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juliensimon/ssodnet-asteroid-properties

SsODNet Asteroid Physical Properties Part of the Orbital Mechanics Datasets collection on Hugging Face. Physical and dynamical properties of 1,487,300 asteroids and dwarf planets from the IMCCE (Paris Observatory) Solar System Open Database Network (SsODNet). This is the most comprehensive asteroid characterization catalog available, compiling best estimates from thousands of published studies. Dataset description SsODNet aggregates physical property measurements… See the full description on the dataset page: https://huggingface.co/datasets/juliensimon/ssodnet-asteroid-properties.

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SsODNet Asteroid Physical Properties

Part of the [Orbital Mechanics Datasets](https://huggingface.co/collections/juliensimon/orbital-mechanics-datasets-69c24caca4ab3934c9856994) collection on Hugging Face.

Physical and dynamical properties of 1,487,300 asteroids and dwarf planets from the IMCCE (Paris Observatory) Solar System Open Database Network (SsODNet). This is the most comprehensive asteroid characterization catalog available, compiling best estimates from thousands of published studies.

Dataset description

SsODNet aggregates physical property measurements from the astronomical literature into a single, curated "best estimates" flat table (ssoBFT). For each asteroid, IMCCE selects the most reliable published value for each property using a transparent ranking scheme. Properties include diameters, albedos, taxonomic classifications, masses, densities, rotation periods, and thermal inertia — alongside orbital elements and dynamical family memberships.

The fill factor varies by property: orbital elements are available for nearly all objects, while physical measurements like mass (429 objects) and density (468 objects) are known for far fewer.

Schema

ColumnTypeDescription
sso_idstringSsODNet unique identifier
sso_numberInt64IAU asteroid catalog number (null for unnumbered)
sso_namestringIAU name (null if unnamed)
sso_typestringObject type (Asteroid, Dwarf Planet, etc.)
sso_classstringDynamical class (MB, NEA, Trojan, Centaur, KBO, etc.)
semi_major_axis_aufloat64Orbital semi-major axis (AU)
eccentricityfloat64Orbital eccentricity
inclination_degfloat64Orbital inclination (degrees)
orbital_period_yrfloat64Orbital period (years)
periapsis_distance_aufloat64Perihelion distance (AU)
apoapsis_distance_aufloat64Aphelion distance (AU)
tisserand_jupiterfloat64Tisserand parameter w.r.t. Jupiter
family_numberInt64Dynamical family number
family_namestringDynamical family name
family_statusstringFamily membership status
absolute_magnitudefloat64Absolute magnitude H (best estimate)
absolute_magnitude_err_minfloat64H magnitude lower error bound
absolute_magnitude_err_maxfloat64H magnitude upper error bound
diameter_kmfloat64Effective diameter (km, best estimate)
diameter_err_min_kmfloat64Diameter lower error bound (km)
diameter_err_max_kmfloat64Diameter upper error bound (km)
albedofloat64Geometric albedo (best estimate)
albedo_err_minfloat64Albedo lower error bound
albedo_err_maxfloat64Albedo upper error bound
mass_kgfloat64Mass (kg, best estimate)
mass_err_min_kgfloat64Mass lower error bound (kg)
mass_err_max_kgfloat64Mass upper error bound (kg)
density_g_cm3float64Bulk density (g/cm3, best estimate)
density_err_min_g_cm3float64Density lower error bound (g/cm3)
density_err_max_g_cm3float64Density upper error bound (g/cm3)
taxonomy_classstringTaxonomic class (e.g., S, C, X, V)
taxonomy_complexstringTaxonomic complex (e.g., S-complex, C-complex)
taxonomy_schemestringClassification scheme (Bus-DeMeo, Tholen, etc.)
taxonomy_waverangestringWavelength range used for classification
taxonomy_techniquestringTechnique used for classification
thermal_inertiafloat64Thermal inertia (J m-2 s-0.5 K-1)
thermal_inertia_err_minfloat64Thermal inertia lower error bound
thermal_inertia_err_maxfloat64Thermal inertia upper error bound
rotation_period_hfloat64Rotation period (hours, best estimate)
rotation_period_err_min_hfloat64Rotation period lower error bound (hours)
rotation_period_err_max_hfloat64Rotation period upper error bound (hours)
moid_earth_aufloat64Minimum orbit intersection distance with Earth (AU)

Quick stats

  • 1,487,300 asteroids and dwarf planets
  • 149,496 with measured diameter
  • 149,497 with measured albedo
  • 170,933 with taxonomic classification
  • 429 with mass estimate
  • 468 with density estimate
  • 51,005 with rotation period
  • 255,987 with dynamical family assignment

Usage

python
from datasets import load_dataset

ds = load_dataset("juliensimon/ssodnet-asteroid-properties", split="train")
df = ds.to_pandas()

# Taxonomy distribution
df["taxonomy_class"].value_counts().head(10)

# Large asteroids with known density
dense = df[df["density_g_cm3"].notna() & (df["diameter_km"] > 100)]
dense[["sso_name", "diameter_km", "density_g_cm3", "taxonomy_class"]].sort_values(
    "diameter_km", ascending=False
)

# Near-Earth asteroids sorted by MOID
neas = df[df["sso_class"] == "NEA"].sort_values("moid_earth_au")
neas[["sso_name", "diameter_km", "moid_earth_au", "albedo"]].head(20)

# Diameter vs albedo by taxonomy
import matplotlib.pyplot as plt
sample = df.dropna(subset=["diameter_km", "albedo", "taxonomy_complex"])
for cpx, grp in sample.groupby("taxonomy_complex"):
    plt.scatter(grp["diameter_km"], grp["albedo"], s=1, alpha=0.4, label=cpx)
plt.xscale("log")
plt.xlabel("Diameter (km)")
plt.ylabel("Albedo")
plt.legend(fontsize=7)

Data source

IMCCE SsODNet — Solar System Open Database Network

The ssoBFT (Best Flat Table) compiles best estimates of physical and dynamical properties for all known asteroids and dwarf planets. Data originates from thousands of peer-reviewed publications, curated by IMCCE (Paris Observatory). See Berthier et al. (2023), "SsODNet: The Solar System Open Database Network", A&A 671, A151.

Pipeline

Source code: juliensimon/space-datasets

Citation

bibtex
@dataset{ssodnet_asteroid_properties,
  author = {Simon, Julien},
  title = {SsODNet Asteroid Physical Properties},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/juliensimon/ssodnet-asteroid-properties},
  note = {Based on IMCCE SsODNet ssoBFT, Berthier et al. (2023)}
}

License

CC-BY-4.0