fsq-os-places: Dataset Card

Foursquare OS Places is now a gated dataset on Hugging Face. Read more about why we are making this change here: https://medium.com/@foursquare/evolving-fsq-os-places-fa7a3f5197cd

Access FSQ OS Places

With Foursquare’s Open Source Places, you can access free data to accelerate geospatial innovation and insights. View the Places OS Data Schemas for a full list of available attributes.

Prerequisites

In order to access Foursquare's Open Source Places data, it is recommended to use Spark. Here is how to load the Places data in Spark from Hugging Face.

• For Spark 3, you can use the read_parquet helper function from the HF Spark documentation. It provides an easy API to load a Spark Dataframe from Hugging Face, without having to download the full dataset locally: python places = read_parquet("hf://datasets/foursquare/fsq-os-places/release/dt=2026-09-15/places/parquet/*.parquet")
• For Spark 4, there will be an official Hugging Face Spark data source available.

Alternatively you can download the following files to your local disk or cluster:

• Parquet Files:
• Places - release/dt=2026-09-15/places/parquet
• Categories - release/dt=2026-09-15/categories/parquet

Hugging Face provides the following download options.

Example Queries

The following are examples on how to query FSQ Open Source Places using Athena and Spark:

• Filter Categories by the parent level
• Filter out non-commercial venues
• Find open and recently active POI

Filter by Parent Level Category

SparkSQL ```sql SparkSQL WITH places_exploded_categories AS ( -- Unnest categories array SELECT fsq_place_id, name, explode(fsq_category_ids) as fsq_category_id FROM places ), distinct_places AS ( SELECT DISTINCT(fsq_place_id) -- Get distinct ids to reduce duplicates from explode function FROM places_exploded_categories p JOIN categories c -- Join to categories to filter on Level 2 Category ON p.fsq_category_id = c.category_id WHERE c.level2_category_id = '4d4b7105d754a06374d81259' -- Restaurants ) SELECT * FROM places WHERE fsq_place_id IN (SELECT fsq_place_id FROM distinct_places)

### Filter out Non-Commercial Categories

**SparkSQL**
```sql SparkSQL
SELECT * FROM places
WHERE arrays_overlap(fsq_category_ids, array('4bf58dd8d48988d1f0931735',    -- Airport Gate 
'62d587aeda6648532de2b88c', -- Beer Festival 
'4bf58dd8d48988d12b951735', -- Bus Line 
'52f2ab2ebcbc57f1066b8b3b', -- Christmas Market 
'50aa9e094b90af0d42d5de0d', -- City 
'5267e4d9e4b0ec79466e48c6', -- Conference 
'5267e4d9e4b0ec79466e48c9', -- Convention 
'530e33ccbcbc57f1066bbff7', -- Country 
'5345731ebcbc57f1066c39b2', -- County 
'63be6904847c3692a84b9bb7', -- Entertainment Event 
'4d4b7105d754a06373d81259', -- Event 
'5267e4d9e4b0ec79466e48c7', -- Festival 
'4bf58dd8d48988d132951735', -- Hotel Pool 
'52f2ab2ebcbc57f1066b8b4c', -- Intersection 
'50aaa4314b90af0d42d5de10', -- Island 
'58daa1558bbb0b01f18ec1fa', -- Line 
'63be6904847c3692a84b9bb8', -- Marketplace 
'4f2a23984b9023bd5841ed2c', -- Moving Target 
'5267e4d9e4b0ec79466e48d1', -- Music Festival 
'4f2a25ac4b909258e854f55f', -- Neighborhood 
'5267e4d9e4b0ec79466e48c8', -- Other Event 
'52741d85e4b0d5d1e3c6a6d9', -- Parade 
'4bf58dd8d48988d1f7931735', -- Plane 
'4f4531504b9074f6e4fb0102', -- Platform 
'4cae28ecbf23941eb1190695', -- Polling Place 
'4bf58dd8d48988d1f9931735', -- Road 
'5bae9231bedf3950379f89c5', -- Sporting Event 
'530e33ccbcbc57f1066bbff8', -- State 
'530e33ccbcbc57f1066bbfe4', -- States and Municipalities 
'52f2ab2ebcbc57f1066b8b54', -- Stoop Sale 
'5267e4d8e4b0ec79466e48c5', -- Street Fair 
'53e0feef498e5aac066fd8a9', -- Street Food Gathering 
'4bf58dd8d48988d130951735', -- Taxi 
'530e33ccbcbc57f1066bbff3', -- Town 
'5bae9231bedf3950379f89c3', -- Trade Fair 
'4bf58dd8d48988d12a951735', -- Train 
'52e81612bcbc57f1066b7a24', -- Tree 
'530e33ccbcbc57f1066bbff9', -- Village
)) = false

Find Open and Recently Active POI

SparkSQL sql SparkSQL SELECT * FROM places p WHERE p.date_closed IS NULL AND p.date_refreshed >= DATE_SUB(current_date(), 365);

Licensing information

The dataset is available under the Apache 2.0 license

Appendix

Non-Commercial Categories Table