Despite its centrality to Chinese culture and wide adoption in Chinese communities, Traditional Chinese Medicine (TCM) has rarely been the application domain of computational analysis in previous academic works. Here we present the first systematic adoption of the state-of-the-art Semantic Web technologies in the codification, management, and utilization of TCM information and knowledge resources. These technologies are proved effective in bridging the semantic gaps between a plurality of legacy and heterogeneous relational databases, enabling ontology-based query and search across database boundaries. A global herb-drug interaction network is constructed and represented in SemanticWeb language, on which the semantic graph mining methodology is applied for discovering and interpreting interesting patterns. This deployed Semantic Web platform provides various innovative information retrieval and knowledge discovery services to the TCM domain experts with positive feedbacks. This project demonstrates Semantic Web’s advantages in connecting data across domain and community boundaries to facilitate interdisciplinary and cross-cultural studies.