AnalogicalModel
type: Class
subclass of: Model
alternative label: AnalogicalIcon
definition: A model that represents the internal logical structure of the object.
example: A physics equation is replicating the mechanisms internal to the object.
example: Electrical diagram is diagrammatic and resemblance
example: MODA and CHADA are diagrammatic representation of a simulation or a characterisation workflow.
scope note: A model that focus on HOW the object works.
scope note: The subclass of model inspired by Peirceian category (b) the diagram, whose internal relations, mainly dyadic or so taken, represent by analogy (with the same logic) the relations in something (e.g. math formula, geometric flowchart).

ArtificialIntelligenceModel
type: Class
subclass of: MathematicalModel
alternative label: ArtificialIntelligence
definition: A machine-based system that perceives its environment, pursues goals, adapts to feedback/change and provides information/takes action.

AtomicInteractionModel
type: Class
subclass of: AtomisticModel
definition: A physics-based model based on a physics equation describing the interaction between atoms.

AtomisticModel
type: Class
subclass of: MaterialsModel
example: A physics-based model based on a physics equation describing the behaviour of atoms.

AtomisticMolecularDynamics
type: Class
subclass of: AtomisticModel
definition: Atomistic model that models the physical movements of atoms and molecules over time by numerically solving Newton’s equations of motion.

ContinuumModel
type: Class
subclass of: MaterialsModel
example: A physics-based model based on a physics equation describing the behaviour of continuum volume.

CumulativeHypergeometricTest
type: Class
subclass of: StatisticalTest
definition: A statistical test that determines the statistical significance (p-value) of observing `k` or more/fewer successes in a sample drawn without replacement from a finite population. It tests if a subpopulation is over- or under-represented, often calculating `P(X>=k)` or `P(X<=k)`. It is essential for small populations where sampling changes probabilities.

DataBasedModel
type: Class
subclass of: MathematicalModel
definition: A mathematical model based on observed data, measurements, or experimental results.

DataProcessing
type: Class
subclass of: Computation
subclass of: Restriction
  on property: hasParticipant
  some values from: DataProcessingSoftware
definition: A computation that provides a data output following the elaboration of some input data, using a data processing application.

DataProcessingSoftware
type: Class
subclass of: Software
subclass of: Restriction
  on property: implementsModel
  some values from: MathematicalModel
alternative label: DataProcessingApplication
definition: A software program aimed for data processing.

ElectronicModel
type: Class
subclass of: MaterialsModel
definition: A physics-based model based on a physics equation describing the behaviour of electrons.
example: Density functional theory. Hartree-Fock.

FunctionalModel
type: Class
subclass of: Model
alternative label: FunctionalIcon
definition: A model that imitates one representative character of the object. It share external similarities with the object, but not necessarily the same internal logical structure.
example: A data based model is only a functional model, since it provide the same relations between the properties of the object (e.g., it can predict some properties as function of others) but is not considering the internal mechanisms (i.e., it can ignore the physics).
scope note: A model that focusing WHAT the object does.
scope note: This subclass of model inspired by Peirceian category (c) the metaphor, which represents the representative character of a sign by representing a parallelism in something else.

GenerativeAIModel
type: Class
subclass of: DeepLearningModel
alternative label: GenerativeArtificialIntelligenceModel
definition: An AI model that can generate new content, like text, images or code.
example: Chatbots

MachineLearningModel
type: Class
see also: Hutter F, Kotthoff L, Vanschoren J (2019) Automated Machine Learning. Springer, New York.
subclass of: DataBasedModel
subclass of: CognitionAndLearningModel
definition: AI model that learns progressively by discovering implicit patterns and performing an intellectual task without explicit instructions in advance.

MaterialsModel
type: Class
subclass of: PhysicsBasedModel
definition: A solvable set of one Physics Equation and one or more Materials Relations.

MathematicalModel
type: Class
subclass of: AnalogicalModel
subclass of: Information
definition: An analogical model expressed in mathematical language.
scope note: A mathematical model can be defined as a description of a system using mathematical concepts and language to facilitate proper explanation of a system or to study the effects of different components and to make predictions on patterns of behaviour. Abramowitz and Stegun, 1968

MesoscopicModel
type: Class
subclass of: MaterialsModel
example: A physics-based model based on a physics equation describing the behaviour of mesoscopic entities, i.e. a set of bounded atoms like a molecule, bead or nanoparticle.

NaturalLanguageProcessingModel
type: Class
subclass of: PerceptionModel
definition: An AI model that understands and generates human language.
example: Chatbots

PhysicsBasedModel
type: Class
is defined by: CEN Workshop Agreement, CWA 17284 Materials modelling - terminology, classification and metadata
subclass of: MathematicalModel
definition: A mathematical model based on a fundamental physics theory which defines the relations between physics quantities of an entity.

PhysicsEquation
type: Class
subclass of: PhysicsBasedModel
definition: An 'equation' that stands for a 'physical_law' by mathematically defining the relations between physics_quantities.
example: The Newton's equation of motion. The Schrödinger equation. The Navier-Stokes equation.

Replica
type: Class
subclass of: FunctionalModel
subclass of: ResemblanceModel
definition: A model that not only resembles the object, but also can express some of the object's functions.
example: A small scale replica of a plane tested in a wind gallery shares the same functionality in terms of aerodynamic behaviour of the bigger one.
example: Pinocchio is a functional model of a boy since it imitates the external behaviour without having the internal biological structure of a human being (it is made of magic wood...).

ResemblanceModel
type: Class
subclass of: Model
alternative label: ResemblanceIcon
definition: A model that mimics the spatial or temporal shape of the object.
example: A geographical map that imitates the shape of the landscape and its properties at a specific historical time.
scope note: A model that focus on WHERE/WHEN the object is, in the sense of spatial or temporal shape.
scope note: The subclass of model inspired by Peirceian category a) the image, which depends on a simple quality (e.g. picture).

StatisticalModel
type: Class
subclass of: MathematicalModel
definition: A mathematical model that embodies a set of statistical assumptions concerning the generation of sample data (and similar data from a larger population).

StatisticalTest
type: Class
subclass of: StatisticalModel
definition: A statistical model for analyzing data to determine if research results are significant and to decide whether to reject the null hypothesis, assessing if findings occurred by chance.

StructureManipulationModel
type: Class
subclass of: AtomisticModel
definition: A physics based model that manipulates atomic structures.

AbductiveReasoningModel
type: Class
subclass of: CognitionAndLearningModel
definition: Identifies the most plausible explanation for incomplete observations. Analogical Reasoning

Adaboost
type: Class
subclass of: Classification
definition: A supervised ensemble learning algorithm primarily used for classification and, less commonly, regression tasks.

AnalogicalReasoningModel
type: Class
subclass of: CognitionAndLearningModel
definition: Solves new problems by drawing parallels to known scenarios.

ArtificialNeuralNetwork
type: Class
subclass of: MachineLearningModel
alternative label: NeuralNetwork
definition: AI model inspired by the human brain, featuring interconnected layers of artificial neurons that process data to recognize complex patterns, make predictions, and drive machine learning, especially in tasks like computer vision and natural language processing.
definition: Neural networks learn by adjusting connection weights via training, with deep networks employing multiple layers for high-level abstraction.

Autoencoder
type: Class
subclass of: ArtificialNeuralNetwork
subclass of: DimensionalityReduction
definition: Neural networks designed to compress input data into a lower-dimensional bottleneck layer and then reconstruct it, effectively learning efficient, non-linear representations.

Bagging
type: Class
subclass of: PredictionLearningModel
definition: A prediction learning meta-algorithm designed to improve the stability and accuracy of predictive models, specifically by reducing variance and helping to avoid overfitting.

BehaviorModel
type: Class
subclass of: ArtificialIntelligenceModel
definition: AI systems trained on vast, multimodal datasets—including video, sensor data, and action logs—to understand, predict, and simulate human-like actions and complex decision-making processes.
scope note: Unlike LLMs that process text, LBMs focus on "what people do," utilizing reinforcement learning to adapt to dynamic environments.

Boosting
type: Class
subclass of: PredictionLearningModel
definition: A prediction learning ensemble model designed to improve the predictive performance of models by converting multiple "weak learners" (models with low predictive power, often simple decision trees) into a single "strong learner".

Classification
type: Class
subclass of: SupervisedLearningModel
definition: A supervised learning model that trains models using labeled data to categorize new, unseen data into predefined classes.

Clustering
type: Class
subclass of: UnsupervicedLearningModel
definition: An unsupervised learning model that automatically groups unlabeled data into clusters based on similarities in their features.

CognitionAndLearningModel
type: Class
subclass of: ArtificialIntelligenceModel
alternative label: Blends artificial intelligence with cognitive science to simulate human thought processes (sensing, reasoning, and learning) rather than just executing predefined rules.
alternative label: CognitiveAI

CollaborativeFiltering
type: Class
subclass of: RemommenderSystem
definition: A widely used recommender system model that primarily operates by leveraging similarities between users and items based on past interactions (like ratings or purchases).

Computation
type: Class
definition: Copmutation

ComputerVision
type: Class
subclass of: PerceptionModel
alternative label: MachineVision
definition: AI system that is able to acquire, understand and use digital images to recognize activities, objects, and images.

ContentExtraction
type: Class
subclass of: NaturalLanguageUnderstanding
definition: A natural language model tha tinvolves analyzing text to move beyond keyword matching, identifying the "who, what, and why" behind user input by extracting entities, themes, and semantic relationships.

ConvolutionNeuralNetwork
type: Class
subclass of: DeepLearningModel
definition: A type of deep learning based on feedforward neural network that learns features via filter (or kernel) optimization.

DecisionTree
type: Class
subclass of: Classification
definition: A non-parametric, supervised learning algorithm used for both classification and regression tasks.

DeepFeedForwardNetwork
type: Class
subclass of: DeepLearningModel
definition: Foundational deep learning model that approximate complex functions by mapping inputs to outputs through multiple, unidirectional hidden layers.

DeepLearningModel
type: Class
subclass of: ArtificialNeuralNetwork
definition: Machine learning based on artificial neural networks with multiple layers (often hundreds) that simulate the human brain's structure to learn complex, non-linear patterns from vast datasets.
scope note: Deep learning powers modern AI in image recognition, NLP, and generative models, outperforming traditional algorithms.

DimensionalityReduction
type: Class
subclass of: MachineLearningModel
definition: AI model that transforms high-dimensional datasets into lower-dimensional representations while preserving essential information, mitigating the "curse of dimensionality.

DynamicProgramming
type: Class
subclass of: ReinforcedLearningModel
definition: A reinforced learning model for solving complex problems by breaking them down into smaller, simpler subproblems and storing the results to avoid redundant calculations.

EnsembleLearningModel
type: Class
subclass of: MachineLearningModel
definition: A machine learning model that combines multiple individual models (often called base learners or weak learners) to produce a single, more accurate, and robust predictive model.

ExpertSystem
type: Class
subclass of: KnowledgeRepresentation
definition: AI system that contains manually inputted rules and data to copy human decision-making abilities.

ExtraTreesClassifier
type: Class
subclass of: Classification
subclass of: EnsembleLearningModel
definition: An ensemble learning model that builds multiple decision trees by choosing random splits for each node, rather than searching for the most discriminative threshold like Random Forest.

GenerativeAdversarialNetwork
type: Class
subclass of: DeepLearningModel
definition: A deep learning framework where two neural networks, the generator and discriminator, compete against each other to create new, synthetic instances of data (images, music, text) that resemble training data.

GraphBasedLearningModel
type: Class
subclass of: SemiSupervicedLearningModel
alternative label: GraphBasedAlgorithm
definition: A semi-superviced machine learning paradigm that analyzes data structured as nodes and edges, exploiting topological relationships rather than treating data points as independent.

GraphNeuralNetwork
type: Class
subclass of: DeepLearningModel
definition: Deep learning model designed to analyze data represented as graphs with nodes (entities) and edges (relationships).

HeuristicLearningModel
type: Class
subclass of: ReinforcedLearningModel
alternative label: HeuristicMethod
definition: An experience-based, discovery-oriented reinforced learning model to problem-solving that uses "rules of thumb," intuition, and mental shortcuts to find satisfactory solutions quickly when optimal ones are impractical.

ImageClassification
type: Class
subclass of: ComputerVision
definition: A core computer vision task that assigns a predefined label or category to an entire image based on its visual content.

ImageSegmentation
type: Class
subclass of: ComputerVision
definition: Computer vision algorithm for partitioning a digital image into distinct, meaningful regions at the pixel level to identify object boundaries and simplify image analysis.

Information
type: Class

KnowledgeRepresentation
type: Class
see also: Liu HC, You JX, Li Z, Tian G (2017) Fuzzy Petri nets for knowledge representation and reasoning: A literature review. Eng Appl Artif Intell 60:45–56.
subclass of: CognitionAndLearningModel
definition: Represent facts in the format of reusable knowledge. It combines a series of rules to simulate how a human brain functions through artificial means. It can make inferences and judgments based on knowledge provided by one or more experts and simulate human experts' decision-making process.

LargeLanguageModel
type: Class
subclass of: ModernGenerativeAIModel
subclass of: TextGeneration
alternative label: LLM
definition: A specialized subset of Generative Artificial Intelligence that is fundamentally defined by its use of transformer architecture (specifically encoders, decoders, or both) to process and generate human-like text by predicting the next token in a sequence.

LinearDiscriminantAnalysis
type: Class
subclass of: DimensionalityReduction
definition: A dimensionality reduction model used in classification tasks to find a feature subspace that maximizes class separability.

Logic
type: Class
subclass of: CognitionAndLearningModel
alternative label: DeductiveReasoning
definition: A AI system based on generic rules of the reasoning behind different cases of problem-solving.
example: If A=B and B=C, then A=C

LogisticRegressionModel
type: Class
subclass of: RegressionModel
definition: A fundamental supervised machine learning algorithm used for classification, predicting the probability of a categorical dependent variable.

LowDensitySeparationModel
type: Class
subclass of: SemiSupervicedLearningModel
definition: A semi-supervised model where the decision boundary between classes is placed in a low-density region of the data distribution.

MachineTranslation
type: Class
subclass of: NaturalLanguageUnderstanding
definition: A natural language understanding model that enables machine translation to move beyond word-for-word substitution by analyzing intent, context, and semantic meaning.

Model
type: Class

ModernGenerativeAIModel
type: Class
subclass of: GenerativeAIModel
subclass of: TransformerAI
definition: Generative AI based on the transformer architecture.

MonteCarloLearningModel
type: Class
subclass of: ReinforcedLearningModel
alternative label: MonteCarloMethod
definition: A model-free reinforcement learning model that estimates value functions by averaging total returns from complete episodes of experience.

NaiveBayes
type: Class
subclass of: Classification
definition: A family of supervised learning algorithms used for classification problems, such as spam detection and sentiment analysis.

NaturalLanguageClassification
type: Class
subclass of: NaturalLanguageUnderstanding
definition: A natural language understandig model that automatically assigns predefined categories, tags, or labels to unstructured text.

NaturalLanguageGeneration
type: Class
subclass of: NaturalLanguageProcessingModel
definition: A subfield of natural language processing (NLP) that automatically converts structured data or input into human-like written or spoken text.

NaturalLanguageUnderstanding
type: Class
subclass of: NaturalLanguageProcessingModel
definition: A subfield natural language processing (NLP) that enables machines to comprehend the intent, sentiment, and context behind human language.

ObjectDetection
type: Class
subclass of: ComputerVision
definition: A computer vision model that combines image classification and localization to identify, label, and locate multiple objects within images or videos.

PerceptionModel
type: Class
subclass of: ArtificialIntelligenceModel
alternative label: KnowledgeBasedInferenceEngine
definition: AI model that interact with the external world and process sensory information.

PlanningModel
type: Class
subclass of: CognitionAndLearningModel
alternative label: Planning
definition: System for intelligent planning and scheduling of tasks.

PredictionLearningModel
type: Class
subclass of: SupervisedLearningModel
alternative label: PredictiveModelling
definition: A branch of supervised learning that uses historical data, statistical algorithms, and data mining techniques to identify patterns and forecast future outcomes.

PrincipalComponentAnalysis
type: Class
subclass of: DimensionalityReduction
definition: linear feature extraction model that transforms data into a new set of variables (principal components) that maximize variance.

ProbabilityModel
type: Class
see also: Anastasopoulos A, Chiang D, Duong L (2016) An unsupervised probability model for speech-to-translation alignment of low-resource languages. arXiv preprint arXiv:1609.08139.
subclass of: CognitionAndLearningModel
alternative label: InductiveReasoning
definition: AI system based on the probabilistic relationships between variables based on mathematical models.
scope note: Generalizes from specific observations, identifying patterns to predict outcomes (probabilistic).

QSARModel
type: Class
subclass of: MathematicalModel
definition: A mathematical model (often a statistical correlation) relating one or more quantitative parameters derived from chemical structure to a quantitative measure of a property or activity (e.g. related to physical-chemical properties, ecotoxicology, environmental fate and transport, and human health hazards). QSARs are quantitative models yielding a continuous or categorical result.
scope note: The aim of a QSAR model is typically to reduce time, monetary cost and needed animal testing.
scope note: To facilitate practical application of (Q)SAR approaches in regulatory contexts by governments and industry and to improve their regulatory acceptance, the OECD (Q)SAR project has developed various outcomes such as the principles for the validation of (Q)SAR models, guidance documents as well as the QSAR Toolbox.

QuestionAnswering
type: Class
subclass of: NaturalLanguageUnderstanding
definition: A subfield of natural language processing and information retrieval that focuses on building systems capable of automatically answering questions posed by humans in natural language.

RandomForest
type: Class
subclass of: PredictionLearningModel
definition: A prediction learning model for classification and regression that builds multiple decision trees during training.

RemommenderSystem
type: Class
subclass of: SupervisedLearningModel
alternative label: Recommendation
definition: A information filtering system using supervised learning to suggest items most relevant to a particular user.

RecurrentNeuralNetwork
type: Class
subclass of: DeepLearningModel
definition: Neural network designed for sequential or time-series data, featuring feedback connections that allow information to persist.

RegressionModel
type: Class
subclass of: SupervisedLearningModel
definition: A supervised learning model used to predict continuous, numerical output values based on labeled training data.

ReinforcedLearningModel
type: Class
subclass of: MachineLearningModel
alternative label: ReinforcementLearning
definition: A machine learning model where an intelligent "agent" learns to make optimal, sequential decisions by interacting with an environment, using trial-and-error to maximize cumulative rewards.

SelfTrainingModel
type: Class
subclass of: SemiSupervicedLearningModel
definition: A semi-supervised machine learning model that improves model performance by iteratively labeling unlabeled data.

SemiSupervicedLearningModel
type: Class
subclass of: MachineLearningModel
definition: A machine learning paradigm that trains models using a small amount of labeled data combined with a large volume of unlabeled data.

SiameseNeuralNetwork
type: Class
subclass of: DeepLearningModel
definition: Class of neural network architectures containing two or more identical subnetworks with shared weights.

Software
type: Class

StepwiseRegressionModel
type: Class
subclass of: RegressionModel
definition: A regression model of fitting regression models in which the choice of predictive variables is carried out by an automatic procedure.

SupervisedLearningModel
type: Class
subclass of: MachineLearningModel
definition: A machine learning paradigm where models are trained using labeled data (input data paired with the correct output) to learn mapping functions that predict outcomes for new, unseen data.

SupportVectorMachine
type: Class
subclass of: Classification
alternative label: SVM
definition: Supervised machine learning algorithms used for classification, regression, and outlier detection.

TDistributedStochasticNeighborEmbedding
type: Class
subclass of: DimensionalityReduction
alternative label: t-SNE
definition: A non-linear dimensionality reduction model excellent for visualizing high-dimensional data in 2D or 3D.

TargetTracking
type: Class
subclass of: ComputerVision
definition: A computer vision model for automatically identifying objects in a video and interpreting them as a set of trajectories with high accuracy.

TextGeneration
type: Class
subclass of: NaturalLanguageGeneration
definition: Natural language subfield that focuses on automatically producing human-like, coherent, and contextually relevant text or speech from structured or unstructured data.

TransformerAI
type: Class
subclass of: DeepLearningModel
definition: Deep-learning architecture introduced by Google in 2017 that power modern generative AI like ChatGPT and Gemini.

UnsupervicedLearningModel
type: Class
subclass of: MachineLearningModel
definition: A type of machine learning that analyzes and clusters unlabeled datasets to discover hidden patterns, structures, or relationships without human intervention.

XGBoostRegressor
type: Class
subclass of: PredictionLearningModel
definition: An optimized machine learning algorithm that uses an ensemble of decision trees within a gradient boosting framework to predict continuous numerical values.
scope note: XGBoost Regressor is widely used in data science competitions and real-world applications due to its speed, performance, and features like built-in regularization and automatic handling of missing values.

Models
type: Ontology
abstract: The Models module of SSbD Core Ontology providing a taxonomy for models.
imports: reused-terms
version IRI: models
introduction: This module is a part of the [SSbD Core Ontology](https://ssbd-ontology.github.io/core/widoco/index-en.html). A model is a useful simplified description of a selected part of the world. A figure showing how the SSbD Core Ontology categorise models can be found [here](https://ssbd-ontology.github.io/core/docs/models.html).