Data-driven approaches such as machine learning and multimedia technology can accelerate research on Japanese culture from a historical perspective. Furthermore, thanks to a widespread movement toward open science, such as open data and open source, research on Japanese culture has finally entered into a big data era. However, humanities data is full of interpretation and meaning, has a complex structure with diversity, and requires implicit knowledge not explicitly described inside the humanities data. Hence we do not expect that a technological silver bullet, such as AI, can solve all the problems at once. Instead, we employ a connect-the-dot approach by developing and connecting tools and datasets to answer humanities research questions for understanding Japanese culture. For that purpose, we carefully gather evidence from many sources in the past, create structured data with human-machine collaborations, and integrate them as linked data to draw a bigger picture of Japanese culture looking backward from the present. The talk will introduce our activities in the ROIS-DS Center for Open Data (CODH) in the Humanities to tackle these challenges as digital humanities and historical big data research. The talk will include machine learning for the recognition of Kuzushiji (Japanese historical cursive scripts), art history research using IIIF (International Image Interoperability Framework), and computer vision-based differential reading for diachronic transcription. We also discuss the importance of domain knowledge and collaboration with domain experts to ask meaningful research questions beyond simplistic metric-based evaluations.