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/python3.12/site-packages/datasets/inspect.py", line 289, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 83, in _split_generators
                  raise ValueError(
              ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
              
              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 65, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 343, in get_dataset_split_names
                  info = get_dataset_config_info(
                         ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 294, 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.

YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/datasets-cards)

FAKER-Air Dataset

This repository contains the dataset used in FAKER-Air, consisting of ground-truth air quality observations interpolated onto a grid and CMAQ reanalysis data tailored for East Asia.

Dataset Structure

The data is organized into two main directories inside data/:

1. Observations (data/obs)

Ground-truth station data interpolated onto the CMAQ 27km grid.

  • Format: .npz (Compressed NumPy archives)
  • Naming: YYYYMMDDHH_obs.npz (e.g., 2016010100_obs.npz)
  • Content: Contains arrays for pollutant concentrations (PM2.5, PM10, etc.) on the grid.
  • Total Files: ~74,000 files (Hourly data from 2016 to 2023+).

2. CMAQ Reanalysis (data/cmaq)

Physics-based model outputs (Community Multiscale Air Quality).

  • Format: .npy and .json
  • Structure: YYYY/MM/DD/NIER_27_01/
  • Files:
    • *_x_conc.npy: Concentration fields.
    • *_x_metcro2d.npy: 2D Meteorological fields.
    • *_x_metcro3d.npy: 3D Meteorological fields.
    • *_meta.json: Metadata.

How to Use

You can download specific parts of the dataset using the huggingface_hub Python library.

Prerequisites

pip install huggingface_hub numpy

Download & Load Example

from huggingface_hub import snapshot_download
import numpy as np
import os

# 1. Download the dataset (It will cache data locally)
# To download only specific years or folders, use `allow_patterns`.
local_dir = snapshot_download(
    repo_id="2na-97/FAKER-Air",
    repo_type="dataset",
    allow_patterns=[
        "data/obs/2023*.npz",       # Example: Only download OBS for 2023
        "data/cmaq/2023/**"         # Example: Only download CMAQ for 2023
    ]
)

print(f"Data downloaded to: {local_dir}")

# 2. Load an OBS file
obs_path = os.path.join(local_dir, "data/obs/2023010100_obs.npz")
if os.path.exists(obs_path):
    data = np.load(obs_path)
    print("Keys in OBS:", data.files)
    # Example access: data['pm25']

# 3. Load a CMAQ file
cmaq_path = os.path.join(local_dir, "data/cmaq/2023/01/01/NIER_27_01/20230101_x_conc.npy")
if os.path.exists(cmaq_path):
    cmaq_data = np.load(cmaq_path)
    print("CMAQ Shape:", cmaq_data.shape)

Citation

@article{kang2026fakerair,
  title={Real-Time Long Horizon Air Quality Forecasting via Group-Relative Policy Optimization},
  author={Kang, Inha and others},
  journal={arXiv preprint arXiv:2511.22169},
  year={2026}
}
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