Model Concepts (OWL Ontology)
Extension ontology for modeling ML-enabled system architectures.
Provides element types, relationship types, stakeholders, concerns, and viewpoints
for describing the ML aspects of software systems — training pipelines, model serving,
feature engineering, data lineage, and the integration boundary between ML and non-ML
components.
Motivated by the gap identified in Moin et al. (2023): existing architecture frameworks
lack stakeholders, viewpoints, and model kinds for data scientists, data engineers, and
ML engineers. This extension addresses that gap within the Linked.Archi ecosystem.
Trademarked names referenced herein are property of their respective owners.
https://meta.linked.archi/ml-systems/onto#
Formal Rules (SHACL Shapes)
SHACL shapes for validating ML-enabled system architecture models.
Enforces governance rules: every ML model must have versioning, monitoring,
and dataset lineage; every serving infrastructure must have latency SLAs.
https://meta.linked.archi/ml-systems/shapes#
Concept Classification (SKOS)
Classification of ML-enabled system concepts by lifecycle phase and component role.
https://meta.linked.archi/ml-systems/tax#MLSystemsConceptScheme
