datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
shippingus-airline-aerospace-defense-layoffs-warn-act-notices-daily
US airline, aerospace and defense layoffs — the actual WARN Act filings, rebuilt every day
Last rebuilt: 2026-09-23. 1,551 layoff and closure notices filed by
airlines and regional carriers, airport ground-handling and catering contractors, aircraft and engine makers, avionics and airfoil shops, and defense and space primes and their suppliers with US state labor departments — 308,032 workers,
301 employers, 45 states, 1989–2026.
172 of the notices (11.1%) were recorded by the… See the full description on the dataset page: https://huggingface.co/datasets/APProjects/us-airline-aerospace-defense-layoffs-warn-act-notices-daily.spc-tornado-history
NOAA / SPC Tornado History (1950–2024)
Bundled for Aerostratospheric / UOGW tornado-trend research. Source of record: NOAA Storm Prediction Center Severe Weather Database.
Contents
1950-2024_all_tornadoes.csv / 1950-2024_actual_tornadoes.csv — SPC actual tornado segment CSV
schema.json — provenance metadata
Bundled UTC: 2026-09-18T15:47:02Z
License / attribution
US Government work redistributed by SPC for public use. You must attribute NOAA/SPC… See the full description on the dataset page: https://huggingface.co/datasets/aerostratospheric/spc-tornado-history.aerogel-structural-manifold-integrity-v0.1Goal
Detect when an aerogel loses structural integrity before visible collapse.
Core idea
Aerogel failure is not a single crack.It is a distortion of the vibration–density–pore manifold.
Three signals must stay coherent:
densityelastic moduluspore network structure
When they decouple, collapse follows.
Inputs
bulk density
nanoindentation modulus
pore size distribution
load cycling
acoustic or strain indicators
Required outputs
structural_coherence_score
manifold_distortion_rate… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/aerogel-structural-manifold-integrity-v0.1.aerospace-interpretation-assumption-control-v01Interpretation and Assumption Control v01
What this dataset is
This dataset evaluates whether a system handles incomplete or ambiguous aerospace information without inventing structure.
You give the model:
A partial flight, performance, or guidance task
Incomplete configuration or environmental data
An analysis request that appears reasonable
You ask it to choose a response.
PROCEED
CLARIFY
REFUSE
The correct move is often to stop.
Why this matters
Aerospace failures rarely come from math… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/aerospace-interpretation-assumption-control-v01.AeroQAf1-latent-cross-coupling-aero-balance-instability-v0.1
What this repo does
This repository introduces a Clarus dataset for detecting latent instability under cross-coupled conditions in Formula 1 aero-balance systems.
The goal is to identify race states in which aero balance may still appear outwardly stable or only mildly anomalous but already contains hidden internal instability that may activate into sudden balance loss once interacting pressures exceed containment.
Core structure
This dataset models a pre-failure geometry… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/f1-latent-cross-coupling-aero-balance-instability-v0.1.aviation-propulsion-aerodynamics-coherence-baseline-v0.1What this dataset tests
Whether a system can model the normal coupling
between propulsion parameters and aerodynamic state.
The signal is relationship shape and lag
not threshold breaches.
Required outputs
coupling_coherence_index
baseline_correlation_matrix
phase_alignment_score
stability_envelope
lag_profile
baseline_confidence
Scoring conventions
all scores range 0 to 1
stability envelope is a low-high interval
lag profile describes expected response delays in seconds… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/aviation-propulsion-aerodynamics-coherence-baseline-v0.1.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.ams_data_train_generic_v0.1_100Question and answer pairs for the first 100 entries of aerospace mechanism symposia 5000 word chunk entries. Full file of entries is here: https://github.com/dsmueller3760/aerospace_chatbot/blob/llm_training/data/AMS/ams_data_answers.jsonl
See this repository for details: https://github.com/dsmueller3760/aerospace_chatbot/tree/main
Prompts generated using TheBloke/Llama-2-7B-Chat-GGUF
SalesDatasomosnlp-2026-aerospace
Dataset Card: Conjunto de Datos Aeroespacial y Cultural Completo
Resumen del Dataset
Este conjunto de datos ha sido diseñado específicamente para la evaluación cultural, lingüística y de alineación de Modelos de Lenguaje (LLMs) en el ámbito iberoamericano, con un foco especial en la historia aeroespacial, técnica, científica e histórica.
Contiene 1.716 interacciones de tipo conversacional (multi-turn) distribuidas en múltiples países de habla hispana y portuguesa.… See the full description on the dataset page: https://huggingface.co/datasets/somosnlp-hackathon-2026/somosnlp-2026-aerospace.ams_data_train_mistral_v0.1_100Question and answer pairs for the first 100 entries of aerospace mechanism symposia 5000 word chunk entries. Full file of entries is here: https://github.com/dsmueller3760/aerospace_chatbot/blob/llm_training/data/AMS/ams_data_answers.jsonl
See this repository for details: https://github.com/dsmueller3760/aerospace_chatbot/tree/main
Prompts generated using TheBloke/Llama-2-7B-Chat-GGUF
Format representative of mistral's instruct llms:
https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1… See the full description on the dataset page: https://huggingface.co/datasets/ai-aerospace/ams_data_train_mistral_v0.1_100.F1-aero-pressure-coherence-mapping-v0.1What this dataset tests
Whether a system can detectlocalized aero coherence lossfrom pressure sensor fields.
Focus
Platform coherencezone asymmetryvortex integritylocalized collapse zonesbalance shift risk
Required outputs
platform coherence score
zone pressure asymmetry index
vortex system integrity flags
localized collapse zones
balance shift risk score
All scores0 to 1
Higher coherencemeans unified platform.
Higher asymmetry and balance riskmean localized collapse is likely.
regime-phase-recognition-aerospace-v01Regime and Phase Recognition v01
What this dataset is
This dataset evaluates whether a system recognizes when the governing aerospace regime or flight phase has changed.
You give the model:
Vehicle class and example
Speed or Mach number
Altitude and atmospheric context
Angle of attack or maneuver
A stated modeling assumption
You ask one question.
Are the same rules
still valid here
Why this matters
Aerospace failures often occur at boundaries.
Common failure patterns:
Treating transonic flow… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/regime-phase-recognition-aerospace-v01.F1-aero-platform-recovery-and-stability-gradient-v0.1What this dataset tests
Whether a system can maphow an aero platform recovers after localized collapseand identify fragile zones that persist.
Focus
Recovery pathstability gradient across zonespersistent imbalancerecovery latencyfragility hotspotsnext collapse risk
Required outputs
recovery path profile
stability gradient map
persistent imbalance flags
recovery latency score
fragility hotspots
next collapse risk score
All indices0 to 1
Higher latency and next riskmean slower… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/F1-aero-platform-recovery-and-stability-gradient-v0.1.F1-aero-localized-collapse-trigger-detection-v0.1What this dataset tests
Whether a system can link disturbancesto localized aero collapse events.
Focus
Trigger typecollapse locationonset latencyrecovery timespread riskbalance shift linkage
Required outputs
trigger event type
trigger location zone
collapse onset latency
coherence recovery time
collapse spread risk
disturbance to balance shift score
All indices0 to 1
Timesin seconds
Higher spread riskmeans collapse likely propagates across the platform.
aviation-propulsion-aerodynamics-decoherence-precursor-detection-v0.1What this dataset tests
Whether a system can detect early decoherence
between propulsion behavior and aerodynamic response.
The signal is relationship drift:
lag expansion
correlation collapse
nonlinear divergence
oscillatory mismatch.
Required outputs
decoherence_onset_time
precursor_pattern_type
severity_gradient
failure_likelihood_index
estimated_time_to_critical_min
primary_decoupling_channels
Scoring conventions
onset time is minutes from window start
severity and… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/aviation-propulsion-aerodynamics-decoherence-precursor-detection-v0.1.aviation-propulsion-aerodynamics-failure-horizon-intervention-mapping-v0.1What this dataset tests
Whether a system can turn detected decoherence
into an operational action plan.
It must estimate horizon,
choose intervention,
and define the decision window.
Required outputs
failure_horizon_minutes
recommended_derate_level
diversion_priority
stability_recovery_probability
intervention_window
action_rationale_channels
Scoring conventions
horizon is minutes to critical instability
diversion priority is low, medium, high, or urgent
intervention window is… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/aviation-propulsion-aerodynamics-failure-horizon-intervention-mapping-v0.1.AeroPredict10K
Dataset Card for AeroPredict10K
Dataset for UIUC CS441 Final Project -- AeroPredict: Transformer-Based Real-Time Flight Delay Predictor
aerospace_turbine_telemetry_logsdataset_aeroespacial_cultural_completo.csv
🚀 LATAM Aerospace Cultural QA
Dataset culturalmente alineado para modelos conversacionales en español y portugués, especializado en historia aeroespacial iberoamericana.
Desarrollado para el #HackathonSomosNLP 2026 — ¿Son los LLMs realmente multiculturales?
🛠 Metodología y Pipeline de Construcción
La versión actual del dataset ha sido refinada mediante un pipeline automatizado diseñado para maximizar la calidad y la diversidad cultural:
Generación Dinámica: Se generan… See the full description on the dataset page: https://huggingface.co/datasets/AngelGabrielTroncoso/dataset_aeroespacial_cultural_completo.csv.Aeroguard-Dataset