Until the middle of the last century, the primary paradigms in mainstream science had been either experimental science or theoretical science. Starting in the 1950s, computational science began its rise to equal prominence and this change resulted in the realization of complex, largescale numerical calculations and simulations. Now, scientifi c research is continuing to evolve with further innovative changes brought by the advent of the Internet and related technologies. Thanks to the technology used in these sophisticated information systems, most of the hardware and sensors used to gather information are linked to these networks. Information distributed in digital form technically allows anybody to access it anytime and from anyplace. The empirical scientific research method based on complex large-scale data collected through these networks is called “Data-centric science.” The “Knowledge Circulation” infrastructure, which creates new value by projecting concrete information from our society into cyber space, analyzing and simulating it on the web, and enabling feedback from the web to real people and objects, will be one of the major pillars of future socio-informatics. In this paper, we describe the trends in methodology of datacentric science developed in various academic disciplines, and the possibility of these types of developments in socio-informatics. Further, we discuss the data sharing/ collaborative research infrastructure that may result in breakthroughs in socio-informatics achieved through sharing vast amounts of data collected from throughout society and utilizing information science.