Update dataset card

README.md

@@ -1,3 +1,77 @@
 ---
-license: apache-2.0
+license: gpl
+language:
+- en
+task_categories:
+- text-classification
+size_categories:
+- 100K<n<1M
+pretty_name: "Africa Synthetic Telecom Hardware Sensor Data Nigeria (TsFile)"
+tags:
+- TsFile
+- time-series
+- modality:timeseries
+- telecom
+- hardware
+- sensor
+- data
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: staged.tsfile
 ---
+
+# Africa Synthetic Telecom Hardware Sensor Data Nigeria (TsFile)
+
+This dataset is an Apache TsFile conversion of [`electricsheepafrica/africa-synth-telecom-hardware-sensor-data-nigeria`](https://huggingface.co/datasets/electricsheepafrica/africa-synth-telecom-hardware-sensor-data-nigeria), a synthetic Nigerian telecom tower hardware sensor dataset with temperature, power, voltage, humidity, vibration, health-status, and alert readings.
+
+## Source Dataset
+
+- **Original dataset:** [`electricsheepafrica/africa-synth-telecom-hardware-sensor-data-nigeria`](https://huggingface.co/datasets/electricsheepafrica/africa-synth-telecom-hardware-sensor-data-nigeria)
+- **Source files:** `hardware_sensor_data.parquet` and `hardware_sensor_data.csv`
+- **Rows:** 500,000
+- **Columns:** 12
+- **Generated date in source card:** 2025-10-05
+- **Time range in converted data:** 2025-09-01 00:00:00 to 2025-10-01 23:59:00
+- **License note:** the source card metadata declares `gpl`; the source README body also says "MIT License - For educational and research purposes".
+
+## TsFile Conversion
+
+- **Converted file:** `staged.tsfile`
+- **TsFile size:** 690,291,491 bytes
+- **TsFile table:** `hardware_sensor_data`
+- **Time column:** source `timestamp` is parsed as the TsFile `Time` column with millisecond precision.
+- **TAG column:** `sensor_id`; the source has 500,000 unique sensor IDs, so `(sensor_id, Time)` is unique.
+- **Rows preserved:** 500,000 source rows -> 500,000 staged rows.
+- **Columns preserved:** all 12 source columns are represented; no source columns or rows are dropped.
+
+## Schema
+
+| Role | Column | Type | Notes |
+|---|---|---|---|
+| TIME | `Time` | INT64 ms | Renamed from source `timestamp` during staging |
+| TAG | `sensor_id` | STRING | TsFile device dimension |
+| FIELD | `tower_id` | STRING | Tower identifier |
+| FIELD | `city` | STRING | Nigerian city |
+| FIELD | `equipment_type` | STRING | Hardware category |
+| FIELD | `temperature_celsius` | DOUBLE | Sensor measurement |
+| FIELD | `power_draw_watts` | DOUBLE | Sensor measurement |
+| FIELD | `voltage_v` | DOUBLE | Sensor measurement |
+| FIELD | `humidity_percent` | DOUBLE | Sensor measurement |
+| FIELD | `vibration_level` | DOUBLE | Sensor measurement |
+| FIELD | `health_status` | STRING | Values observed locally: `normal`, `warning` |
+| FIELD | `alert_triggered` | BOOLEAN | 20,508 true values in the converted data |
+
+## Read Example
+
+Use Apache TsFile tooling or SDKs to read:
+
+```python
+from tsfile import TsFileReader
+
+path = "staged.tsfile"
+reader = TsFileReader(path)
+schemas = reader.get_all_table_schemas()
+reader.close()
+```