An Application of Semantic Techniques to the Analysis of Enterprise Architecture Models

Abstract

Enterprise architecture (EA) model analysis can be defined as the application of property assessment criteria to EA models. Ontologies can be used to represent conceptual models, allowing the application of computational inference to derive logical conclusions from the facts present in the models. As the actual common EA modelling languages are conceptual, advantage can be taken of representing such conceptual models using ontologies. Several techniques for this purpose are widely available as part of the semantic web standards and frameworks. This paper explores the use of the aforementioned techniques in the analysis of enterprise architecture models. Namely, two techniques are used to this end: computational inference and the use of SPARQL. The aim is to demonstrate the possibilities brought by the use of these techniques in EA model analysis.

Automating threat modeling using an ontology framework

“…Semantic techniques serve as a tool for analyzing enterprise architecture models, where ontologies represent the conceptual models and derive logical conclusions about the models. In Antunes et al (2016), such an analysis was performed using both SPARQL and computational inference, and the approach was claimed to have facilitated analysis using syntactic and semantic information from the models. The semantics and structure of data can cause organization-wide heterogeneity problems, as described in Song et al (2013).…”