An Infrastructure and Application of Computational Archival Science to Enrich and Integrate Big Digital Archival Data: Using Taiwan Indigenous Peoples Open Research Data (TIPD) as Example

Abstract

This paper highlights research on constructing a big archival data called Taiwan Indigenous Peoples Open Research Data (TIPD, see https://osf.io/e4rvz/) based on contemporary census and household registration data sets in 2013-2017 (see http://TIPD.sinica.edu.tw). TIPD utilizes record linkage, geocoding, and high-performance in-memory computing technology to construct various dimensions of Taiwan Indigenous Peoples (TIPs) demographics and developments. Embedded in collecting, cleaning, cleansing, processing, exploring, and enriching individual digital records are archival computational science and data science. TIPD consists of three categories of archival open data: (1) categorical data, (2) household structure and characteristics data, and (3) population dynamics data, including cross-sectional time-series categorical data, longitudinally linked population dynamics data, life tables, household statistics, micro genealogy data, marriage practice and ethnic identity data, internal migration data, geocoded data, etc. TIPD big archival data not only help unveil contemporary TIPs demographics and various developments, but also help overcome research barriers and unleash creativity for TIPs studies.