The design of a big data-driven information management system for engineering seismic research centers under cloud-native architecture

To address challenges such as data silos, resource rigidity, and high operational costs in earthquake engineering research, this study designs and implements a big data-driven information management system for engineering seismic research centers based on cloud-native architecture. The system employs an elastic cloud platform and multi-level storage for its hardware infrastructure, along with a microservices-based and frontend-backend separated software architecture. Technologies such as Vue.js, PHP, MySQL, and Spark are integrated to achieve core functions including full lifecycle equipment management, visual data analysis, and intelligent scheduling. Practical application demonstrates that the system effectively integrates multi-source heterogeneous data, improving the efficiency of research resource utilization and collaborative innovation capabilities, offering a feasible pathway for transforming seismic research from "experience-driven" to "data-driven".