Empirical Academic Platform: Building an Intelligent Infrastructure for Empirical Research in China

Abstract

Current empirical research faces structural difficulties, and data silos exist in many fields. Also, researchers spend much time on repetitive labor in low level, and scientific resources are wasted because of this. These issues can limit the efficiency of academic innovation and they make achievement transformation difficult in current system. We propose to build an empirical academic platform which has the core function of data integration and automatic standardization of empirical results, with dynamic update, and we use big data and artificial intelligence, plus econometric modeling so that the entire process of empirical research can be automated. Then we describe the theoretical framework, core architecture, technological path, and application scenarios of this platform, and we design a Chinese pilot program which is government led, with university co-construction, and enterprises also participate. We also analyze the challenges and response strategies that the platform faces. It is worth noting that research suggests empirical academic platforms can promote the return of empirical research from method driven to problem driven. They can reshape academic research paradigms. Also, technical support can be provided for the construction of Chinese philosophy and social science system and it has significant theoretical value and practical significance.