OSCAR: a framework to integrate spatial computing ability and data aggregation for emergency management of public health

Abstract

Spatial computing has emerged a critical issue in emergency management of public health. Due to the complexity of spatial data structure and disperse character of spatio-temporal data, when emergency event of public health occurs, it is difficult to get the needed data and analysis it then make quick decision in a short time. In this paper, OSCAR: an Open Spatial Computing and data Resource platform were introduced including its components, framework, elements and two implementations. OSCAR provides a data resource aggregation platform to retrieve data from official statistic agencies through data service and database, scrawl related data from BBS and social media and mirror the environment data from earth observation data sites. All the dataset are arranged in data cubes according to their spatial and temporal dimensions. This mechanism ensures the feasibility and timeliness of time-sequence analysis of specific regions. The algorithms of spatial computing of public health are usually complicated and depend on particular computing environment, which is usually not default configuration of computer of nowadays. OSCAR deploys a series of computation images in a cloud-computing environment. The computation ability can be extended on-demand and thus the time of the computation can be shortened and limited in several minutes when it is needed. The two implementation of human rabies of China and H7N9 in China show the convenience of our platform.