,257,624rows
• Europecoverage
• Monthlyrefresh
• 10 Oct 2026last refreshed
• 5data files

Map Sample rows

Query it with DuckDB.

With an account Without an account

BashCopy

lhbox duckdb --catalog commons/pubdata

SQL · Pharmacies by countryCopy

SELECT p.country_code, count(*) AS pharmacies
FROM commons_pubdata.places.places AS p
WHERE p.category = 'pharmacy'
GROUP BY 1 ORDER BY 2 DESC;

Read it where you work.

Public, read-only data. With an account, lhbox duckdb attaches the catalog as commons_pubdata; an agent with the LakehouseBox connector opens it with open_public_catalog("commons/pubdata"). Without one, DuckDB reads the public files directly.

Example queries

• Pharmacies by country

  SELECT p.country_code, count(*) AS pharmacies
  FROM commons_pubdata.places.places AS p
  WHERE p.category = 'pharmacy'
  GROUP BY 1 ORDER BY 2 DESC;

• The ten nearest hospitals to a point (Madrid, Puerta del Sol)

  SELECT name, locality, round(6371 * 2 * asin(sqrt(pow(sin(radians(latitude - 40.4169) / 2), 2)
         + cos(radians(40.4169)) * cos(radians(latitude)) * pow(sin(radians(longitude + 3.7035) / 2), 2))), 2) AS km
  FROM commons_pubdata.places.places
  WHERE basic_category = 'hospital' AND latitude BETWEEN 40.2 AND 40.7 AND longitude BETWEEN -4.0 AND -3.4
  ORDER BY km LIMIT 10;

Know your columns.

Column	Type	Meaning
place_id	string	Overture GERS id of the place
name	string	primary name
basic_category	string	Overture's coarse category (e.g. restaurant, hospital, pharmacy_and_drug_store, elementary_school)
category	string	Overture's taxonomy category (the most specific)
category_path	string	the taxonomy path from general to specific, joined with ' > '
confidence	double	Overture's confidence that the place exists, 0.9 to 1

View all 18 columns

operating_status	string	open, permanently_closed or temporarily_closed when known
country_code	string	ISO 3166-1 alpha-2 of the address (joins reference.countries)
region	string	the address region as given (not always an ISO 3166-2 code)
locality	string	city or town
postcode	string	postal code
address	string	the street address as one line
longitude	double	WGS84 longitude
latitude	double	WGS84 latitude
geometry	geometry	the point (WGS84, longitude/latitude), for spatial joins and maps
website	string	the first website listed
brand	string	brand name for chain locations
overture_release	string	the release this row came from

Join keys: country_code.

Before you query.

1. Filter on basic_category for broad questions (restaurant, hospital, pharmacy_and_drug_store, elementary_school, high_school; list them with SELECT DISTINCT basic_category) and on category or category_path for specific ones (category = 'pharmacy').
2. Rows are stored in Hilbert order, so a box around an area reads little: a bounding box on longitude and latitude, or geometry && ST_MakeEnvelope(xmin, ymin, xmax, ymax), before any distance arithmetic.
3. geometry is an Iceberg v3 geometry column (DuckDB 1.5.6 or newer; PyIceberg 0.12 cannot load v3 geometry tables yet).
4. Coverage and freshness vary by country (Overture merges several providers); confidence 0.9 already drops most duplicates and stale entries, but a closed business can remain.

• Combine with Airports →Joins on country_code.
• Combine with Countries →Joins on country_code.
• Combine with Countries & regions →Joins on country_code.

Source & licence.

Source

Overture Maps Foundation, places theme

Licence

CDLA-Permissive-2.0 (a few sources CC0-1.0 or Apache-2.0; the per-record licence is in Overture's sources)

Attribution

© Overture Maps Foundation (CDLA-Permissive-2.0).

Coverage

Europe (EU-27, EFTA, the UK, the Western Balkans, the microstates, Ukraine, Moldova, Belarus), by address country; the latest Overture release

Refresh

monthly, the whole table replaced; source version overture 2026-09-23.1

Table

commons/pubdata · places.places · Iceberg v3 · browse the catalog

Recipe

pubdata/recipes/places.py, registry entry pubdata/registry/places.yaml

Source: Overture Maps Foundation, places theme · CDLA-Permissive-2.0 · Snapshot shown: 10 Oct 2026HTML for people. Markdown for agents.

# Places of interest in Europe

*Shops, schools, hospitals, stations and cafés, with a category and a point.*

Points of interest across Europe from Overture Maps' places theme: one row per place with its name, Overture's category (and the category path from general to specific), a confidence score, the address fields, a longitude and a latitude, and a website and brand when known. Kept where the address country is European and Overture's confidence is at least 0.9, about 7.7 million places.

## At a glance

| | |
|---|---|
| Table | `pubdata.places.places` |
| Category | Places · Places, Spatial, Europe |
| Rows | 7,257,624 |
| Size | 5 data file(s) |
| Iceberg format | v3 |
| Last refreshed | 2026-10-10T11:25:24Z |
| Source version | overture 2026-09-23.1 |
| Refresh cadence | monthly (replace) |
| Coverage | Europe (EU-27, EFTA, the UK, the Western Balkans, the microstates, Ukraine, Moldova, Belarus), by address country; the latest Overture release |

## Origin

- **Source:** [Overture Maps Foundation, places theme](https://docs.overturemaps.org/guides/places/)
- **Licence:** CDLA-Permissive-2.0 (a few sources CC0-1.0 or Apache-2.0; the per-record licence is in Overture's sources)
- **Attribution:** © Overture Maps Foundation (CDLA-Permissive-2.0).
- **Note:** Overture releases monthly; the release name is the source version. Measured on 2026-09-23.1, about 0.55 GB.
- **Recipe:** `pubdata/recipes/places.py` in the LakehouseBox repository; registry entry `pubdata/registry/places.yaml`.

## Schema

| column | type | description |
|---|---|---|
| `place_id` | string | Overture GERS id of the place |
| `name` | string | primary name |
| `basic_category` | string | Overture's coarse category (e.g. restaurant, hospital, pharmacy_and_drug_store, elementary_school) |
| `category` | string | Overture's taxonomy category (the most specific) |
| `category_path` | string | the taxonomy path from general to specific, joined with ' > ' |
| `confidence` | double | Overture's confidence that the place exists, 0.9 to 1 |
| `operating_status` | string | open, permanently_closed or temporarily_closed when known |
| `country_code` | string | ISO 3166-1 alpha-2 of the address (joins reference.countries) |
| `region` | string | the address region as given (not always an ISO 3166-2 code) |
| `locality` | string | city or town |
| `postcode` | string | postal code |
| `address` | string | the street address as one line |
| `longitude` | double | WGS84 longitude |
| `latitude` | double | WGS84 latitude |
| `geometry` | geometry | the point (WGS84, longitude/latitude), for spatial joins and maps |
| `website` | string | the first website listed |
| `brand` | string | brand name for chain locations |
| `overture_release` | string | the release this row came from |

**Join keys:** `country_code`.

## For agents

Filter on `basic_category` for broad questions (restaurant, hospital, pharmacy_and_drug_store, elementary_school,
high_school; list them with `SELECT DISTINCT basic_category`) and on `category` or `category_path` for specific ones
(`category = 'pharmacy'`). Rows are stored in Hilbert order, so a box around an area reads little: a bounding box on
longitude and latitude, or `geometry && ST_MakeEnvelope(xmin, ymin, xmax, ymax)`, before any distance arithmetic.
`geometry` is an Iceberg v3 geometry column (DuckDB 1.5.6 or newer; PyIceberg 0.12 cannot load v3 geometry tables
yet). Coverage and freshness vary by country (Overture merges several providers); `confidence` 0.9 already drops most duplicates and stale entries, but a closed business can remain.

## Example SQL (DuckDB)

```sql
-- pharmacies by country
SELECT p.country_code, count(*) AS pharmacies
FROM pubdata.places.places AS p
WHERE p.category = 'pharmacy'
GROUP BY 1 ORDER BY 2 DESC;
-- the ten nearest hospitals to a point (Madrid, Puerta del Sol)
SELECT name, locality, round(6371 * 2 * asin(sqrt(pow(sin(radians(latitude - 40.4169) / 2), 2)
       + cos(radians(40.4169)) * cos(radians(latitude)) * pow(sin(radians(longitude + 3.7035) / 2), 2))), 2) AS km
FROM pubdata.places.places
WHERE basic_category = 'hospital' AND latitude BETWEEN 40.2 AND 40.7 AND longitude BETWEEN -4.0 AND -3.4
ORDER BY km LIMIT 10;
```

## How to read it

Without an account, over HTTPS (the bucket is public):

```sql
INSTALL iceberg; LOAD iceberg; INSTALL httpfs; LOAD httpfs;
-- anonymous: the bucket is public, requests go unsigned, through the public-data cache
CREATE OR REPLACE SECRET pubdata (TYPE S3, ENDPOINT 'lakehousebox-public-data.b-cdn.net', URL_STYLE 'path', REGION 'us-east-1');
CREATE OR REPLACE VIEW places AS SELECT * FROM iceberg_scan('s3://commons--pubdata/places/places');
SELECT * FROM places LIMIT 10;
```

With a LakehouseBox account:

```bash
# with a LakehouseBox account (any organisation): the public catalog by name, read-only
lhbox duckdb --catalog commons/pubdata     # opens DuckDB attached as `commons_pubdata`
SELECT * FROM commons_pubdata.places.places LIMIT 10;
```

Public URL of the table's storage: `https://s3.lakehousebox.com/commons--pubdata/places/places/`. This card: `https://lakehousebox.com/pubdata/cards/places.md`; the page: https://lakehousebox.com/public-data/places. Every dataset as a table: `commons_pubdata.meta.datasets`; as Markdown: https://lakehousebox.com/public-data.md.