Datasets:

Outerview
/

underground-fire-hydrant

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
title: string
description: string
version: string
row_count: int64
files: struct<data.parquet: struct<path: string, size_bytes: int64>, data.geojson: struct<path: string, siz (... 67 chars omitted)
  child 0, data.parquet: struct<path: string, size_bytes: int64>
      child 0, path: string
      child 1, size_bytes: int64
  child 1, data.geojson: struct<path: string, size_bytes: int64>
      child 0, path: string
      child 1, size_bytes: int64
  child 2, data.csv: struct<path: string, size_bytes: int64>
      child 0, path: string
      child 1, size_bytes: int64
repository: string
publisher: string
to
{'version': Value('string'), 'title': Value('string'), 'publisher': Value('string'), 'repository': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              title: string
              description: string
              version: string
              row_count: int64
              files: struct<data.parquet: struct<path: string, size_bytes: int64>, data.geojson: struct<path: string, siz (... 67 chars omitted)
                child 0, data.parquet: struct<path: string, size_bytes: int64>
                    child 0, path: string
                    child 1, size_bytes: int64
                child 1, data.geojson: struct<path: string, size_bytes: int64>
                    child 0, path: string
                    child 1, size_bytes: int64
                child 2, data.csv: struct<path: string, size_bytes: int64>
                    child 0, path: string
                    child 1, size_bytes: int64
              repository: string
              publisher: string
              to
              {'version': Value('string'), 'title': Value('string'), 'publisher': Value('string'), 'repository': Value('string')}
              because column names don't match

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Underground Fire Hydrants (OSM) - 30,000-record Geospatial Sample

A free, ready-to-use sample of 30,000 geolocated underground fire hydrants (current openstreetmap snapshot), published by Outerview.

Underground fire hydrants mapped by OpenStreetMap contributors, with coordinates and the original OSM tags preserved.

This is a 30,000-record sample of a much larger collection (about 1,089,000 source records). Need the full dataset, other places or years, or live search? See the Outerview atlas.

At a glance


Records	30,000
Period	Current OpenStreetMap snapshot
Geometry	Point, WGS 84 (EPSG:4326)
Formats	Parquet, GeoJSON, CSV
Publisher	Outerview

Quick start

from datasets import load_dataset

ds = load_dataset("parquet", data_files="hf://datasets/Outerview/underground-fire-hydrant/data.parquet", split="train")
print(ds)
print(ds[0])

import pandas as pd
import json

df = pd.read_parquet("hf://datasets/Outerview/underground-fire-hydrant/data.parquet")
df["properties"] = df["properties"].apply(json.loads)
df[["latitude", "longitude"]].describe()

Search millions more geographic features

Outerview provides developers and AI systems access to millions of geographic features and geolocated imagery spanning infrastructure, places, roads, buildings, nature and community issues.

Build with Outerview

Geographic Feature List — browse geographic features available through Outerview
Outerview — programmable infrastructure for Earth
Developer Documentation — APIs, tools, guides, and examples
SDK — build geographic capabilities directly into applications
CLI — work with geographic search and spatial data from the terminal
MCP — connect geographic search and spatial tools to AI agents

Use cases

Emergency-response and fire-safety coverage analysis
Insurance and risk modelling
Water-network and infrastructure planning
Training detection and geolocation models

Schema

Column	Type	Description
`id`	string	Stable identifier for the record in the source table.
`sample`	boolean	Reserved flag for optional image samples; false for source-table exports.
`latitude`	float64	Latitude in decimal degrees (WGS 84).
`longitude`	float64	Longitude in decimal degrees (WGS 84).
`geometry_wkb`	binary	Record geometry encoded as Well-Known Binary for spatial workflows.
`media_url`	string	URL of associated imagery when available; usually empty for this dataset.
`attribution`	string	Attribution text for the contributing source.
`source`	string	Source or provider label.
`properties`	string	JSON-encoded object with the source-specific fields (see Properties).

Properties

The properties column is a JSON string holding the original source attributes. The most common keys in this sample:

Key	Example value
`osm_id`	`10159498218`
`tag_name`	`fire_hydrant:type`
`label_name`	`underground`
`fire_hydrant:type`	`underground`
`emergency`	`fire_hydrant`
`fire_hydrant:position`	`sidewalk`
`survey:date`	`2018-09-27`
`water_source`	`main`
`flow_rate`	`122`
`couplings`	`1`
`note`	`National-Land Numerical Information (Public Faci`
`addr:street`	`Stubaier Höhenweg (Nr. 4)`

Keys vary by record and source; not every field is populated for every row.

Files

Methodology

Records are exported directly from the Outerview geographic index, ordered by identifier and capped at 30,000 rows. Coordinates are WGS 84. Source fields are preserved in properties without reinterpretation. Inclusion means a record appeared in the contributing public dataset; it was not independently verified.

Sources and attribution

OpenStreetMap contributors (ODbL 1.0)
Prepared and distributed by Outerview

License

Contains information from OpenStreetMap, made available under the Open Database License (ODbL) 1.0. Attribute OpenStreetMap contributors and keep derived databases under ODbL.

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Total file size:

105 MB