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Soft ontologies aim to provide more flexible knowledge representations as compared with hierarchy-based ontology models. Soft ontologies can restructure itself according to the necessities of an interaction context. This is especially desirable in systems that need to deal with dynamic domains and situations with a high degree of uncertainty. However, the definition of soft ontologies is a challenging task due to the lack of generic and well defined components. In addition, such definition may suffer from problems with interoperability and integration with other models. We argue that soft ontologies should coexist with other models in an interoperable framework. In this paper, we propose and formalize a metamodel to provide adequate conciliation among various ontology representation approaches. We develop soft ontologies based on matrices of probabilities and apply a triplification process in which concepts are represented as fuzzy RDF statements. Our proposal was evaluated in a case study in an educational context, which uses a soft ontology to express a repertoire of actions in an mBot robot. The results indicate the feasibility of our fuzzy RDF approach to represent soft ontologies and the use of the metamodel to support interoperability in heterogeneous ontology networks.