AIDOC-AP - AI Documentation Application Profile
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AIDOC-AP - AI Documentation Application Profile

Release: 11 Nov, 2025

Modified on: 08 Jul, 2026
This version:
https://w3id.org/aidoc-ap/1.1
Revision:
1.1
Issued on:
04 Dec, 2025
Authors:
Sebastian Neumaier, University of Applied Sciences St. Pölten
Tobias Dam, University of Applied Sciences St. Pölten
Fabian Kovac, University of Applied Sciences St. Pölten
Contributors:
Timea Pahi, University of Applied Sciences St. Pölten
Publisher:
CERTAIN Project, University of Applied Sciences St. Pölten
Download serialization:
JSON-LD RDF/XML N-Triples TTL
License:
https://creativecommons.org/licenses/by/4.0/ License
Visualization:
Visualize with WebVowl
Evaluation:
Evaluate with OOPS!
Ontology Specification Draft

Introduction back to ToC

This ontology provides a semantic vocabulary for documenting AI systems and their lifecycle. Use the classes and properties defined here to create RDF graphs describing AI systems, their components (models, datasets), activities (training, deployment), and responsible agents (providers, deployers). The ontology extends W3C PROV and integrates with existing standards, and is explicitly grounded in the technical documentation obligation of Article 11 and Annex IV of the EU AI Act.

Terminology

An Application Profile is a data specification aimed to facilitate the data exchange in a well-defined application context. It re-uses concepts from one or more semantic data specifications, while adding more specificity, by identifying mandatory, recommended, and optional elements, addressing particular application needs, and providing recommendations for controlled vocabularies to be used. More information can be found on the SEMIC Style Guide.

Additional Resources

Explore additional resources linked to the AIDOC‑AP ontology.
📋

AI Act Requirements

List of technical documentation requirements extracted from EU AI Act Annex IV, with descriptions, lifecycle stages, and competency questions.

— requirements — competency questions
View all requirements →
📊

Coverage Analysis

How well AIDOC‑AP covers EU AI Act Annex IV — across ontology development iterations and by empirical, SPARQL‑based competency‑question answering on pilot knowledge graphs.

— avg coverage (final iter.) — pilots CQ‑tested
View coverage analysis →
🔗

Cross‑Ontology Alignments

Mappings between AIDOC‑AP terms and external ontologies (AIRO, VAIR, DPV, PROV‑O, etc.) with relation types and provenance.

— mappings — ontologies
View alignments →

AIDOC-AP: Overview back to ToC

This ontology has the following classes and properties.

Classes

Object Properties

Data Properties

Annotation Properties

Named Individuals

Cross-reference for AIDOC-AP classes, object properties and data properties back to ToC

This section provides details for each class and property defined by AIDOC-AP.

Classes

AI Activityc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#AIActivity

A superclass for all activities in the AI lifecycle, derived from prov:Activity.
has super-classes
Activity c
has sub-classes
Data Pipeline c, Machine Learning Pipeline c, Post-market Monitoring Activity c, Post-market Performance Evaluation Activity c, Software Code Pipeline c
is in domain of
affects op, has Frequency op
is in range of
has AI activity op

AI Agentc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#AIAgent

A superclass for all agents involved in the AI lifecycle, derived from prov:Agent.
has super-classes
Agent c
has sub-classes
AI Deployer c, AI Provider c, AI Researcher c, Auditor c
is in range of
has stakeholder op

AI Artifactc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#AIArtifact

A superclass for all tangible inputs and outputs of the AI lifecycle, derived from prov:Entity for provenance tracking.
has super-classes
Entity c
has sub-classes
AI Model c, Dataset c, Software Component c, Software Dependency c, Software Implementation c
is in domain of
depends on op, has risk op, is stored at op, requires hardware op
is in range of
affects op, depends on op, has component op, stores op

AI Deployerc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#AIDeployer

Any natural or legal person, public authority, agency or other body using an AI system under its authority except where the AI system is used in the course of a personal non-professional activity
Source
EU AI Act 2024/1689, Article 3(4)
has super-classes
A I Deployer c, AI Agent c, Agent c, Organization c
is in range of
is deployed by op

AI Methodc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#AIMethod

Reflects a mathematical algorithm which computes input data to execute an AI task.
has super-classes
Algorithm c
is in domain of
implements task op
is in range of
uses AI method op

AI Modelc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#AIModel

A computational representation that enables an AI method to execute an AI task.
has super-classes
AI Artifact c, Model c, Model c
is in domain of
has architecture dp, uses AI method op

AI Providerc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#AIProvider

A natural or legal person, public authority, agency or other body that develops an AI system or a general-purpose AI model or that has an AI system or a general-purpose AI model developed and places it on the market or puts the AI system into service under its own name or trademark, whether for payment or free of charge.
Source
EU AI Act 2024/1689, Article 3(3)
has super-classes
A I Provider c, AI Agent c, Agent c, Organization c
is in range of
is provided by op

AI Researcherc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#AIResearcher

A person involved in the technical development of an AI system.
has super-classes
AI Agent c, Agent c, Person c
is in range of
has responsible developer op

AI Systemc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#AISystem

An AI system is a machine-based system that is designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment, and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments.
Source
EU AI Act 2024/1689, Article 3(1)
has super-classes
A I System c, Entity c
is in domain of
applies standard op, depends on op, has architecture dp, has capability op, has changelog op, has component op, has declaration of conformity op, has human oversight op, has intended purpose op, has interface op, has lifecycle stage op, has modality op, has risk op, has software component op, has transparency measure op, has visual documentation op, is deployed by op, is provided by op, requires hardware op

AI System Capabilityc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#AISystemCapability

Represents a category of tasks or functions that an AI system can perform, such as sensory, knowledge, or control action processing.
is in range of
has capability op, supports capability op
has members
Action Control Processing ni, Communication Processing ni, Knowledge Processing ni, Sensory Input Processing ni

AI Taskc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#AITask

An action to achieve a specific goal using an AI model.
is in domain of
supports capability op
is in range of
implements task op

Auditorc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#Auditor

An organization or person responsible for reviewing the AI system for compliance.
has super-classes
AI Agent c, Agent c, Organization c, Person c

Build and Integration Testingc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#BuildAndIntegrationTesting

Activity of building system components and conducting integration testing.
has super-classes
Software Code Pipeline c

Change Logc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#ChangeLog

A log of changes made to the system during its lifecycle.
has super-classes
Entity c
is in domain of
has change record op
is in range of
has changelog op

Change Recordc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#ChangeRecord

A record of a change, including reason, start and end date, stakeholders, and the change itself.
has super-classes
Entity c
is in domain of
end date dp, has stakeholder op, reason for change dp, records change op, start date dp
is in range of
has change record op

Computational Resourcec back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#ComputationalResource

A computational resource used during the AI lifecycle, such as GPUs, CPUs, clusters or cloud instances.
has super-classes
Entity c
is in domain of
resource configuration dp, resource type dp, resource vendor dp
is in range of
provides computational resource op

Data Acquisition Activityc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#DataAcquisitionActivity

The activity of obtaining data from various sources.
has super-classes
Data Pipeline c

Data Cleaning Procedurec back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#DataCleaningProcedure

A procedure describing how data cleaning is performed, such as outlier detection and removal of invalid records.
has super-classes
Data Wrangling/Cleaning c
is in domain of
missing data strategy dp, outlier handling method dp, quality metrics used dp

Data Monitoring and Loggingc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#DataMonitoringAndLogging

Activity of capturing system events, performance, and traceability.
has super-classes
Data Pipeline c
is in domain of
logs activity op, produces log op, stores logs at op

Data Pipelinec back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#DataPipeline

The pipeline for data-centric activities in the AI lifecycle.
has super-classes
AI Activity c
has sub-classes
Data Acquisition Activity c, Data Monitoring and Logging c, Data Processing c, Data Testing c, Data Training c, Data Validation c, Data Wrangling/Cleaning c, Exploration and Validation c, Labeling Procedure c
is in domain of
has source dataset op, produces dataset op

Data Processingc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#DataProcessing

Activity of combining, preprocessing data resulting in a different dataset.
has super-classes
Data Pipeline c

Data Sheetc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#DataSheet

Structured documentation for a dataset or training configuration, including provenance, scope and main characteristics.
has super-classes
Entity c
has sub-classes
Training Data Sheet c

Data Testingc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#DataTesting

Activity of using datasets for model testing. Testing data means data used for providing an independent evaluation of the AI system in order to confirm the expected performance of that system before its placing on the market or putting into service.
Source
EU AI Act 2024/1689, Article 3(32)
has super-classes
Data Pipeline c
is in domain of
uses test data op

Data Trainingc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#DataTraining

Activity of using datasets for model training. Training data means data used for training an AI system through fitting its learnable parameters.
Source
EU AI Act 2024/1689, Article 3(29)
has super-classes
Data Pipeline c
is in domain of
uses training data op

Data Validationc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#DataValidation

Activity of using datasets for model validation. Validation data means data used for providing an evaluation of the trained AI system and for tuning its non-learnable parameters and its learning process in order, inter alia, to prevent underfitting or overfitting.
Source
EU AI Act 2024/1689, Article 3(30)
has super-classes
Data Pipeline c
is in domain of
uses validation data op

Data Wrangling/Cleaningc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#DataWrangling

Activity of ensuring data quality through cleaning, filtering, and enrichment.
has super-classes
Data Pipeline c
has sub-classes
Data Cleaning Procedure c

Datasetc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#Dataset

Represents a dataset used in the AI lifecycle.
has super-classes
AI Artifact c, Dataset c, Dataset c
is in domain of
data characteristic dp, data collection method dp, data scope dp, data selection criteria dp
is in range of
has source dataset op, produces dataset op, uses test data op, uses training data op, uses validation data op

Declaration of Conformityc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#DeclarationOfConformity

A document declaring the system's conformity with standards, such as the EU Declaration of Conformity.
has super-classes
Entity c
is in range of
has declaration of conformity op

Decommissioningc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#Decommissioning

Activity of taking a model out of production.
has super-classes
Software Code Pipeline c

Deploymentc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#Deployment

Activity of delivering the AI system to production environments.
has super-classes
Software Code Pipeline c

Explainable AI Featurec back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#ExplainableAIFeature

A specific feature designed to provide explanations for the AI system's output.
has super-classes
Transparency Measure c

Exploration and Validationc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#ExplorationAndValidation

Activity of reviewing data requirements, sources, and initial assessments.
has super-classes
Data Pipeline c

Hardware Componentc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#HardwareComponent

Represents the hardware required for an AI system to run.
has super-classes
Entity c
is in domain of
provides computational resource op
is in range of
requires hardware op

Human Oversight Mechanismc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#HumanOversightMechanism

A mechanism or measure to facilitate human intervention or supervision.
has super-classes
Entity c
is in range of
has human oversight op

Intended Purposec back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#IntendedPurpose

The use for which an AI system is intended by the provider, including the specific context and conditions of use, as specified in the instructions for use, promotional or sales materials and statements, and the technical documentation. Modelled as a class so that intended purposes can be related (e.g. via skos:broader/narrower), compared and tracked across system versions.
Source
EU AI Act 2024/1689, Article 3(12)
has super-classes
Intended Purpose c
is in range of
has intended purpose op

Interfacec back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#Interface

The interface provided for users or operators of an AI system.
has super-classes
A I Component c, Entity c
is in range of
has interface op

Labeling Procedurec back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#LabelingProcedure

An activity describing how data labels were assigned, including annotators, tools and guidelines.
has super-classes
Data Pipeline c
is in domain of
annotation tool dp, annotator type dp, labeling guideline dp

Logc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#Log

A record of system events, performance, and traceability.
has super-classes
Entity c
is in range of
produces log op

Machine Learning Pipelinec back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#MLPipeline

The pipeline for machine learning-centric activities in the AI lifecycle.
has super-classes
AI Activity c
has sub-classes
Model Engineering c, Model Evaluation c, Model Packaging c, Model Versioning c

Modalityc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#Modality

The form in which the AI system is provided or placed on the market (e.g. standalone software, a software service/API, a component embedded in a product, or a hardware product). Modelled as a class with a controlled vocabulary so provision forms can be enumerated, compared and reused across systems.
Source
EU AI Act 2024/1689, Annex IV(1)
is in range of
has modality op
has members
Cloud service ni, Embedded component ni, Hardware product ni, Software service / API ni, Standalone software ni

Model Engineeringc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#ModelEngineering

Activity of defining architecture, selecting algorithms, and training the model.
has super-classes
Experiment c, Machine Learning Pipeline c

Model Evaluationc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#ModelEvaluation

Activity of assessing performance, robustness, and accuracy.
has super-classes
Machine Learning Pipeline c
is in domain of
evaluation method dp, has performance metric op

Model Packagingc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#ModelPackaging

Activity of preparing the trained model for deployment.
has super-classes
Machine Learning Pipeline c

Model Versioningc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#ModelVersioning

Activity of managing revisions and tracking changes in model iterations.
has super-classes
Machine Learning Pipeline c

Performance Metricc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#PerformanceMetric

A metric used to evaluate the performance of an AI system.
has super-classes
Metric c
is in range of
has performance metric op

Post-market Monitoring Activityc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#PostMarketMonitoringActivity

Activity of monitoring the system's performance and behavior after deployment.
has super-classes
AI Activity c

Post-market Performance Evaluation Activityc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#PostMarketPerformanceEvaluationActivity

Activity of evaluating system performance in the post-market phase.
has super-classes
AI Activity c

Software Code Pipelinec back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#SoftwareCodePipeline

The pipeline for software development-centric activities in the AI lifecycle.
has super-classes
AI Activity c
has sub-classes
Build and Integration Testing c, Decommissioning c, Deployment c, Software Development c, Software Versioning c

Software Componentc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#SoftwareComponent

A logical or physical software component of the AI system, such as a service, module, or microservice participating in the overall processing.
has super-classes
AI Artifact c
is in domain of
feeds into component op
is in range of
feeds into component op, has software component op

Software Dependencyc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#SoftwareDependency

A software package or library that the AI system depends on.
has super-classes
AI Artifact c, Entity c, Software c

Software Developmentc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#SoftwareDevelopment

Activity of developing and writing software code for the AI system.
has super-classes
Software Code Pipeline c
is in domain of
has responsible developer op

Software Implementationc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#SoftwareImplementation

Represents the concrete, executable software that realizes an algorithm.
has super-classes
AI Artifact c, Implementation c

Software Versioningc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#SoftwareVersioning

Activity of managing revisions and tracking changes in software iterations.
has super-classes
Software Code Pipeline c

Standardc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#Standard

A harmonised or other standard applied to the AI system.
has super-classes
Entity c, Standard c
is in range of
applies standard op

Training Data Sheetc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#TrainingDataSheet

A data sheet focusing on training methodologies, techniques, hyperparameters and dataset usage for training, validation and testing.
has super-classes
Data Sheet c

Transparency Measurec back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#TransparencyMeasure

A feature or measure to ensure the transparency of an AI system.
has super-classes
Entity c
has sub-classes
Explainable AI Feature c
is in range of
has transparency measure op

Visual Documentationc back to ToC or Class ToC

IRI: https://w3id.org/aidoc-ap#VisualDocumentation

Visual documentation of an AI system including photographs, illustrations, diagrams, or renderings that show external features, internal layout, or markings as required by Annex IV.
has super-classes
Entity c
is in domain of
depicts dp
is in range of
has visual documentation op

Object Properties

affectsop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#affects

Links an activity to the artifact it affects or modifies.
has domain
AI Activity c
has range
AI Artifact c

applies standardop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#appliesStandard

Links an AI system to a standard it has applied for compliance.
has domain
AI System c
has range
Standard c

depends onop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#dependsOn

Links a system or component to its software.
has super-properties
has Part op
has domain
AI Artifact c or AI System c
has range
AI Artifact c

feeds into componentop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#feedsIntoComponent

Indicates that the output of one software component is used as input by another, forming part of the system's processing flow.
has domain
Software Component c
has range
Software Component c

has AI activityop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasAIActivity

Links an AI Lifecycle Phase to a specific AI Activity.
has domain
A I Lifecycle Phase c
has range
AI Activity c

has capabilityop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasCapability

Relates an AISystem to an AISystemCapability it is designed to exhibit or support
has domain
AI System c
has range
AI System Capability c

has change recordop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasChangeRecord

Links a ChangeLog to one or more ChangeRecords.
has domain
Change Log c
has range
Change Record c

has changelogop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasChangeLog

Links an AI system to its change log.
has domain
AI System c
has range
Change Log c

has componentop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasComponent

Links an AISystem to its constituent components like models and datasets.
has sub-properties
has software component op
has domain
AI System c
has range
AI Artifact c or A I Component c

has declaration of conformityop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasDeclarationOfConformity

Links an AI system to its EU Declaration of Conformity document.
has domain
AI System c
has range
Declaration of Conformity c

has Frequencyop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasFrequency

Specifies the frequency or recurrence pattern at which an AI activity is performed.
has domain
AI Activity c
has range
Frequency c

has human oversightop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasHumanOversight

Links an AI system to a mechanism for human oversight or intervention.
has domain
AI System c
has range
Human Oversight Mechanism c

has intended purposeop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasIntendedPurpose

Links an AI system to its intended purpose, modelled as an aidoc:IntendedPurpose resource rather than a plain string, so that purposes can be linked, compared and tracked across system versions.
Source
EU AI Act 2024/1689, Article 3(12)
has domain
AI System c
has range
Intended Purpose c

has interfaceop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasInterface

Links an AI system to the interface it provides to users or operators.
has domain
AI System c
has range
Interface c

has lifecycle stageop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasLifecycleStage

Links an AI system to its various phases throughout its entire lifecycle.
has domain
AI System c
has range
A I Lifecycle Phase c

has modalityop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasModality

Links an AI system to its form of provision, modelled as a resource rather than a plain string. The datatype property aidoc:modality is retained as a string shortcut for text-based documentation workflows.
has domain
AI System c
has range
Modality c

has performance metricop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasPerformanceMetric

Links an evaluation activity to the performance metric it uses.
has domain
Model Evaluation c
has range
Performance Metric c

has responsible developerop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasResponsibleDeveloper

Links a software development activity to the developers responsible for it.
has domain
Software Development c
has range
AI Researcher c or A I Developer c

has riskop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasRisk

Links an AI artifact (e.g., model or dataset) or an AI system to an associated risk. An AI risk can be modelled using the AIRO ontology. Risk means the combination of the probability of an occurrence of harm and the severity of that harm.
Source
EU AI Act 2024/1689, Article 3(2)
has domain
AI Artifact c or AI System c
has range
Risk c

has software componentop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasSoftwareComponent

Links an AI system to its software components, such as services or modules that participate in the overall processing.
has super-properties
has component op
has domain
AI System c
has range
Software Component c

has source datasetop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasSourceDataset

Links a DataPipeline activity to its source datasets.
has domain
Data Pipeline c
has range
Dataset c

has stakeholderop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasStakeholder

Links the change record to stakeholders (airo:stakeholder or aidoc-ap:AIAgent).
has domain
Change Record c
has range
AI Agent c or Stakeholder c

has transparency measureop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasTransparencyMeasure

Links an AI system to measures in place to ensure transparency.
has domain
AI System c
has range
Transparency Measure c

has visual documentationop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#hasVisualDocumentation

Links an AI system to visual documentation such as photographs, diagrams, or illustrations showing external features, markings, and internal layout.
has domain
AI System c
has range
Visual Documentation c

implements taskop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#implementsTask

Links an AIMethod to the AITask it is designed to perform.
has domain
AI Method c
has range
AI Task c

is deployed byop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#isDeployedBy

Links an AI system to its deployer.
has domain
AI System c
has range
AI Deployer c

is provided byop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#isProvidedBy

Links an AI system to its provider.
has domain
AI System c
has range
AI Provider c

is stored atop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#isStoredAt

Links an AI artifact to the location or entity where it is stored.
has domain
AI Artifact c
has range
Entity c
is inverse of
stores op

logs activityop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#logsActivity

Links a monitoring activity to the type of activity that is logged.
has domain
Data Monitoring and Logging c
has range
Activity c

produces datasetop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#producesDataset

Links a DataPipeline activity to the finished dataset it produces.
has domain
Data Pipeline c
has range
Dataset c

produces logop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#producesLog

Links a monitoring activity to the log it produces.
has domain
Data Monitoring and Logging c
has range
Log c

provides computational resourceop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#providesComputationalResource

Links a hardware component to the computational resource it provides.
has domain
Hardware Component c
has range
Computational Resource c

records changeop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#recordsChange

Links the change record to the change (airo:Change).
has domain
Change Record c
has range
Change c

requires hardwareop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#requiresHardware

Links a system or artifact to the hardware components or servers it needs to run.
has domain
AI Artifact c or AI System c
has range
Server c or Hardware Component c

storesop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#stores

Links a storage location or entity to the AI artifacts it stores.
has domain
Entity c
has range
AI Artifact c
is inverse of
is stored at op

stores logs atop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#storesLogsAt

Links a monitoring activity to where its logs are stored.
has domain
Data Monitoring and Logging c
has range
Entity c

supports capabilityop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#supportsCapability

Indicates that an AITask contributes to achieving a broader AISystemCapability.
has domain
AI Task c
has range
AI System Capability c

uses AI methodop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#usesAIMethod

Links an AI model to the specific AI method it is based on.
has domain
AI Model c
has range
AI Method c

uses test dataop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#usesTestData

Links a testing activity to the dataset used for testing.
has domain
Data Testing c
has range
Dataset c

uses training dataop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#usesTrainingData

Links a training activity to the dataset used for training.
has domain
Data Training c
has range
Dataset c

uses validation dataop back to ToC or Object Property ToC

IRI: https://w3id.org/aidoc-ap#usesValidationData

Links a validation activity to the dataset used for validation.
has domain
Data Validation c
has range
Dataset c

Data Properties

annotation tooldp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#annotationTool

Tool or platform used to perform annotation (e.g., internal tool, external labeling platform).
has domain
Labeling Procedure c
has range
string

annotator typedp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#annotatorType

Type of annotators involved in the labeling procedure (e.g., domain experts, laypersons, crowd workers).
has domain
Labeling Procedure c
has range
string

data characteristicdp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#dataCharacteristic

Project-specific summary of key characteristics of the dataset, such as feature types, label distributions, data modalities or known biases. For interoperable descriptions, individual variables SHOULD be modeled with schema:variableMeasured and quality aspects with dqv:hasQualityMeasurement / dqv:hasQualityAnnotation.
has domain
Dataset c
has range
string

data collection methoddp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#dataCollectionMethod

Project-specific description of the method used to collect the data (e.g., manual annotation, web scraping, sensor logs). For interoperability, this SHOULD be complemented with dcterms:provenance and, where appropriate, schema:measurementTechnique.
has domain
Dataset c
has range
string

data scopedp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#dataScope

Project-specific summary of the scope of the data contained in the dataset (e.g., population, geography, time period). For interoperable modeling, more specific aspects SHOULD be captured using dcterms:spatial, dcterms:temporal and dcterms:coverage.
has domain
Dataset c
has range
string

data selection criteriadp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#dataSelectionCriteria

Project-specific description of inclusion and exclusion criteria or sampling strategy used to select data for the dataset. Related sampling and bias information MAY also be represented using dqv:hasQualityAnnotation on the dataset or a dedicated sampling-plan resource.
has domain
Dataset c
has range
string

depictsdp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#depicts

Description of what the visual documentation shows (e.g., 'external view', 'internal layout', 'marking placement').
has domain
Visual Documentation c
has range
string

end datedp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#endDate

The end date of the change.
has domain
Change Record c
has range
date

evaluation methoddp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#evaluationMethod

The methodology used to evaluate a performance metric.
has domain
Model Evaluation c
has range
string

has architecturedp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#hasArchitecture

Links a system or model to a description of its architecture.
has domain
AI Model c or AI System c
has range
Literal

labeling guidelinedp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#labelingGuideline

Guidelines or instructions provided to annotators when assigning labels.
has domain
Labeling Procedure c
has range
string

missing data strategydp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#missingDataStrategy

Strategy for handling missing data (e.g., imputation, deletion, flagging).
has domain
Data Cleaning Procedure c
has range
string

outlier handling methoddp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#outlierHandlingMethod

Methods used to identify and handle outliers or other problematic records in the data.
has domain
Data Cleaning Procedure c
has range
string

quality metrics useddp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#qualityMetricsUsed

Data quality metrics or thresholds used to assess the dataset after cleaning.
has domain
Data Cleaning Procedure c
has range
string

reason for changedp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#reasonForChange

The reason for the change.
has domain
Change Record c
has range
string

resource configurationdp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#resourceConfiguration

Configuration details of the computational resource (e.g., number and type of GPUs, CPU cores, memory, accelerator type).
has domain
Computational Resource c
has range
string

resource typedp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#resourceType

Type of computational resource used (e.g., GPU cluster, CPU server, cloud instance).
has domain
Computational Resource c
has range
string

resource vendordp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#resourceVendor

Provider or vendor of the computational resource (e.g., cloud provider, hardware manufacturer).
has domain
Computational Resource c
has range
string

start datedp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#startDate

The start date of the change.
has domain
Change Record c
has range
date

versiondp back to ToC or Data Property ToC

IRI: https://w3id.org/aidoc-ap#version

The version of the AI system or artifact.
has domain
Entity c
has range
string

Annotation Properties

broad Matchap back to ToC or Annotation Property ToC

IRI: http://www.w3.org/2004/02/skos/core#broadMatch

broaderap back to ToC or Annotation Property ToC

IRI: http://www.w3.org/2004/02/skos/core#broader

close Matchap back to ToC or Annotation Property ToC

IRI: http://www.w3.org/2004/02/skos/core#closeMatch

contributorap back to ToC or Annotation Property ToC

IRI: http://purl.org/dc/terms/contributor

creatorap back to ToC or Annotation Property ToC

IRI: http://purl.org/dc/terms/creator

definitionap back to ToC or Annotation Property ToC

IRI: http://www.w3.org/2004/02/skos/core#definition

descriptionap back to ToC or Annotation Property ToC

IRI: http://purl.org/dc/terms/description

exact Matchap back to ToC or Annotation Property ToC

IRI: http://www.w3.org/2004/02/skos/core#exactMatch

fundingap back to ToC or Annotation Property ToC

IRI: https://schema.org/funding

homepageap back to ToC or Annotation Property ToC

IRI: http://xmlns.com/foaf/0.1/homepage

issuedap back to ToC or Annotation Property ToC

IRI: http://purl.org/dc/terms/issued

keywordsap back to ToC or Annotation Property ToC

IRI: https://schema.org/keywords

languageap back to ToC or Annotation Property ToC

IRI: http://purl.org/dc/terms/language

licenseap back to ToC or Annotation Property ToC

IRI: http://purl.org/dc/terms/license

mboxap back to ToC or Annotation Property ToC

IRI: http://xmlns.com/foaf/0.1/mbox

modifiedap back to ToC or Annotation Property ToC

IRI: http://purl.org/dc/terms/modified

nameap back to ToC or Annotation Property ToC

IRI: http://xmlns.com/foaf/0.1/name

narrow Matchap back to ToC or Annotation Property ToC

IRI: http://www.w3.org/2004/02/skos/core#narrowMatch

organizationap back to ToC or Annotation Property ToC

IRI: http://xmlns.com/foaf/0.1/organization

preferred Namespace Prefixap back to ToC or Annotation Property ToC

IRI: http://purl.org/vocab/vann/preferredNamespacePrefix

preferred Namespace Uriap back to ToC or Annotation Property ToC

IRI: http://purl.org/vocab/vann/preferredNamespaceUri

publisherap back to ToC or Annotation Property ToC

IRI: http://purl.org/dc/terms/publisher

related Matchap back to ToC or Annotation Property ToC

IRI: http://www.w3.org/2004/02/skos/core#relatedMatch

sourceap back to ToC or Annotation Property ToC

IRI: http://purl.org/dc/terms/source

titleap back to ToC or Annotation Property ToC

IRI: http://purl.org/dc/terms/title

Named Individuals

Action Control Processingni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#ActionControlProcessing

Action control processing refers to AI system capabilities that enable movement and control through mechanical, electronic, or software components, allowing simulation and execution of human-like behaviors, object manipulation, and natural gestures with high precision.
belongs to
AI System Capability c
has facts
broader ap AI System Capability c
definition ap "Action control processing refers to AI system capabilities that enable movement and control through mechanical, electronic, or software components, allowing simulation and execution of human-like behaviors, object manipulation, and natural gestures with high precision."

Classificationni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#Classification

Techniques that assign input data to predefined categories or classes.
belongs to
AI Method Category c
has facts
broader ap Supervised Learning ni
definition ap "Techniques that assign input data to predefined categories or classes."

Cloud serviceni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#CloudService

The AI system is provided as a managed cloud service.
belongs to
Modality c
has facts
broader ap Software service / API ni
definition ap "The AI system is provided as a managed cloud service."@en

Clusteringni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#Clustering

Techniques that group similar data points together based on their features.
belongs to
AI Method Category c
has facts
broader ap Unsupervised Learning ni
definition ap "Techniques that group similar data points together based on their features."

Communication Processingni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#CommunicationProcessing

Communication processing encompasses AI system capabilities for transmitting and exchanging information, either unidirectionally without feedback or bidirectionally and omnidirectionally with feedback, enabling content generation and interactive communication in individual or group contexts.
belongs to
AI System Capability c
has facts
broader ap AI System Capability c
definition ap "Communication processing encompasses AI system capabilities for transmitting and exchanging information, either unidirectionally without feedback or bidirectionally and omnidirectionally with feedback, enabling content generation and interactive communication in individual or group contexts."

Conversational Learningni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#ConversationalLearning

Methods that involve interactive learning through dialogue or feedback from users or other agents.
belongs to
AI Method Category c
has facts
broader ap Hybrid Learning ni
definition ap "Methods that involve interactive learning through dialogue or feedback from users or other agents."

Decision Makingni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#DecisionMaking

Approaches for selecting optimal actions under constraints or uncertainty.
belongs to
AI Method Category c
has facts
broader ap Traditional AI Techniques ni
definition ap "Approaches for selecting optimal actions under constraints or uncertainty."

Dimension Reductionni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#DimensionReduction

Techniques that reduce the number of features in the data while preserving important information.
belongs to
AI Method Category c
has facts
broader ap Unsupervised Learning ni
definition ap "Techniques that reduce the number of features in the data while preserving important information."

Embedded componentni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#EmbeddedComponent

The AI system is provided as a component embedded within a larger software or hardware product.
belongs to
Modality c
has facts
definition ap "The AI system is provided as a component embedded within a larger software or hardware product."@en

Graph-Based Semi-Supervised Learningni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#GraphBasedSemiSupervisedLearning

belongs to
AI Method Category c
has facts
broader ap Semi-Supervised Learning ni

Hardware productni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#HardwareProduct

The AI system is provided as, or integrated into, a physical hardware product.
belongs to
Modality c
has facts
definition ap "The AI system is provided as, or integrated into, a physical hardware product."@en

Hybrid Learningni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#HybridLearning

Methods that combine different learning paradigms, such as hybrid neuronal systems, learning with knowledge, and conversational learning.
belongs to
AI Method Category c
has facts
broader ap AI Method Category c
definition ap "Methods that combine different learning paradigms, such as hybrid neuronal systems, learning with knowledge, and conversational learning."

Hybrid Neuronal Systemsni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#HybridNeuronalSystems

Methods that combine neural architectures with symbolic reasoning or other AI techniques.
belongs to
AI Method Category c
has facts
broader ap Hybrid Learning ni
definition ap "Methods that combine neural architectures with symbolic reasoning or other AI techniques."

Knowledge Processingni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#KnowledgeProcessing

Knowledge processing refers to AI system capabilities for handling different types of knowledge—factual, conceptual, procedural, and metacognitive—through activities such as recognizing patterns, classifying information, generating concepts, executing procedures, and applying reflective reasoning to solve problems and adapt to new situations.
belongs to
AI System Capability c
has facts
broader ap AI System Capability c
definition ap "Knowledge processing refers to AI system capabilities for handling different types of knowledge—factual, conceptual, procedural, and metacognitive—through activities such as recognizing patterns, classifying information, generating concepts, executing procedures, and applying reflective reasoning to solve problems and adapt to new situations."

Knowledge Representationni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#KnowledgeRepresentation

Methods for structuring and organizing knowledge, including ontologies, semantic networks, and knowledge graphs.
belongs to
AI Method Category c
has facts
broader ap Symbolic AI ni
definition ap "Methods for structuring and organizing knowledge, including ontologies, semantic networks, and knowledge graphs."

Learning with Knowledgeni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#LearningWithKnowledge

Techniques that integrate both symbolic or explicit knowledge representation and machine learning approaches.
belongs to
AI Method Category c
has facts
broader ap Hybrid Learning ni
definition ap "Techniques that integrate both symbolic or explicit knowledge representation and machine learning approaches."

Logical Reasoningni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#LogicalReasoning

Methods that use rules and principles for formal as well as interactive verification to identify patterns and logical structures and make logical deductions.
belongs to
AI Method Category c
has facts
broader ap Symbolic AI ni
definition ap "Methods that use rules and principles for formal as well as interactive verification to identify patterns and logical structures and make logical deductions."

Machine Learningni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#MachineLearning

Methods that learn patterns from data, including supervised, unsupervised, semi-supervised, self-supervised, and reinforcement learning.
belongs to
AI Method Category c
has facts
broader ap AI Method Category c
definition ap "Methods that learn patterns from data, including supervised, unsupervised, semi-supervised, self-supervised, and reinforcement learning."

Model-Based Reinforcement Learningni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#ModelBasedReinforcementLearning

belongs to
AI Method Category c
has facts
broader ap Reinforcement Learning ni

Model-Free Reinforcement Learningni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#ModelFreeReinforcementLearning

belongs to
AI Method Category c
has facts
broader ap Reinforcement Learning ni

Modified Learning Conceptsni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#ModifiedLearningConcepts

belongs to
AI Method Category c
has facts
broader ap Semi-Supervised Learning ni

Non-Probabilistic Reasoningni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#NonProbabilisticReasoning

Techniques that do not rely on probabilistic models, such as qualitative procedures, rule-based approaches, reasoning with uncertainty as well as reasoning with belief functions.
belongs to
AI Method Category c
has facts
broader ap Symbolic AI ni
definition ap "Techniques that do not rely on probabilistic models, such as qualitative procedures, rule-based approaches, reasoning with uncertainty as well as reasoning with belief functions."

Optimizationni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#Optimization

Methods for improving solutions iteratively, including heuristic and metaheuristic approaches.
belongs to
AI Method Category c
has facts
broader ap Traditional AI Techniques ni
definition ap "Methods for improving solutions iteratively, including heuristic and metaheuristic approaches."

Planningni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#Planning

Approaches for autonomous and semi-autonomous planning procedures as well as plan recognition.
belongs to
AI Method Category c
has facts
broader ap Traditional AI Techniques ni
definition ap "Approaches for autonomous and semi-autonomous planning procedures as well as plan recognition."

Probabilistic Reasoningni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#ProbabilisticReasoning

Techniques that handle uncertainty and incomplete information using probabilistic models, such as Bayesian networks and Markov decision processes.
belongs to
AI Method Category c
has facts
broader ap Symbolic AI ni
definition ap "Techniques that handle uncertainty and incomplete information using probabilistic models, such as Bayesian networks and Markov decision processes."

Regressionni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#Regression

Techniques that predict continuous output values based on input data.
belongs to
AI Method Category c
has facts
broader ap Supervised Learning ni
definition ap "Techniques that predict continuous output values based on input data."

Reinforcement Learningni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#ReinforcementLearning

Techniques that learn optimal actions through trial and error by receiving feedback in the form of rewards or penalties.
belongs to
AI Method Category c
has facts
broader ap Machine Learning ni
definition ap "Techniques that learn optimal actions through trial and error by receiving feedback in the form of rewards or penalties."

Self-Supervised Learningni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#SelfSupervisedLearning

Techniques that generate their own labels from the input data to learn useful representations.
belongs to
AI Method Category c
has facts
broader ap Machine Learning ni
definition ap "Techniques that generate their own labels from the input data to learn useful representations."

Semi-Supervised Learningni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#SemiSupervisedLearning

Techniques that combine a small amount of labeled data with a large amount of unlabeled data during training.
belongs to
AI Method Category c
has facts
broader ap Machine Learning ni
definition ap "Techniques that combine a small amount of labeled data with a large amount of unlabeled data during training."

Sensory Input Processingni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#SensoryInputProcessing

Internal sensory processing refers to AI system capabilities for interpreting data about its own internal states, such as position, orientation, pose, spatial configuration, or physical integrity, enabling self-monitoring and maintaining stability or optimal functioning.
belongs to
AI System Capability c
has facts
broader ap AI System Capability c
definition ap "Internal sensory processing refers to AI system capabilities for interpreting data about its own internal states, such as position, orientation, pose, spatial configuration, or physical integrity, enabling self-monitoring and maintaining stability or optimal functioning."

Software service / APIni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#SoftwareService

The AI system is provided as a hosted service consumed over an interface such as a web API.
belongs to
Modality c
has facts
definition ap "The AI system is provided as a hosted service consumed over an interface such as a web API."@en

Standalone softwareni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#StandaloneSoftware

The AI system is provided as a standalone software application installed and run by the deployer.
belongs to
Modality c
has facts
definition ap "The AI system is provided as a standalone software application installed and run by the deployer."@en

Statistical Approachesni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#StatisticalApproaches

belongs to
AI Method Category c
has facts
broader ap Semi-Supervised Learning ni

Supervised Learningni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#SupervisedLearning

Techniques that learn from labeled data to make predictions or classifications.
belongs to
AI Method Category c
has facts
broader ap Machine Learning ni
definition ap "Techniques that learn from labeled data to make predictions or classifications."

Symbolic AIni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#SymbolicAI

Methods that use knowledge representation and logic-based reasoning to model knowledge and make inferences.
belongs to
AI Method Category c
has facts
broader ap AI Method Category c
definition ap "Methods that use knowledge representation and logic-based reasoning to model knowledge and make inferences."

Traditional AI Techniquesni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#TraditionalAI

Algorithmic strategies for search, optimization, planning and decision making
belongs to
AI Method Category c
has facts
broader ap AI Method Category c
definition ap "Algorithmic strategies for search, optimization, planning and decision making"

Unsupervised Learningni back to ToC or Named Individual ToC

IRI: https://w3id.org/aidoc-ap#UnsupervisedLearning

Techniques that identify patterns and structures in unlabeled data.
belongs to
AI Method Category c
has facts
broader ap Machine Learning ni
definition ap "Techniques that identify patterns and structures in unlabeled data."

Legend back to ToC

c: Classes
op: Object Properties
dp: Data Properties
ni: Named Individuals

Acknowledgments back to ToC

The authors would like to thank Silvio Peroni for developing LODE, a Live OWL Documentation Environment, which is used for representing the Cross Referencing Section of this document and Daniel Garijo for developing Widoco, the program used to create the template used in this documentation.