Gaia-DR3: A Billion-Star Dataset for Galactic Analysis

This dataset is a high-fidelity, pre-processed collection of over 1 Billion stellar records derived from the European Space Agency (ESA) Gaia Mission (Data Release 3). It is specifically curated for large-scale galactic archaeology, 3D mapping, and training advanced machine learning models like SADIM-54M.

1. Dataset Overview

The dataset provides a comprehensive snapshot of the Milky Way, covering astrometric, kinematic, and photometric parameters. It has been optimized for high-performance computing and AI-driven astronomical frameworks.

2. Feature Schema (13 Core Parameters)

The dataset is structured with 13 essential features for understanding stellar dynamics:

Feature Name	Data Type	Scientific Description
source_id	int64	Unique Gaia DR3 identifier for each stellar source.
ra / dec	float64	Equatorial Coordinates: Right Ascension & Declination.
l / b	float64	Galactic Coordinates: Longitude & Latitude relative to the Galaxy.
pmra / pmdec	float64	Proper Motion: Angular velocity of the star across the sky (mas/yr).
d_pc	float64	Distance: Calculated distance from Earth in Parsecs ($1/parallax$).
x, y, z	float64	3D Cartesian: Heliocentric position relative to the Sun.
abs_m	float64	Absolute Magnitude: The intrinsic brightness of the star.
bp_rp	float32	Color Index: Difference between BP and RP (Temperature indicator).

3. Usage & Access (Streaming Mode)

Note: Due to the massive scale of this dataset (1B+ rows), downloading the full files to a local machine is not recommended. Use the Streaming Mode provided by the Hugging Face datasets library to process data on the fly:

from datasets import load_dataset

# Stream the dataset directly without downloading the full files
dataset = load_dataset("samfatnassi/gaia-dr3", split="train", streaming=True)

# Access a single stellar record
star_record = next(iter(dataset))
print(star_record)

4. Integration with SADIM-54M
This dataset serves as the foundational "knowledge base" for the SADIM-54M Model. While the dataset provides the raw observational facts, the model provides the analytical intelligence to predict and classify these stars.
5. Research & Ethics (Open Science)
This dataset is released under the Apache 2.0 License. It is provided as a contribution to Open Science and Humanity, encouraging researchers, students, and developers worldwide to explore the mysteries of our galaxy without boundaries.
Data Source: European Space Agency (ESA) Gaia Mission
Project Lead: KilmaAI / Sadim