Advanced aggregate computation for large data visualization

Large data visualization and analysis faces challenges related to performance, operability, degree of discrimination, etc. In this paper, an advanced aggregate computation is proposed to solve these issues from three aspects. By virtue of visualization-based data separation and aggregation, a large dataset is mapped to a visualization-based small dataset for efficient visualization while keeping operability of data. A minimum size of visual primitives for aggregated data is defined to ensure visibility of important but tiny information. And a D3-based rendering implementation improves the performance of consecutive visualizations.