Datasets:
Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 271, in _split_generators
scan = self._scan_metadata(all_files)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 318, in _scan_metadata
with self._open_reader(file) as reader:
~~~~~~~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 742, in _open_reader
return TsFileReader(file)
File "tsfile/tsfile_reader.pyx", line 364, in tsfile.tsfile_reader.TsFileReaderPy.__init__
File "tsfile/tsfile_reader.pyx", line 367, in tsfile.tsfile_reader.TsFileReaderPy.init_reader
File "tsfile/tsfile_py_cpp.pyx", line 789, in tsfile.tsfile_py_cpp.tsfile_reader_new_c
File "tsfile/tsfile_py_cpp.pyx", line 55, in tsfile.tsfile_py_cpp.check_error
tsfile.exceptions.FileOpenError: 28: Failed to open file
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
HLT-010 Synthetic Hospital Resource Usage Dataset — OR + Staffing + Equipment + Capacity (Sample Preview) (TsFile)
Apache TsFile version of xpertsystems/hlt010-sample.
Overview
A fully synthetic hospital operations dataset combining operating room schedules, staffing/workforce records, biomedical equipment utilization, daily capacity metrics, and facility master data across mixed facility types (academic / large community / medium community / critical access). Calibrated to AHA Annual Survey 2023, AORN benchmarks, NSI nursing data, ECRI Institute equipment data, and CMS Conditions of Participation.
- Tables: 5 TsFile table(s), 35,255 rows in total.
equipment: 17,461 rows, 2023-01-01 00:00:00 → 2023-01-14 00:00:01.238000 (UTC)facilities: 3 rows, 1970-01-01 00:00:00 → 1970-01-01 00:00:00.002000 (UTC)hospital_resources: 42 rows, 2023-01-01 00:00:00 → 2023-01-14 00:00:00.002000 (UTC)or_schedule: 4,226 rows, 2023-01-01 00:00:00 → 2023-01-14 00:00:00.189000 (UTC)staffing: 13,523 rows, 2023-01-01 00:00:00 → 2023-01-14 00:00:00.605000 (UTC)
Schema (TsFile structure)
equipment.tsfile
- Time (INT64, milliseconds) — the source
record_datecolumn. - TAG: none — the table is stored as a single device.
- FIELD (13):
asset_id(string),facility_id(string),equipment_class(string),equipment_age_yrs(double),utilization_rate(double),in_service_hours(double),downtime_hours(double),unplanned_downtime_flag(int64),downtime_cause(string),last_maintenance_date(string),next_maintenance_due(string),failure_flag(int64),repair_cost_usd(double)
facilities.tsfile
- Time (INT64, milliseconds) — synthetic row index over the stable source order; this table has no clock column.
- TAG: none — the table is stored as a single device.
- FIELD (11):
facility_id(string),facility_type(string),teaching_status(int64),trauma_level(string),bed_count(int64),icu_beds(int64),or_suite_count(int64),pacu_bays(int64),state(string),region(string),daily_or_capacity(double)
hospital_resources.tsfile
- Time (INT64, milliseconds) — the source
census_datecolumn. - TAG: none — the table is stored as a single device.
- FIELD (40):
facility_id(string),day_of_week(string),is_weekend(int64),total_beds(int64),occupied_beds(int64),occupancy_rate(double),icu_beds_x(int64),icu_occupied(int64),icu_occupancy_rate(double),pacu_bays_x(int64),pacu_patients(int64),pacu_utilization_rate(double),ed_boarding_hours(double),diversion_flag(int64),diversion_hours(double),capacity_breach_flag(int64),surge_day_flag(int64),or_utilization_rate(double),surgical_cases_scheduled(int64),or_revenue_usd(double),or_cost_per_min_usd(double),total_or_minutes(int64),contribution_margin_usd(double),block_release_efficiency(double),staffing_adequacy_score(double),operational_efficiency_index(double),surgical_site_infection_flag(int64),near_miss_flag(int64),consent_timeout_completed(int64),equipment_safety_check_flag(int64),facility_type(string),teaching_status(int64),trauma_level(string),bed_count(int64),icu_beds_y(int64),or_suite_count(int64),pacu_bays_y(int64),state(string),region(string),daily_or_capacity(double)
or_schedule.tsfile
- Time (INT64, milliseconds) — the source
case_datecolumn. - TAG: none — the table is stored as a single device.
- FIELD (17):
case_id(string),facility_id(string),or_id(string),case_type(string),surgeon_id(string),is_emergency(int64),scheduled_start_min(int64),actual_start_min(double),start_delay_min(double),first_case_ontime_flag(string),scheduled_duration_min(int64),actual_duration_min(double),turnover_time_min(double),cancellation_flag(int64),cancellation_reason(string),block_owner(string),add_on_flag(int64)
staffing.tsfile
- Time (INT64, milliseconds) — the source
shift_datecolumn. - TAG: none — the table is stored as a single device.
- FIELD (10):
shift_id(string),facility_id(string),staff_id(string),staff_role(string),shift_type(string),hours_worked(int64),overtime_flag(int64),float_pool_flag(int64),agency_flag(int64),staff_to_patient_ratio(double)
Conversion notes
- One TsFile per source CSV (5 tables), each stored as a single device: the facility id, asset id, staff id and surgeon id stay ordinary FIELDs.
- Time = the daily reporting date of each table (
record_date,census_date,case_date,shift_date) as INT64 milliseconds at 00:00 UTC. Several rows share a day, so they are ordered by a 1 ms step in stable source order; the calendar day is unaffected. facilitiesis a 3-row facility master with no date column, so its Time is a synthetic row index. No column is dropped.
Usage
Install the Apache TsFile Python SDK (pip install tsfile) and read a converted file:
from pathlib import Path
from tsfile import TsFileReader
path = Path("equipment.tsfile")
with TsFileReader(str(path)) as reader:
schemas = reader.get_all_table_schemas()
print("tables:", list(schemas))
table_name = next(iter(schemas))
table = schemas[table_name]
columns = [column.get_column_name() for column in table.get_columns()]
print("columns:", columns)
field_names = [
column.get_column_name()
for column in table.get_columns()
if column.get_column_name() not in {"Time", "time"}
]
if field_names:
with reader.query_table(table_name, field_names[:3], batch_size=1024) as result:
batch = result.read_arrow_batch()
if batch is not None:
print(batch.to_pandas().head())
Source & license
- Original dataset:
xpertsystems/hlt010-sample - Source card title / publisher: HLT-010 Synthetic Hospital Resource Usage Dataset — OR + Staffing + Equipment + Capacity (Sample Preview)
- License: cc-by-nc-4.0 (as declared by the original dataset).
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