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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.
- Overview
- Schema (TsFile structure)
alarm_events.tsfiledrilling_parameters.tsfileenvironmental_conditions.tsfilehydraulic_systems.tsfilemaintenance_records.tsfilepower_systems.tsfilerigs_master.tsfilerul_labels.tsfilesensor_fusion_features.tsfilesensor_health.tsfilesensors_master.tsfiletelemetry_streams.tsfilethermal_monitoring.tsfilevibration_analysis.tsfile
- Conversion notes
- Usage
- Source & license
OIL-012 — Synthetic Rig Sensor IoT Dataset (Sample) (TsFile)
Apache TsFile version of xpertsystems/oil012-sample.
Overview
A free, schema-identical preview of XpertSystems.ai's enterprise drilling rig IoT telemetry dataset for predictive-maintenance ML, condition-monitoring ML, sensor-fusion modeling, and remaining-useful-life forecasting. The sample covers 30 rigs across 10 global basins and 8 rig types, with 134,622 rows including 94,745 sparse-format telemetry events linked across 15 tables.
- Tables: 14 TsFile table(s), 134,622 rows in total.
alarm_events: 278 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.002000 (UTC)drilling_parameters: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC)environmental_conditions: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC)hydraulic_systems: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC)maintenance_records: 29 rows, 2026-01-01 00:10:00 → 2026-01-01 14:40:00 (UTC)power_systems: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC)rigs_master: 30 rows, 1970-01-01 00:00:00 → 1970-01-01 00:00:00.029000 (UTC)rul_labels: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC)sensor_fusion_features: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC)sensor_health: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC)sensors_master: 660 rows, 1970-01-01 00:00:00 → 1970-01-01 00:00:00.659000 (UTC)telemetry_streams: 94,745 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.656000 (UTC)thermal_monitoring: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC)vibration_analysis: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC)
Schema (TsFile structure)
alarm_events.tsfile
- Time (INT64, milliseconds) — the source
event_tscolumn. - TAG: none — the table is stored as a single device.
- FIELD (8):
alarm_id(string),rig_id(string),alarm_code(string),severity(string),subsystem(string),duration_sec(int64),anomaly_score(double),acknowledged_flag(int64)
drilling_parameters.tsfile
- Time (INT64, milliseconds) — the source
event_tscolumn. - TAG: none — the table is stored as a single device.
- FIELD (11):
event_id(string),rig_id(string),operating_state(string),wob_klbs(double),torque_ftlb(double),rpm(double),rop_ft_hr(double),standpipe_pressure_psi(double),flow_rate_gpm(double),hook_load_klbs(double),stick_slip_index(double)
environmental_conditions.tsfile
- Time (INT64, milliseconds) — the source
event_tscolumn. - TAG: none — the table is stored as a single device.
- FIELD (6):
rig_id(string),ambient_temp_f(double),humidity_pct(double),wind_speed_mph(double),environmental_stress_index(double),weather_impact_factor(double)
hydraulic_systems.tsfile
- Time (INT64, milliseconds) — the source
event_tscolumn. - TAG: none — the table is stored as a single device.
- FIELD (6):
rig_id(string),pump_pressure_psi(double),hydraulic_pressure_psi(double),hydraulic_temp_f(double),flow_rate_gpm(double),cavitation_risk_score(double)
maintenance_records.tsfile
- Time (INT64, milliseconds) — the source
event_tscolumn. - TAG: none — the table is stored as a single device.
- FIELD (9):
maintenance_id(string),rig_id(string),component_id(string),maintenance_type(string),subsystem(string),failure_mode(string),labor_hours(double),repair_cost_usd(double),post_maintenance_health_index(double)
power_systems.tsfile
- Time (INT64, milliseconds) — the source
event_tscolumn. - TAG: none — the table is stored as a single device.
- FIELD (6):
rig_id(string),voltage(double),amperage(double),motor_current(double),load_pct(double),current_harmonic_distortion(double)
rigs_master.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 (13):
rig_id(string),rig_type(string),operator_name(string),basin_name(string),country_region(string),rig_age_years(double),automation_level(double),offshore_flag(int64),hthp_flag(int64),environmental_stress_index(double),base_health_index(double),daily_operating_hours(double),commissioned_year(int64)
rul_labels.tsfile
- Time (INT64, milliseconds) — the source
event_tscolumn. - TAG: none — the table is stored as a single device.
- FIELD (6):
rig_id(string),component_id(string),remaining_useful_life_hr(double),failure_probability(double),failure_horizon_days(int64),subsystem_health_score(double)
sensor_fusion_features.tsfile
- Time (INT64, milliseconds) — the source
event_tscolumn. - TAG: none — the table is stored as a single device.
- FIELD (6):
rig_id(string),fusion_vector_id(string),anomaly_score(double),health_index(double),sensor_fusion_consistency(double),maintenance_priority_score(double)
sensor_health.tsfile
- Time (INT64, milliseconds) — the source
event_tscolumn. - TAG: none — the table is stored as a single device.
- FIELD (5):
rig_id(string),calibration_score(double),sensor_drift_pct(double),packet_loss_pct(double),edge_latency_ms(double)
sensors_master.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 (9):
sensor_id(string),rig_id(string),sensor_type(string),subsystem(string),unit(string),sensor_age_years(double),sampling_profile(string),calibration_score(double),edge_device_id(string)
telemetry_streams.tsfile
- Time (INT64, milliseconds) — the source
event_tscolumn. - TAG: none — the table is stored as a single device.
- FIELD (8):
rig_id(string),sensor_id(string),sensor_type(string),subsystem(string),unit(string),sensor_value(double),quality_flag(string),operating_state(string)
thermal_monitoring.tsfile
- Time (INT64, milliseconds) — the source
event_tscolumn. - TAG: none — the table is stored as a single device.
- FIELD (5):
rig_id(string),component_temp_f(double),bearing_temp_f(double),thermal_gradient(double),thermal_stress_index(double)
vibration_analysis.tsfile
- Time (INT64, milliseconds) — the source
event_tscolumn. - TAG: none — the table is stored as a single device.
- FIELD (7):
rig_id(string),vibration_rms(double),axial_vibration(double),torsional_vibration(double),harmonic_index(double),stick_slip_index(double),shock_event_flag(int64)
Conversion notes
- One TsFile per source CSV (14 tables) for this drilling-rig telemetry sample; each table is stored as a single device, so the rig/well/tank/sensor ids stay ordinary FIELDs.
- Time = the table's own timestamp column as INT64 milliseconds (event timestamps, daily record/production dates, or test dates). Master/inventory tables that carry no clock (
rigs_master,sensors_master,wells_master,tank_master, the label tables andscada_telemetry) use a synthetic row index as Time. - No column is dropped. Rows that share a timestamp are ordered by a 1 ms step in stable source order; daily tables keep their exact calendar day.
- Not converted:
equipment_failures.csv— the file ships with a header only and zero data rows.
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("alarm_events.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/oil012-sample - Source card title / publisher: OIL-012 — Synthetic Rig Sensor IoT Dataset (Sample)
- License: cc-by-nc-4.0 (as declared by the original dataset).
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