Research on Time-series Visualization Methods for Scientific and Technical Consulting Graph Data

The existing open-source knowledge visualization components do not support knowledge graph temporal visualization exploration capabilities and cannot meet the demand of analyzing the dynamic evolutionary changes of industries in science and technology consulting scenarios. In this paper, to address the above problems, we propose a knowledge graph-based temporal visualization component construction and optimization method to build a graph visualization component that supports temporal dynamic exploration based on existing open-source knowledge visualization components to address the demand for industry insight analysis in science and technology consulting graph analysis services. At the same time, a data processing and graph rendering optimization strategy is proposed to improve the overall task execution efficiency in response to the problems of low rendering efficiency and high computational resource occupation rate in the time-series visualization exploration scenario.