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---
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license: apache-2.0
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language:
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- en
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tags:
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- space-science
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- cassini
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- cosmic-dust
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- time-of-flight-spectra
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- mass-spectrometry
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- saturn
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- enceladus
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- planetary-science
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pretty_name: Cassini CDA Time-of-Flight Spectra
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size_categories:
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- 100K<n<1M
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---
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# Cassini Cosmic Dust Analyzer (CDA) Time-of-Flight Spectra Dataset
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## Dataset Description
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This dataset contains time-of-flight (TOF) mass spectra from the **Cosmic Dust Analyzer (CDA)** instrument aboard NASA's Cassini spacecraft. The CDA was designed to analyze the composition of cosmic dust particles in the Saturnian system and interplanetary space.
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### Data Cutoff
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**Important:** Only data until **2008-277** (October 3, 2008, day of year 277) are included in this dataset. Data recorded after this date are excluded due to a **sensitivity drop** of the CDA instrument. This sensitivity change occurred after a close flyby of Enceladus, during which Cassini flew through an ice plume—a cloud of ice particles ejected by Enceladus' geysers. This event likely introduced bias in subsequent measurements.
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## Dataset Structure
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```
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data/
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├── lvl1/
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│ └── cda_qm_spectra_pre2008277_lvl1.parquet # Raw spectra (774,953 samples)
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├── lvl2/
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│ ├── cda_qm_spectra_pre2008277_train_lvl2.parquet # Labeled spectra (19,820 samples)
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│ └── cda_qm_spectra_pre2008277_inf_lvl2.parquet # Unlabeled spectra for inference (755,136 samples)
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└── meta/
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└── cda_class_list.csv # Human-determined labels (34,850 entries)
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```
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## Data Levels
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### Level 1 (lvl1)
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Raw time-of-flight spectra with the following columns:
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| Column | Type | Description |
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|--------|------|-------------|
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| `sclk` | float | Spacecraft Clock - unique identifier counting in seconds. Due to CDA's 1-second dead-time, SCLK serves as a unique event identifier |
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| `f_desc` | int | Internal file descriptor (not relevant for analysis) |
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| `event_id` | int | Internal event identifier (not relevant for analysis) |
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| `spectrum` | array[float] | Time-of-flight spectrum array (1018 values). Each value corresponds to a time step covering ~6 microseconds total. Values are in **Volts** |
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| `class` | int | Set to -1000 (unlabeled in lvl1) |
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| `qi_ampl` | float | QI channel amplitude in **Coulombs**. The QI (Charge Induction) channel is mounted in front of the TOF spectrometer |
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| `spectrum_length` | int | Length of spectrum array (1018 for all samples; shorter spectra are excluded) |
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### Level 2 (lvl2)
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Processed data split into training and inference sets:
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**Training set** (`train_lvl2`): 19,820 samples with human-determined labels
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- Same columns as lvl1, but with valid `class` labels
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- Excludes `spectrum_length` column
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**Inference set** (`inf_lvl2`): 755,136 samples without labels
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- Same columns as training, but without `class` column
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- Suitable for model inference/prediction tasks
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### Metadata
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The `cda_class_list.csv` file contains human-determined labels with:
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| Column | Description |
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|--------|-------------|
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| `sclk` | Spacecraft Clock (identifier) |
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| `utc` | UTC timestamp |
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| `utc-doy` | UTC with day-of-year format |
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| `class` | Human-determined spectrum classification |
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**Note:** The metadata file includes labels for all classified spectra, including those after 2008-277 and compressed format spectra (e.g., 509-length), which are not present in the parquet files.
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## Class Labels
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| Class | Count (Train) | Description |
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|-------|---------------|-------------|
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| `Noise` | 12,077 | Noise/artifacts |
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| `1` | 4,491 | Type 1 spectrum |
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| `2` | 1,015 | Type 2 spectrum |
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| `3` | 909 | Type 3 spectrum |
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| `?` | 553 | Uncertain/unclassified |
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| `4` | 263 | Type 4 spectrum |
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| `5` | 186 | Type 5 spectrum |
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| `3-Car` | 89 | Type 3 Carbon subclass |
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| `3-Cl` | 47 | Type 3 Chlorine subclass |
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| `3-OH` | 47 | Type 3 Hydroxyl subclass |
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| `3-KNa` | 41 | Type 3 Potassium-Sodium subclass |
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| `5-Na` | 41 | Type 5 Sodium subclass |
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| `3-P` | 34 | Type 3 Phosphorus subclass |
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| `3-K` | 22 | Type 3 Potassium subclass |
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| `2-X` | 3 | Type 2 variant |
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| `X` | 2 | Unknown/special |
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### Important Note on Subclasses
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The subclasses (e.g., `3-OH`, `3-Car`, `3-Cl`) were introduced later in the classification scheme. It is likely that spectra with these specific characteristics exist within the general `3` class samples that were labeled earlier. This may introduce **label bias** when training models, as some `3` class samples may actually belong to the more specific subclasses.
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## Usage
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### Loading the Data
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```python
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import pandas as pd
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# Load training data
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train_df = pd.read_parquet("data/lvl2/cda_qm_spectra_pre2008277_train_lvl2.parquet")
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# Load inference data
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inf_df = pd.read_parquet("data/lvl2/cda_qm_spectra_pre2008277_inf_lvl2.parquet")
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# Load raw lvl1 data
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lvl1_df = pd.read_parquet("data/lvl1/cda_qm_spectra_pre2008277_lvl1.parquet")
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# Load metadata
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meta_df = pd.read_csv("data/meta/cda_class_list.csv")
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```
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### With Hugging Face Datasets
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```python
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from datasets import load_dataset
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# Load the dataset
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dataset = load_dataset("your-username/cassini-cda-spectra")
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```
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## Citation
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If you use this dataset, please cite the Cassini CDA team and relevant publications.
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## License
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This dataset is released under the [Apache 2.0 License](LICENSE).
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## Acknowledgments
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This dataset is derived from data collected by the Cosmic Dust Analyzer (CDA) instrument aboard NASA's Cassini spacecraft during its mission to Saturn (1997-2017). We thank the CDA team and NASA/ESA for making this data available for scientific research.
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