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摘要
The visualization of multifactor time series data and abnormal data is of great significance in improving the decision-making efficiency and other problems. Since different types of data have different characteristics, traditional visualization methods will face the challenges of complex graphics and low user observation efficiency when drawing such data. Therefore, an efficient visualization method MDataEE for exploring multifactor time series data and abnormal data is proposed. Firstly, the view of multiple kinds of data is simplified by visual mapping. Secondly, the rendering of coordinate axes is optimized according to the density and importance of data and visual perception. Finally, we added some interactive operations, such as displaying and hiding graphics and generating contrast views, so that users could explore different aspects of data freely according to their needs. The real-world PM2.5 data set is used for the experimental tests in this paper. The results show that the proposed method can generate a concise visual view, which has advantages in analyzing the trend and causes of abnormal data, and can improve the efficiency in understanding and analyzing abnormal multifactor time series data. ? 2022 Institute of Computing Technology.
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