Temporal queries are normally issued for cohort selection from the high-dimensional dataset in many contexts, such as medical related research areas. The idea was inspired by the difficulties when interacting with the i2b2 system, an NIH-funded National Center for Biomedical Computing based at Partners HealthCare System, which seldom provides informative feedbacks and interactive exploration about the clinical events of each query or the expecting follow-up cohort. Considering the complexity and time-consuming nature of complicated temporal queries, it would be frustrating when iterative query refining is needed. The paper presents a newly designed web-based visual query system to facilitate refining the initial temporal query to select a satisfactory cohort for a given research. A detailed interface design associated with the query time frame and the implementation of the visual query algorithm that enables advanced arbitrary temporal query logic is included. In addition, a case study with 3 participants in medical related research areas was conducted that shows the system was overall useful to help the users to gain an idea about their follow-up queries.Master of Science in Information Scienc
