The explosively growing big biomedical data provides enormous opportunities to revolutionize the current clinical practices as well as the biomedical research if the accompanied challenges of heterogeneity in knowledge discovery on biomedical big data can be addressed with novel informatics technologies. Our team has been working on developing semantic technologies to normalize, integrate, query, and analyze the massive volumes of biomedical data as well as to infer new knowledge based on what is known. The core technologies we are developing are based on ontologies and the Semantic Web. Here we share our vision on applying semantic web techniques to clinical knowledge and data representation, as well as to retrieve useful information and knowledge from EHR or online resources. In particular, we will introduce our efforts on (1) representing and normalizing large-scale EHR data in semantic web notations to enable automatic consistency checking and semantic reasoning; (2) temporal information modeling, extraction, and reasoning for patient medical history and time trending analysis; and (3) using semantic queries for patient education.