This special issue advances reflective and comparative discussion/deliberation in the study of social data governance. By the term “social data governance,” we refer to the design, operation, and promotion of quantified governing mechanisms in which the information of social behaviors is collected, datafied, manipulated, and represented through communication technologies for the purpose of resource allocation and socio-political control, with various implications. Social data governance has existed for a long time and in many forms, ranging from credit bureaus’ scrutiny, evaluation, and labeling of their customers, to Internet-enabled massive data collection and scoring systems, and to automated contact tracing techniques as a centerpiece of dataveillance and infection control amid the COVID-19 pandemic. Nevertheless, the domain of research, comprising scholarly work from a wide range of disciplines like laws, mathematics, and business and with diverse geographical foci, has not yet been comparatively and reflectively articulated. Daunting questions remain as to how could disparate types of Internet and data governance better understand one another, thereby breaking up geographical borders and facilitating mutual collaboration? Is universal “data justice” or a contingency model in data governance that entails relevant contextual considerations pursuable? Adding to the growing field of critical scholarly research on Big Data, the research articles and commentaries in this special theme promote a reflective and comparative conversation on Big Data governance theories, perspectives, and practices with consideration of their plurality, diversity, and cultural richness.