Biomedical ontologies and controlled terminologies provide structured domain knowledge to a variety of health information systems. The rich thesaurus with concepts linked by semantic relationships has been widely used in natural language processing, data mining, machine learning, semantic annotation, and automated reasoning. The dramatically increasing amount of health-related data poses unprecedented opportunities for mining previously unknown knowledge with semantics-powered data analytics methods. However, due to the heterogeneity of different data sources, it is a challenging problem to leverage multiple sources to solve real-world problems, such as designing cost-effective treatment plan for patients, designing generalizable clinical trials, drug repurposing, and clinical phenotyping. The goal of this workshop is to bring people in the field of knowledge representation, knowledge management, and health data analytics to discuss innovative semantic methods, applications, and data analytics to address problems in healthcare, biomedicine, public health, and clinical research with biomedical, clinical, behavioral, and social web data.