README.md

metadata

license: apache-2.0
language:
  - en
tags:
  - space-science
  - cassini
  - cosmic-dust
  - time-of-flight-spectra
  - mass-spectrometry
  - saturn
  - enceladus
  - planetary-science
pretty_name: Cassini CDA Time-of-Flight Spectra
size_categories:
  - 100K<n<1M

Cassini Cosmic Dust Analyzer (CDA) Time-of-Flight Spectra Dataset

Dataset Description

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.

Data Cutoff

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.

Dataset Structure

data/
├── lvl1/
│   └── cda_qm_spectra_pre2008277_lvl1.parquet    # Raw spectra (774,953 samples)
├── lvl2/
│   ├── cda_qm_spectra_pre2008277_train_lvl2.parquet  # Labeled spectra (19,820 samples)
│   └── cda_qm_spectra_pre2008277_inf_lvl2.parquet    # Unlabeled spectra for inference (755,136 samples)
└── meta/
    └── cda_class_list.csv                         # Human-determined labels (34,850 entries)

Data Levels

Level 1 (lvl1)

Raw time-of-flight spectra with the following columns:

Column	Type	Description
sclk	float	Spacecraft Clock - unique identifier counting in seconds. Due to CDA's 1-second dead-time, SCLK serves as a unique event identifier
f_desc	int	Internal file descriptor (not relevant for analysis)
event_id	int	Internal event identifier (not relevant for analysis)
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
class	int	Set to -1000 (unlabeled in lvl1)
qi_ampl	float	QI channel amplitude in Coulombs. The QI (Charge Induction) channel is mounted in front of the TOF spectrometer
spectrum_length	int	Length of spectrum array (1018 for all samples; shorter spectra are excluded)

Level 2 (lvl2)

Processed data split into training and inference sets:

Training set (train_lvl2): 19,820 samples with human-determined labels

• Same columns as lvl1, but with valid class labels
• Excludes spectrum_length column

Inference set (inf_lvl2): 755,136 samples without labels

• Same columns as training, but without class column
• Suitable for model inference/prediction tasks

Metadata

The cda_class_list.csv file contains human-determined labels with:

Column	Description
sclk	Spacecraft Clock (identifier)
utc	UTC timestamp
utc-doy	UTC with day-of-year format
class	Human-determined spectrum classification

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.

Class Labels

Class	Count (Train)	Description
Noise	12,077	Noise/artifacts
1	4,491	Type 1 spectrum
2	1,015	Type 2 spectrum
3	909	Type 3 spectrum
?	553	Uncertain/unclassified
4	263	Type 4 spectrum
5	186	Type 5 spectrum
3-Car	89	Type 3 Carbon subclass
3-Cl	47	Type 3 Chlorine subclass
3-OH	47	Type 3 Hydroxyl subclass
3-KNa	41	Type 3 Potassium-Sodium subclass
5-Na	41	Type 5 Sodium subclass
3-P	34	Type 3 Phosphorus subclass
3-K	22	Type 3 Potassium subclass
2-X	3	Type 2 variant
X	2	Unknown/special

Important Note on Subclasses

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.

Usage

Loading the Data

import pandas as pd

# Load training data
train_df = pd.read_parquet("data/lvl2/cda_qm_spectra_pre2008277_train_lvl2.parquet")

# Load inference data
inf_df = pd.read_parquet("data/lvl2/cda_qm_spectra_pre2008277_inf_lvl2.parquet")

# Load raw lvl1 data
lvl1_df = pd.read_parquet("data/lvl1/cda_qm_spectra_pre2008277_lvl1.parquet")

# Load metadata
meta_df = pd.read_csv("data/meta/cda_class_list.csv")

With Hugging Face Datasets

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("your-username/cassini-cda-spectra")

Citation

If you use this dataset, please cite the Cassini CDA team and relevant publications.

License

This dataset is released under the Apache 2.0 License.

Acknowledgments

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.