Abstract
Work towards creation of a knowledge sharing system for sustainability science through the application of semantic data modeling is described. An ontology grounded in description logics was developed based on the ISO 15926 data model to describe three types of sustainability science conceptualizations: situational knowledge, analytic methods, and scenario frameworks. Semantic statements were then created using this ontology to describe expert knowledge expressed in research proposals and papers related to sustainability science and in scenarios for achieving sustainable societies. Semantic matching based on logic and rule-based inference was used to quantify the conceptual overlap of semantic statements, which shows the semantic similarity of topics studied by different researchers in sustainability science, similarities that might be unknown to the researchers themselves.