As digital humanities research relies on the digitization of sources, many of its applications are based on access to data on a huge scale that makes quantitative analyses and distant reading (or a birds-eye view) possible. Based on this assumption, we show how the genre of Chinese local gazetteers, with its volume, consistent structures, and broad geographic and temporal range, provides an ideal case to benefit from the digital approach. This paper introduces the Local Gazetteers Research Tools (LoGaRT), a suite of research tools designed for studying Chinese local gazetteers based on the philosophy that any comprehensive genre, such as Chinese local gazetteers, when accompanied with tools that aim to bring a collective lens to the genre, can greatly enrich the ways that scholars approach it and can transform the genre into a research infrastructure that enables new types of research. We report on how LoGaRT opens up new perspectives for researching Chinese history by showing case studies and the scholarly breakthroughs made by our research group. With this paper we hope to provide one possible answer to the question of how digital methods can contribute to humanities research. Even though LoGaRT is developed for a specific Chinese genre, we argue that the proposed research methodology and the corresponding user workflow and tools developed in our software can be applied to other genres or collections of sources when certain criteria are met.

In this paper, we introduce a web GIS platform created expressly for exploring and researching a set of 63,467 historical maps and illustrations extracted from 4,000 titles of Chinese local gazetteers. We layer these images with a published, geo-referenced collection of Land Survey Maps of China (1903–1948), which includes the earliest large-scale maps of major cities and regions in China that are produced with modern cartographic techniques. By bringing together historical illustrations depicting spatial configurations of localities and the earliest modern cartographic maps, researchers of Chinese history can study the different spatial epistemologies represented in both collections. We report our workflow for creating this web GIS platform, starting from identifying and extracting visual materials from local gazetteers, tagging them with keywords and categories to facilitate content search, to georeferencing them based on their source locations. We also experimented with neural networks to train a tagger with positive results. Finally, we display them in the web GIS platform with two modes, Images in Map (IIM) and Maps in Map (MIM), and with content- and location-based filtering. These features together enable researchers easy and quick exploration and comparison of these two large sets of geospatial and visual materials of China.