Progressive time series visualization in a mobile environment

Beside their original functions, mobile devices are now enabled with increasing computational power and wireless communication technology that can facilitate many different applications. One valuable application is about the mobile access of financial data and a major task involved is to provide the historical stock price movement so that the market players can make appropriate investment decisions. However, due to the limitations of this new environment (e.g. screen size, bandwidth for data exchange, storage and computational power), adaptation is needed for time series visualization. In this paper, a progressive time series visualization method, with additional compression ability, for the mobile environment is proposed. The proposed method is based on a perceptually important point (PIP) identification scheme so that the time series data points can be disseminated in the order of importance for the changing (data access) requirements. The application of the proposed method to stock price time series visualization in mobile devices is demonstrated.