Lei Hui1), Chen Haidong2), Xu Jiayi2), Wu Xiangyang3), and Chen Wei2)*
1)(Department of Electronics and Information Engineering, Changsha University of Science and Technology, Changsha 410004) 2)(State Key Laboratory of CAD & CG, Zhejiang University, Hangzhou 310058) 3)(College of Computer Science, Hangzhou Dianzi University, Hangzhou 310018)
It is inevitable to bring about uncertainty during the process of data acquisition, derivation, and visualization. Different from data error and data conflict, uncertainty resides in and propagates along each stage of the visualization pipeline. Uncertainty is an important ingredient of data. Visualizing uncertainty can help the analysts gain insight into the data to make better decisions. In this paper, first we introduce the main sources of uncertainty; then we summarize the state-of-the-art uncertainty visualization approaches into four categories: glyph, visual variable encoding, geometry, and animation; at last we outline some directions requiring further studies.