SemGen

SemGen facilitates modular composition and semantic annotation of physiological biosimulation models using composite annotations that integrate multiple reference ontologies.

Key Features:

• Composite Annotations: Uses composite annotations that combine multiple reference ontologies to capture the physics-based meaning of model variables with high semantic expressivity.
• Model Merging and Interoperability: Disambiguates model elements via semantic annotations to support merging of models and interoperability across different simulation frameworks and datasets.
• Ontology Integration: Links and connects multiple reference ontologies to represent semantics that a single ontology cannot encompass, enabling cross-ontological references.

Scientific Applications:

• Physiological biosimulation: Enables semantically precise representation of biological entities and processes within physiological simulation models.
• Model integration and reuse: Supports merging models from diverse sources while preserving semantic integrity for collaborative research and interoperability between datasets and frameworks.

Methodology:

Creates and applies composite annotations drawn from multiple reference ontologies to annotate model variables, support semantic disambiguation, and enable model merging.