Visualization is commonly used in the interpretation of physical behavior (PB) data, either in conjunction with or as precursor to formal analysis. Effective representations of the data can enable the identification of patterns of behavior, and how they relate to the temporal context in a single day, or across multiple days. An understanding of behavior patterns is essential to inform appropriate intervention strategies. Current visualizations of PB data are designed primarily to identify periods of activity, such as, standing, walking, running, etc. These representations generally work well, as the events are often relatively short and rarely cross the boundary of the calendar day. Sedentary events, however, are generally longer, and the major sedentary events of lying often cross over day boundaries. This article assesses current visualization approaches, with a shift in focus to identifying patterns of sedentary behavior. The article argues for the need to use visualization techniques which do not place artificial breaks in the data over day or hour boundaries and proposes potential solutions which may facilitate improved analysis of sedentary behavior data.