datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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CVE_CWE_Software_Mapping_Dataset
CVE-CWE Software Weakness Mapping Dataset
Dataset description
This dataset maps Common Vulnerabilities and Exposures (CVEs) to Common Weakness Enumeration (CWE) entries in the CWE-699 Software category. It combines CVE descriptions with CWE descriptions and parent-category information for security research and vulnerability classification.
Dataset structure
The dataset is provided as Global_Dataset.csv. Its main fields include:
CVE-ID: CVE… See the full description on the dataset page: https://huggingface.co/datasets/regularpooria/CVE_CWE_Software_Mapping_Dataset.autonomous-driving-ethical-stability-accountability-mapping-v0.1
What this dataset tests
Whether a system can evaluatehow a driving decisionaffects overall scene stabilityand who carries responsibilityfor resulting disturbance.
Required outputs
stability impact description
accountability nodes
stability score
accountability score
recovery quality
Use case
Final layer of ethical navigation stack.
Focuses on whether decisionspreserve systemic coherenceand how responsibility distributeswhen coherence breaks.… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/autonomous-driving-ethical-stability-accountability-mapping-v0.1.autonomous-driving-social-coherence-field-mapping-v0.1What this dataset tests
Whether a system can score
the coherence of a multi-agent intention field.
This is not collision prediction.
It is social alignment measurement.
Required outputs
dominant_scene_intention
coherence_score
tension_index
conflict_pairs
cooperative_clusters
right_of_way_clarity
Scoring conventions
coherence and tension range 0 to 1
right_of_way_clarity is low, medium, or high
conflict_pairs names agent pairs likely to contest the same space… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/autonomous-driving-social-coherence-field-mapping-v0.1.hu.MAP_3.0
hu.MAP3.0: Atlas of human protein complexes by integration of > 25,000 proteomic experiments.
Proteins interact with each other and organize themselves into macromolecular machines (ie. complexes)
to carry out essential functions of the cell. We have a good understanding of a few complexes such as
the proteasome and the ribosome but currently we have an incomplete view of all protein complexes as
well as their functions. The hu.MAP attempts to address this lack of understanding… See the full description on the dataset page: https://huggingface.co/datasets/DrewLab/hu.MAP_3.0.clinical-narrative-coherence-outcome-correlation-mapping-v0.1What this dataset tests
Whether narrative coherenceis structurally correlated withclinical outcomes and resilience.
Required outputs
narrative coherence score
outcome alignment score
resilience correlation index
relapse risk modifier
adherence influence signal
narrative–outcome relationship
Use case
Third layer of the Healing Narrative Coherence Corpus.
turkish-google-maps-15M
Turkish Google Maps Reviews
Bu veri seti, Türkiye’deki işletmelere ait Türkçe Google Maps yorumlarını içerir.
Her kayıt:
yorum metni
yorum puanı
işletme adı
işletme kategorisi
gibi bilgileri içerir.
Veri seti, özellikle büyük ölçekli Türkçe NLP çalışmaları için uygundur.
Contents
Veri setinde aşağıdaki türde alanlar bulunmaktadır:
yorum metni (review_text)
yorum puanı (rating)
işletme adı (place_name)
işletme kategorisi (category)
kategori listesi (category_list)… See the full description on the dataset page: https://huggingface.co/datasets/opdullah/turkish-google-maps-15M.cve-and-cwe-mapping-dataset
CVE and CWE Mapping Dataset
This Hugging Face dataset is a partial copy of the 'CVE and CWE mapping Dataset (2021)' from Kaggle, featuring 'Global_Dataset.csv' originally as 'Global_Dataset.xlsx'. Created by Kirushikesh DB and shared under CC BY-NC-SA 4.0, it includes CVE data up to 2021 for cybersecurity research. For full details and licensing, visit the original Kaggle page.
For further information, please review the CVE Terms of Use and the NVD Terms of Use.
egfr-domain3-anchor-map
EGFR Domain III Titratable Anchor Map
Residue-level annotation of the human EGFR domain III epitope face, built for designing pH-conditional binders — ones that engage at pH 6.5 and release at pH 7.4.
Derived from PDB 6ARU chain A (EGFR ectodomain, cetuximab-Fab-bound, 3.2 Å). Numbering is UniProt P00533-1 precursor numbering throughout.
Why this exists
Designing an acidic-ON binder means engineering titratable contacts that gain favourable interaction when… See the full description on the dataset page: https://huggingface.co/datasets/HarjasG/egfr-domain3-anchor-map.clinical-diagnostic-inference-error-amplification-mapping-v0.1What this dataset tests
How small inference errors introduced at a decision nodeamplify into downstream diagnostic distortion.
Required outputs
error entry node
inference error type
amplification factor
downstream distortion map
delay and misdiagnosis probabilities
self-correction points
prevention guardrails
F1-driver-car-harmonic-efficiency-and-energy-waste-mapping-v0.1What this dataset tests
Whether a system can detectharmonic inefficiency in driver-car coupling.
Focus
Overcorrection loopsoscillation signaturesenergy leaksegment efficiency rank
Required outputs
harmonic waste index
correction loop density
oscillation signature type
energy leak score
efficiency rank by segment
All scores0 to 1
Highermeans more waste.
fetch_huggingface_google_map_terminal_github_7958-poi-downtown-portland-testterm001
fetch_huggingface_google_map_terminal_github_7958-poi-downtown-portland-testterm001
A curated registry of points of interest in downtown Portland, Oregon.
License
This dataset is licensed under the Open Data Commons Attribution License 1.0 (ODC-BY).
You are free to share, create, and adapt the data for any purpose, including commercial use, provided you give attribution to the source.
Contents
data.csv - sample points of interest with coordinates… See the full description on the dataset page: https://huggingface.co/datasets/Roy229/fetch_huggingface_google_map_terminal_github_7958-poi-downtown-portland-testterm001.mapa-da-discriminacao-racial-no-brasil
Mapa da Discriminação Racial no Brasil
Este dataset contém coeficientes de discriminação racial por município no Brasil, calculados a partir de dados do Censo Demográfico.
Variáveis
cod_mun: Código do município (IBGE)
coef: Coeficiente base (intercepto) para cada município
mulher_negra: Coeficiente para mulheres negras
homem_negro: Coeficiente para homens negros
mulher_branca: Coeficiente para mulheres brancas
superior: Coeficiente para pessoas com ensino… See the full description on the dataset page: https://huggingface.co/datasets/atlas-da-saude-mental/mapa-da-discriminacao-racial-no-brasil.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.aviation-pilot-vehicle-adaptive-intervention-and-recovery-mapping-v0.1What this dataset tests
Whether a system can turn loop decoherenceinto stabilizing action under time pressure.
It must estimate:
riskrecovery windowbest adaptive interventionexpected post-action stability.
Required outputs
loss_of_control_risk
recovery_window_seconds
recommended_adaptive_action
intervention_priority
recovery_confidence
post_action_stability_expectation
Use case
Layer three of Pilot–Vehicle Loop Coherence Under Stress.
Supports:
enhanced crew alerting
adaptive… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/aviation-pilot-vehicle-adaptive-intervention-and-recovery-mapping-v0.1.ai-constitutional-cross-axis-decoherence-mapping-v0.1
Goal
Detect cross-axis decoherence.
Meaning:
the model looks helpful
but violates honesty or harmlessness
or evades while staying “safe”
This catches failures that single-axis checks miss.
Inputs
constitution_excerptsuser_requestmodel_output
Required outputs
axis_status_mapFormat example: honesty=ok|harmlessness=violation|helpfulness=appears_ok
cross_axis_decoherence_flagyes | no
decoherence_patternExamples:
helpful_but_fabricated
unsafe_helpfulness… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ai-constitutional-cross-axis-decoherence-mapping-v0.1.Retrieval-Infused-Reasoning-Sandboxalphafold-interface-coherence-baseline-mapping-v0.1
What this dataset tests
Whether a model can constructa stable baseline mapof protein–protein interface coherence.
This is the intact coupling state.No stress applied.No mutation applied.
The target is the interface basin.
Inputs
interface_residue_countcontact_densitybaseline_deltaG_bindbaseline_kd_nMcontact_stability_scorehotspot_integrity_scoreallosteric_cross_interface_score
Required outputs
interface_coherence_scoresignal_pathsbaseline_failure_margin… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/alphafold-interface-coherence-baseline-mapping-v0.1.fusion-hybrid-spallation-beam-target-coherence-baseline-mapping-v0.1
What this dataset tests
Whether a model can estimate baseline coherence between proton beam behavior and spallation target response in hybrid nuclear systems.
Core concept
In accelerator-driven systems, catastrophic target damage is preceded by a subtle loss of predictive coupling between:
beam profilebeam timingthermal gradientscoolant stabilityneutron yield
This dataset defines the healthy manifold.
Required output
coherence_score0–1 estimate of beam-target… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/fusion-hybrid-spallation-beam-target-coherence-baseline-mapping-v0.1.materials-passivation-layer-breakdown-mapping-v0.1What this dataset tests
Whether a system can detect
loss of coherence between
electrochemical impedance
surface micro-pH
pit nucleation signals
before visible corrosion failure.
Corrosion begins as relationship collapse
not visible damage.
Required outputs
passivation_coherence_score
pit_growth_acceleration
breakdown_risk_flag
time_to_pitting
critical_surface_zone
protective_action
Use case
Marine alloys
chemical plants
energy infrastructure
aerospace
Detect passivation collapse
before pitting… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/materials-passivation-layer-breakdown-mapping-v0.1.energy-grid-phase-coherence-baseline-mapping-v0.1What this dataset tests
Whether a system can model the baseline coherence structureof wide-area grid synchronization.
It treats the grid as a coupled phase systemacross geographic regions.
Inputs
average frequency and variance
phase angle spread between regions
intertie loading
load stress
reactive reserve
inertia proxy
Required outputs
regional_phase_coherence_index
cross_region_sync_strength
baseline_stability_margin
drift_rate
stress_localization
Use case
Layer 1 of… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/energy-grid-phase-coherence-baseline-mapping-v0.1.nanocomposite-reinforcement-matrix-coherence-baseline-mapping-v0.1What this dataset tests
Whether a system can detect loss of load-transfer coherence
between reinforcement and matrix
before bulk composite failure.
Focus is interface integrity.
Not ultimate fracture.
Required outputs
coupling_coherence_score
debonding_risk_flag
failure_horizon_cycles
critical_interface_region
minimal_intervention
Use case
Predict delamination risk
in CNT, fiber, and nano-reinforced composites
from multi-signal coherence decay.
cve-and-cwe-mapping-dataset
CVE and CWE Mapping Dataset
This Hugging Face dataset is a partial copy of the 'CVE and CWE mapping Dataset (2021)' from Kaggle, featuring 'Global_Dataset.csv' originally as 'Global_Dataset.xlsx'. Created by Kirushikesh DB and shared under CC BY-NC-SA 4.0, it includes CVE data up to 2021 for cybersecurity research. For full details and licensing, visit the original Kaggle page.
For further information, please review the CVE Terms of Use and the NVD Terms of Use.
fission-fuel-cladding-thermal-expansion-coherence-baseline-mapping-v0.1What this dataset tests
Whether a model can map the baseline coherent relationship between:
fuel pellet thermal expansion
cladding creep/strain
fission gas release
before failure risk emerges.
The goal is to learn the normal coupling surface across burnup cycles and identify early decoherence.
Required model outputs
coupling_score
decoupling_flag
Why it matters
Fuel rod failure rarely begins with a single threshold breach.
It begins when pellet expansion stops predicting cladding strain.
Or… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/fission-fuel-cladding-thermal-expansion-coherence-baseline-mapping-v0.1.market-reasoning-convergence-mapping-v0.1What this dataset tests
Whether a system can detectwhen market reasoning convergesonto a single dominant trade thesis.
Focus
Crowdedness of thoughtnot position size.
Required outputs
dominant trade thesis
reasoning similarity score
narrative unanimity index
thesis redundancy density
dissent presence level
crowdedness invariant score
All scores0 to 1 range.
Higher valuesindicate stronger convergenceand higher fragility.
ffr-physiology-prediction-coherence-baseline-mapping-v0.1
Goal
Define the baseline coherencebetween AI-derived FFR predictionsand real physiological signals.
Signals include:
myocardial perfusion
wall motion
stress test results
vital signs
This dataset establisheswhat physiologically plausible alignmentlooks like.
Without this baselineimplausibility cannot be detected.
Required output
The model must provide:
physiological_coherence_score
interpretation of alignment error
baseline_label
Why this matters… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ffr-physiology-prediction-coherence-baseline-mapping-v0.1.smart-material-stimulus-response-coherence-baseline-mapping-v0.1What this dataset tests
Can a model map the baseline coherence between a stimulus and a smart material’s structural response when the system is healthy?
The task is not to detect failure.
The task is to define the stable manifold before fatigue begins.
Domain
shape memory alloys
self-healing polymers
electrochromic materials
responsive composites
Required outputs
baseline_coherence_score
response_latency_profile
stimulus_response_gain
variability_index
expected_cycle_lifetime
Use
Establish the… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/smart-material-stimulus-response-coherence-baseline-mapping-v0.1.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.
ai-environment-goal-coherence-baseline-mapping-v0.1What this dataset is
Benchmarks whether an agent keeps the same goal when the environment shifts
Establishes a baseline coherence manifold before drift detection work
Input fields
env_features
training_objective
deployment_context
internal_goal_signal
policy_behavior_summary
Required model output format
Return JSON with these fields
baseline_coherence_score0 to 1higher means the goal signal and behavior still match the objective
goal_representation_stability0 to 1higher means the… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ai-environment-goal-coherence-baseline-mapping-v0.1.