Computational Archives of Population Dynamics and Migration Networks as a Gateway to Get Deep Insights into Hard-to-reach Populations: Research on Taiwan Indigenous Peoples

This paper highlights research on constructing big computational archives of hard-to-reach populations (HRPs), using Taiwan Indigenous Peoples (TIPs) as an example. The research uses archives of (1) anonymous individual-level migration flows computed from population dynamics data and (2) Taiwan indigenous community data (TICD) to illustrate characteristics of HRPs which were unknown before. The research suggests that computational HRP networks (e.g., migration networks) help overcome barriers to accessing HRPs and promote mutual understanding. The archives of Taiwan Indigenous Peoples Open Research Data (TIPD) are a research data source, with archives of address geocoding, population dynamics, and indigenous communities being most relevant to TIPs network systems. The migration flows are computed at the individual level and have unveiled various dimensions of HRP networks that were invisible before. The newly computed TICD archives enable us to trace migration flows of TIPs within and between indigenous communities and urban localities at the individual level in the context of ethnic lineages. The research findings suggest that strengthening intra- and inter-ethnic network connections serves as an effective measure to get deep insights into HRPs.