datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
adsb
ADSB Historical Aircraft Traces
This dataset is a collection of historical ADSB.lol aircraft traces, converted to Parquet.
Source and License
The source data comes from the ADSB.lol historical data archive. It is distributed under the Open Database License (ODbL) 1.0.
tartanaviation-atc-adsb-utterances
TartanAviation ATC + ADS-B (Utterances)
Speech utterances split from twangodev/tartanaviation-atc-adsb
by voice-activity detection (pyannote/segmentation-3.0).
Each row is one speech segment (16 kHz mono) with the ADS-B from its parent clip.
531,050 utterances · ~398 h speech · 16 kHz mono · 67% carry ADS-B. From 40,899 of 41,823 clips
(silent clips have no utterances). Built with squawk.
Usage
from datasets import load_dataset
ds =… See the full description on the dataset page: https://huggingface.co/datasets/twangodev/tartanaviation-atc-adsb-utterances.tartanaviation-atc-adsb
TartanAviation ATC + ADS-B
Paired ATC audio and ADS-B for Pittsburgh KAGC and KBTP, aligned from CMU
TartanAviation. Each row is one ADS-B-triggered
audio capture (16 kHz mono) plus the aircraft tracks present during it.
41,823 clips · 16 kHz mono · 67% carry ADS-B. Built with squawk.
Usage
from datasets import load_dataset
ds = load_dataset("twangodev/tartanaviation-atc-adsb", split="train", streaming=True)
ex = next(iter(ds))
ex["audio"] # {'array': ...… See the full description on the dataset page: https://huggingface.co/datasets/twangodev/tartanaviation-atc-adsb.adsblol_globe_historysample-adsb100K dataset schema ADSB
Sample raw:
"icao_address","aircraft_type","callsign","flight","origin","origin_name","destination","destination_name","altitude","speed","heading","lat","lon","timestamp","country","status"
"AF622D","A20N","SVMGL766","SQW3952","KJFK","SwasIxUFQknZtDA","VTBS","YnxtCQBvbmxgcJO",29015,443,265,77.49,-140.06,"2023-11-03T08:57:24","SG","landed"
"81B676","E195","GITUA615","XAI5321","WIII","qymDgLDkhuEgInJ","LFPG","GkELxVBOZesHojP",40691,402,108,69.15,-140.78… See the full description on the dataset page: https://huggingface.co/datasets/flatseek/sample-adsb.adsb-coretartanaviation-adsb-19k-clean
TartanAviation ADS-B Dataset (19.7K Clean Samples)
Dataset Description
19,714 high-quality ADS-B trajectory datapoints from aircraft operations, rigorously cleaned and validated. Perfect for machine learning research in aviation, reinforcement learning, and trajectory prediction.
Key Features
19,714 clean samples (no missing data, no duplicates)
17 comprehensive features including aircraft ID, timestamp components, altitude, speed, heading, geolocation, and… See the full description on the dataset page: https://huggingface.co/datasets/SANIKKI/tartanaviation-adsb-19k-clean.ADSBtartanaviation-adsb-19k-clean
TartanAviation ADS-B Dataset (19.7K Clean Samples)
Dataset Description
19,714 high-quality ADS-B trajectory datapoints from aircraft operations, rigorously cleaned and validated. Perfect for machine learning research in aviation, reinforcement learning, and trajectory prediction.
Key Features
19,714 clean samples (no missing data, no duplicates)
17 comprehensive features including aircraft ID, timestamp components, altitude, speed, heading, geolocation, and… See the full description on the dataset page: https://huggingface.co/datasets/Pathange/tartanaviation-adsb-19k-clean.aeroscope-adsb-anomaly-benchmark
AeroScope ADS-B Anomaly Benchmark v1
A free, openly-licensed benchmark for evaluating ADS-B anomaly and spoofing detectors. It pairs
real airborne ADS-B traffic with synthetically injected attacks following the standard taxonomy in the
ADS-B security literature, so detectors can be compared on a shared, labelled, reproducible dataset.
918 rows — 459 real / 459 injected (balanced)
38 documented columns — raw ADS-B fields, integrity fields (NIC/NACp/NACv/SIL), and derived… See the full description on the dataset page: https://huggingface.co/datasets/Muhammaduazir69/aeroscope-adsb-anomaly-benchmark.adsbiq-caribbean-aircraft-data
ADSBiq Caribbean aircraft state-diff sample
This repository contains a reproducible 100,000-row educational sample from
the ADSBiq daily open ADS-B corpus. It covers positioned observations between
5–30° N and 95–55° W on 2026-06-29 and is intended for classroom, geospatial,
stream-processing, and machine-learning exploration.
The complete dataset is published as one zstd-compressed Parquet file per UTC
day in monthly GitHub releases:
Complete daily corpus
Schema and… See the full description on the dataset page: https://huggingface.co/datasets/jsals/adsbiq-caribbean-aircraft-data.tartanaviation-adsb-19k-clean
TartanAviation ADS-B Dataset (19.7K Clean Samples)
Dataset Description
19,714 high-quality ADS-B trajectory datapoints from aircraft operations, rigorously cleaned and validated. Perfect for machine learning research in aviation, reinforcement learning, and trajectory prediction.
Key Features
19,714 clean samples (no missing data, no duplicates)
17 comprehensive features including aircraft ID, timestamp components, altitude, speed, heading… See the full description on the dataset page: https://huggingface.co/datasets/RunningCFOP/tartanaviation-adsb-19k-clean.tartanaviation-adsb-19k-clean
TartanAviation ADS-B Dataset (19.7K Clean Samples)
Dataset Description
19,714 high-quality ADS-B trajectory datapoints from aircraft operations, rigorously cleaned and validated. Perfect for machine learning research in aviation, reinforcement learning, and trajectory prediction.
Key Features
19,714 clean samples (no missing data, no duplicates)
17 comprehensive features including aircraft ID, timestamp components, altitude, speed, heading, geolocation, and… See the full description on the dataset page: https://huggingface.co/datasets/Gogul001/tartanaviation-adsb-19k-clean.lookupjet-adsb-optical-tracking-jets-airplanes-aviation-samplesnull
Lookup-Jet: Multimodal Aviation Tracking Dataset
Overview
The Lookup-Jet Dataset is an industry-grade, sensor-fusion dataset designed for advanced computer vision and machine learning tasks. It combines high-resolution visual tracking (bounding boxes and polygon segmentations) of aircraft with synchronized ADS-B kinematics, environmental conditions, and astronomical data.
This dataset is pre-formatted for immediate deployment across standard ML frameworks… See the full description on the dataset page: https://huggingface.co/datasets/Lookupjet/lookupjet-adsb-optical-tracking-jets-airplanes-aviation-samples.adsbadbadsbadbadsbadbv