# Dataset information: the entry point for dataset configuration, including file locations for each modality.
dataset_id: LeageST
dataset_name: LargeST
domain: traffic_management

sample_defination:
  sample_type: traffic flow monitoring sensor
  sample_id_graph: ID2 # Corresponding column name in the data; use None if the index is used directly.
  sample_id_time_series: ID # Corresponding column name in the data; use None if the index is used directly.
  description: each sample corresponds to a traffic flow monitoring sensor

modalities: 
# Available feature modalities.
  meta_features: # Static metadata, analogous to tabular data; read ca_meta.csv from the main directory.
    required: true # meta_features is required.
    file_name: ca_meta.csv # All provided files should be directly readable by pandas as a pd.DataFrame.

  node_level_task_graphs:
    available: true # Whether a graph for node-level tasks is available; if so, load its data from the corresponding directory.
    graph_ids:
      - road_distance_graph # Graph name, for example road_distance_graph (shortest driving distance graph).

  time_series: 
    available: true # Whether time series data is available; if so, load it from the corresponding directory.
    time_series_ids:
      - traffic_flow # Time series name, for example traffic_flow (traffic volume).

tasks: # Task construction.
# Supported task types, for example meta_feature prediction, time series forecasting, and ranking.
  - lane_count_regression # Lane count regression.
  - traffic_flow_forecasting # Traffic flow forecasting.

# Data source information.
license:
  data_license: source-dependent
  redistribution_allowed: true

source:
  name: Citi Bike Trip History
  url: source url or citation