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Abstract Compared with the collaborative innovation evaluation in provinceslevel, results of dynamic evaluation across cities can more easily show the characteristics of regional development, and visual analysis highlightswill display regional differences more effectively.Based on three dimensions: collaborative innovation foundation, collaborative innovation cooperation and collaborative innovation output, this paper constructs the dynamic assessmentand visual analysis model of collaborative innovation evaluation in urban areas, and conducts overall and subevaluation analysis from static and dynamic perspectives.The results show that there is significant difference in the level of collaborative innovation in the cities of Jiangsu province, existing the phenomenon of "high in the south and low in the north, polarization".Nanjing benefited from its political, economic and educational resources, having the highest level of collaborative innovation; Suzhou, the highest level cityin southern Jiangsu, which is deeply influenced ineconomic environment, and the ShanghaiNanjing radiation promotes its collaborative innovation; Xuzhou overtakessome cities in southern Jiangsu because of the inseparable location advantages and educational resources.This paper applies time factors into dynamic evaluation methods, and multi visualization patterns is used to present final results, which will greatlyimprove the speed and efficiency of differentiation.
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