Abstract: In the context of the development of new quality productive forces, accelerating the digital transformation of communities to enhance community resilience has become the core orientation and fundamental demand of grassroots community governance. Based on the perspective of the whole life cycle of data, the hybrid method of Structural Equation Model (SEM) and BP Neural Network was used to empirically analyze the resilience changes of different types of communities under the influence of data elements, and reveal the mechanism and effect of data-empowered community resilience. The research results are as follows: data production, data integration and data application have different impacts on the physical, social, institutional and cultural resilience of communities, respectively. The community refined consultation governance model promotes data integration and sharing, breaks down departmental barriers and the phenomenon of "digital suspension", and improves the physical and social resilience of communities. Under the basic national conditions of China's population aging, the phenomenon of "silver digital divide" reduces the overall data utilization level of communities, resulting in a decrease in the institution resilience of communities. The dual blessing of community refined consultation governance and the development of community digital technology has made up for the shortcomings of the aging community population, and the overall level of community resilience has been improved.

Key words: Data elements, Data empowerment, Community resilience, Full life cycle, Urban governance