Interoperability in healthcare data remains a challenge, especially when exploring complex relationships within data modeled as Fast Healthcare Interoperability Resources (FHIR). While FHIR standardizes data exchange, traditional visualization methods often fail to capture its semantic richness. This paper introduces \emph{FHIR Lens}, an interactive graph-based platform that enhances FHIR exploration through RDF. It leverages SPARQL for dynamic query execution and employs recursive graph expansion to traverse structured healthcare data, addressing challenges like blank nodes and inconsistent references. By visualizing FHIR resources as interconnected nodes and edges, FHIR Lens supports advanced data analysis, relationship discovery, and decision support, contributing to semantic interoperability in healthcare by bridging data standards with graph-based modeling. We describe the platform's functionality and underlying algorithms and evaluate its performance on increasingly large FHIR datasets.