  Data Spaces are an emerging concept for the trusted implementation of
data-based applications and business models, offering a high degree of
flexibility and sovereignty to all stakeholders. As Data Spaces are currently
emerging in different domains such as mobility, health or food, semantic
interfaces need to be identified and implemented to ensure the technical
interoperability of these Data Spaces. This paper consolidates data models from
13 different domains and analyzes the ontological dissonance of these domains.
Using a network graph, central data models and ontology attributes are
identified, while the semantic heterogeneity of these domains is described
qualitatively. The research outlook describes how these results help to connect
different Data Spaces across domains.
