Linked.Archi ML-Enabled Systems Taxonomy
type: Ontology
imports: core#
license: http://creativecommons.org/licenses/by/4.0/
preferred namespace prefix: mlsystax
creator: Kalin Maldzhanski
description: SKOS taxonomy classifying ML-enabled system concepts by lifecycle phase and component role.
created: 2026-05-03
modified: 2026-05-03
publisher: Linked.Archi
publisher: linked.archi
status: draft
version IRI: 0.1.0#
version info: 0.1.0

ML-Enabled Systems Concept Scheme
type: ConceptScheme
definition: Classification of ML-enabled system concepts by lifecycle phase and component role.
has top concept: By Lifecycle Phase
has top concept: By Component Role
has top concept: By Stakeholder Domain

By Lifecycle Phase
type: Concept
top concept of: ML-Enabled Systems Concept Scheme
in scheme: ML-Enabled Systems Concept Scheme

Data Preparation
type: Concept
broader: By Lifecycle Phase
definition: Phase covering data collection, cleaning, labeling, and feature engineering.
in scheme: ML-Enabled Systems Concept Scheme

Model Development
type: Concept
broader: By Lifecycle Phase
definition: Phase covering algorithm selection, training, evaluation, and experiment tracking.
in scheme: ML-Enabled Systems Concept Scheme

Model Deployment
type: Concept
broader: By Lifecycle Phase
definition: Phase covering model packaging, serving infrastructure setup, and production release.
in scheme: ML-Enabled Systems Concept Scheme

Model Monitoring
type: Concept
broader: By Lifecycle Phase
definition: Phase covering production monitoring, drift detection, and retraining triggers.
in scheme: ML-Enabled Systems Concept Scheme

By Component Role
type: Concept
top concept of: ML-Enabled Systems Concept Scheme
in scheme: ML-Enabled Systems Concept Scheme

Inference Component
type: Concept
broader: By Component Role
definition: Components that perform prediction or inference — models and serving infrastructure.
in scheme: ML-Enabled Systems Concept Scheme

Data Management Component
type: Concept
broader: By Component Role
definition: Components that manage data flow — pipelines, feature stores, datasets.
in scheme: ML-Enabled Systems Concept Scheme

Orchestration Component
type: Concept
broader: By Component Role
definition: Components that orchestrate ML workflows — training pipelines, experiment trackers.
in scheme: ML-Enabled Systems Concept Scheme

Governance Component
type: Concept
broader: By Component Role
definition: Components that support ML governance — model registries, monitoring, audit trails.
in scheme: ML-Enabled Systems Concept Scheme

By Stakeholder Domain
type: Concept
top concept of: ML-Enabled Systems Concept Scheme
in scheme: ML-Enabled Systems Concept Scheme

Analytics Modeling (Data Science)
type: Concept
broader: By Stakeholder Domain
definition: The domain of data scientists — algorithm selection, model training, evaluation.
in scheme: ML-Enabled Systems Concept Scheme

Analytics Operations (Data Engineering)
type: Concept
broader: By Stakeholder Domain
definition: The domain of data engineers — deployment, serving, monitoring, pipeline management.
in scheme: ML-Enabled Systems Concept Scheme

ML Governance
type: Concept
broader: By Stakeholder Domain
definition: The domain of ethics officers and compliance — fairness, explainability, privacy, audit.
in scheme: ML-Enabled Systems Concept Scheme