Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
pulled: timestamp[s]
osm_features: int64
osm_after_dedupe: int64
osm_drawn: int64
osm_not_drawn: int64
epoch_us: int64
epoch_drawn: int64
epoch_outside_contiguous: int64
epoch_unplaced: int64
epoch_mw_drawn: int64
epoch: list<item: struct<source: string, name: string, operator: string, mw: double, h100e: double, capex_u (... 73 chars omitted)
child 0, item: struct<source: string, name: string, operator: string, mw: double, h100e: double, capex_usd_b: doubl (... 61 chars omitted)
child 0, source: string
child 1, name: string
child 2, operator: string
child 3, mw: double
child 4, h100e: double
child 5, capex_usd_b: double
child 6, address: string
child 7, lat: double
child 8, lon: double
child 9, placed: string
osm: list<item: struct<source: string, osm: string, name: string, operator: string, lat: double, lon: dou (... 39 chars omitted)
child 0, item: struct<source: string, osm: string, name: string, operator: string, lat: double, lon: double, buildi (... 27 chars omitted)
child 0, source: string
child 1, osm: string
child 2, name: string
child 3, operator: string
child 4, lat: double
child 5, lon: double
child 6, building: string
child 7, status: string
to
{'pulled': Value('timestamp[s]'), 'osm': List({'source': Value('string'), 'osm': Value('string'), 'name': Value('string'), 'operator': Value('string'), 'lat': Value('float64'), 'lon': Value('float64'), 'building': Value('string'), 'status': Value('string')}), 'epoch': List({'source': Value('string'), 'name': Value('string'), 'operator': Value('string'), 'mw': Value('float64'), 'h100e': Value('float64'), 'capex_usd_b': Value('float64'), 'address': Value('string'), 'lat': Value('float64'), 'lon': Value('float64'), 'placed': Value('string')})}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 544, 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 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 361, 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 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
pulled: timestamp[s]
osm_features: int64
osm_after_dedupe: int64
osm_drawn: int64
osm_not_drawn: int64
epoch_us: int64
epoch_drawn: int64
epoch_outside_contiguous: int64
epoch_unplaced: int64
epoch_mw_drawn: int64
epoch: list<item: struct<source: string, name: string, operator: string, mw: double, h100e: double, capex_u (... 73 chars omitted)
child 0, item: struct<source: string, name: string, operator: string, mw: double, h100e: double, capex_usd_b: doubl (... 61 chars omitted)
child 0, source: string
child 1, name: string
child 2, operator: string
child 3, mw: double
child 4, h100e: double
child 5, capex_usd_b: double
child 6, address: string
child 7, lat: double
child 8, lon: double
child 9, placed: string
osm: list<item: struct<source: string, osm: string, name: string, operator: string, lat: double, lon: dou (... 39 chars omitted)
child 0, item: struct<source: string, osm: string, name: string, operator: string, lat: double, lon: double, buildi (... 27 chars omitted)
child 0, source: string
child 1, osm: string
child 2, name: string
child 3, operator: string
child 4, lat: double
child 5, lon: double
child 6, building: string
child 7, status: string
to
{'pulled': Value('timestamp[s]'), 'osm': List({'source': Value('string'), 'osm': Value('string'), 'name': Value('string'), 'operator': Value('string'), 'lat': Value('float64'), 'lon': Value('float64'), 'building': Value('string'), 'status': Value('string')}), 'epoch': List({'source': Value('string'), 'name': Value('string'), 'operator': Value('string'), 'mw': Value('float64'), 'h100e': Value('float64'), 'capex_usd_b': Value('float64'), 'address': Value('string'), 'lat': Value('float64'), 'lon': Value('float64'), 'placed': Value('string')})}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
ATLAS: United States data centers
Sites mapped in two open sources, pulled 2026-10-28: features tagged as data centers in OpenStreetMap (merged when within 250 m with the same name), and the United States AI data centers in Epoch AI's dataset, with coordinates added by us from the US Census geocoder and OpenStreetMap Nominatim. This is what those sources hold, not a count of every data center. Map and context: https://indahl.ai/atlas .
Files: datacenters.json (records with their source), summary.json (counts), build_atlas.py and geocode_epoch.py (the scripts).
Licences: the OpenStreetMap part is (c) OpenStreetMap contributors under the ODbL 1.0 (https://www.openstreetmap.org/copyright), and this combined database is shared under the ODbL 1.0. The Epoch AI fields are CC BY 4.0: Epoch AI, 'AI data centers', epoch.ai/data/ai-data-centers.
Reference: HLC-BAD4BB03
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