Datasets:
Xu Zhijian commited on
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update: general report
Browse files- README.md +132 -0
- weather/weather_report/general_report/fast_general_weather_forecast_2014.json +0 -0
- weather/weather_report/general_report/fast_general_weather_forecast_2015.json +0 -0
- weather/weather_report/general_report/fast_general_weather_forecast_2016.json +0 -0
- weather/weather_report/general_report/fast_general_weather_forecast_2017.json +0 -0
- weather/weather_report/general_report/fast_general_weather_forecast_2018.json +0 -0
- weather/weather_report/general_report/fast_general_weather_forecast_2019.json +0 -0
- weather/weather_report/general_report/fast_general_weather_forecast_2020.json +0 -0
- weather/weather_report/general_report/fast_general_weather_forecast_2021.json +0 -0
- weather/weather_report/general_report/fast_general_weather_forecast_2022.json +0 -0
- weather/weather_report/general_report/fast_general_weather_forecast_2023.json +0 -0
- weather/weather_report/general_report/fast_general_weather_forecast_2024.json +0 -0
- weather/weather_report/general_report/fast_general_weather_forecast_2025.json +0 -0
- weather/weather_report/general_report/static_info.json +29 -0
README.md
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| 1 |
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---
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task_categories:
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- time-series-forecasting
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language:
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- en
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tags:
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- TimeSeries,
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- Multimodal,
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- Heterogeneous
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size_categories:
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- 1B<n<10B
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---
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# WIATS: Weather-centric Intervention-Aware Time Series Multimodal Dataset
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## Data source:
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- [Jena_Atmospheric_Physics](https://www.timeanddate.com/weather)
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## Dataset Structure
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The dataset is organized into the following structure:
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```
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|-- subdataset1
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| |-- raw_data # Original data files
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| |-- time_series # Rule-based Imputed data files
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| | |-- id_1.parquet # Time series data for each subject can be multivariate, can be in csv, parquet, etc.
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| | |-- id_2.parquet
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| | |-- ...
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| | |-- id_info.json # Metadata for each subject
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| |-- weather
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| | |-- location_1
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| | | |-- raw_data
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| | | | |-- daily_weather_raw_????.json
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| | | | |-- ...
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| | | | |-- daily_weather_????.csv
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| | | | |-- ...
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| | | | |-- hourly_weather_????.csv
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| | | | |-- ...
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| | | |-- weather_report (can be flattened and use regex to extract the version)
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| | | | |-- version_1
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| | | | | |-- weather_report_????.json
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| | | | | |-- ...
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| | | | |-- version_2
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| | | | |-- ...
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| | | |-- report_embedding # embedding for the weather report
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| | | | |-- version_1
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| | | | | |-- report_embedding_????.pkl
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| | | | | |-- ...
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| | | | |-- version_2
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| | | | |-- ...
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| | |-- location_2
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| | |-- ...
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| | |-- merged_report_embedding # merged embedding for multiple needed locations (optional)
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| | | |-- version_1
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| | | | |-- report_embedding_????.pkl
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| | | | |-- ...
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| | | |-- version_2
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| | | |-- ...
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| | |-- merged_general_report # merged general report for multiple needed locations (optional)
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| | | |-- xxx.json
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| | | |-- ...
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| |-- scripts # Scripts for data processing, model training, and evaluation
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| |-- id_info.json # Metadata for whole dataset without preprocessing
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| |-- static_info.json # Static information for this dataset, including the dataset information, channel information, downtime reasons.
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| |-- static_info_embeddings.pkl
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| |-- slim_data (optional)
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| |-- full_data (optional) # intermediate data during the data processing
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|-- subdataset2
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|-- ......
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```
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## id_info.json Structure
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The `id_info.json` file contains metadata for each subject in the dataset. Extracted from the raw dataset. The structure is as follows:
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```json
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{
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"id_1": {
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"len": 1000, # Length of the time series data
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"sensor_downtime": {
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1: {
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"time": [yyyy-mm-dd hh:mm:ss, yyyy-mm-dd hh:mm:ss],
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"index": [start_index, end_index]
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},
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2: {
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"time": [yyyy-mm-dd hh:mm:ss, yyyy-mm-dd hh:mm:ss],
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"index": [start_index, end_index]
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},
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...
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},
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"other_info_1": "value_1", # Other information about the subject customizable entry
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"other_info_2": "value_2",
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...
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},
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"id_2": ...
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}
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```
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## static_info.json Structure
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The `static_info.json` file contains static information for the whole dataset. The structure is as follows:
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```json
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{
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"general_info": "description of the dataset",
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"downtime_prompt": "",
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"channel_info": {
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"id_1": {
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"channel_1": "channel 1 is xxx",
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"channel_2": "channel 2 is xxx",
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...
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},
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"id_2": {
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"channel_1": "channel 1 is xxx",
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"channel_2": "channel 2 is xxx",
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...
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},
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...
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},
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}
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```
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weather/weather_report/general_report/static_info.json
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{
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"general_info": "This dataset contains comprehensive weather and climate measurements recorded in Jena, Germany, spanning multiple years.",
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"downtime_prompt": "No reading at this time for unknown reason, set 0 as default, ignore.",
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"channel_info": {
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"weather_large": {
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"p (mbar)": "Atmospheric pressure measured in millibars. It indicates the weight of the air above the point of measurement.",
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"T (degC)": "Temperature at the point of observation, measured in degrees Celsius.",
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"Tpot (K)": "Potential temperature, given in Kelvin. This is the temperature that a parcel of air would have if it were brought adiabatically to a standard reference pressure, often used to compare temperatures at different pressures in a thermodynamically consistent way.",
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"Tdew (degC)": "Dew point temperature in degrees Celsius. It's the temperature to which air must be cooled, at constant pressure and water vapor content, for saturation to occur. A lower dew point means dryer air.",
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"rh (%)": "Relative humidity, expressed as a percentage. It measures the amount of moisture in the air relative to the maximum amount of moisture the air can hold at that temperature.",
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"VPmax (mbar)": "Maximum vapor pressure, in millibars. It represents the maximum amount of moisture that the air can hold at a given temperature.",
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"VPact (mbar)": "Actual vapor pressure, in millibars. It's the current amount of water vapor present in the air.",
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"VPdef (mbar)": "Vapor pressure deficit, in millibars. The difference between the maximum vapor pressure and the actual vapor pressure; it indicates how much more moisture the air can hold before saturation.",
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"sh (g/kg)": "Specific humidity, the mass of water vapor in a given mass of air, including the water vapor. It's measured in grams of water vapor per kilogram of air.",
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"H2OC (mmol/mol)": "Water vapor concentration, expressed in millimoles of water per mole of air. It's another way to quantify the amount of moisture in the air.",
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"rho (g/m³)": "Air density, measured in grams per cubic meter. It indicates the mass of air in a given volume and varies with temperature, pressure, and moisture content.",
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"wv (m/s)": "Wind velocity, the speed of the wind measured in meters per second.",
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"max. wv (m/s)": "Maximum wind velocity observed in the given time period, measured in meters per second.",
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"wd (deg)": "Wind direction, in degrees from true north. This indicates the direction from which the wind is coming.",
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"rain (mm)": "Rainfall amount, measured in millimeters. It indicates how much rain has fallen during the observation period.",
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"raining (s)": "Duration of rainfall, measured in seconds. It specifies how long it has rained during the observation period.",
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"SWDR (W/m²)": "Shortwave Downward Radiation, the amount of solar radiation reaching the ground, measured in watts per square meter.",
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"PAR (μmol/m²/s)": "Photosynthetically Active Radiation, the amount of light available for photosynthesis, measured in micromoles of photons per square meter per second.",
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"max. PAR (μmol/m²/s)": "Maximum Photosynthetically Active Radiation observed in the given time period, indicating the peak light availability for photosynthesis.",
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"Tlog (degC)": "Likely a logged temperature measurement in degrees Celsius. It could be a specific type of temperature measurement or recording method used in the dataset.",
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"CO2 (ppm)": "Carbon dioxide concentration in the air, measured in parts per million. It's a key greenhouse gas and indicator of air quality."
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}
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}
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}
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