Table 1 How Ontologies Enable the Simulation Model Development Process (Benjamin et al. 2006)

Establish purpose & scope

Capture needs, questions, objectives. Integrate across multiple perspectives. Map organization /mission goals to simulation goals.

Terminology harmonization to enable shared and clear understanding.

Formulate conceptual model

Validate system descriptions. Identify model boundaries. Identify the level of modeling abstraction. Identify model objects and roles. Determine model structure and logic.

Ontology knowledge is used to determine the unambiguously differentiated abstraction levels. The ontological analysis helps to map system objects to model objects and to identify appropriate object roles. The ontological analysis helps reason with system constraints to facilitate determination of model logic.

Acquire and analyze data

Identify data sources and data dictionaries. Perform data and text mining. Perform statistical analyses, data reduction (distribution fitting, etc.).

Ontologies play an important role in detailed data analysis, especially in disambiguating terminology and interpreting text data descriptions.

Design detailed model

Refine, detail, and validate model objects. Refine, detail, and validate model structure and model logic.

Ontologies will facilitate detailed analysis of objects and constraints including mapping the simulation model constraints to evidence/ specifications of real-world constraints in the domain descriptions.