ZuantuSet: A Collection of Historical Chinese Visualizations and Illustrations

2025-02-26

AI Summary

Systematic scholarly investigation of premodern Chinese visual materials remains severely underdeveloped. Method: This paper introduces ZuantuSet—the first large-scale dataset of ancient Chinese illustrated texts, comprising over 71,000 visualizations and 108,000 illustrations—constructed via a semi-automated pipeline integrating OCR, layout analysis, multi-scale object detection, and expert verification. It further establishes an interdisciplinary annotation framework grounded in philology, art history, and visualization design. Contribution/Results: The study pioneers the systematic taxonomy of traditional Chinese visualization paradigms—including spatiotemporal nesting and mutual illustration-text interpretation—and identifies their historical, cultural, and intellectual foundations, thereby filling a critical gap in non-Western visualization historiography. ZuantuSet serves as a foundational benchmark for culturally aware visualization generation, historical knowledge graph construction, and cross-disciplinary research at the intersection of digital humanities and information visualization.

Technology Category

• Data Mining & Knowledge Management: Data Visualization & Summarization
• Computer Vision: Visual Reasoning & Symbolic Representations
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning

Application Category

• Web Mining and Content Analysis: Web data visualization
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies

Abstract

Historical visualizations are a valuable resource for studying the history of visualization and inspecting the cultural context where they were created. When investigating historical visualizations, it is essential to consider contributions from different cultural frameworks to gain a comprehensive understanding. While there is extensive research on historical visualizations within the European cultural framework, this work shifts the focus to ancient China, a cultural context that remains underexplored by visualization researchers. To this aim, we propose a semi-automatic pipeline to collect, extract, and label historical Chinese visualizations. Through the pipeline, we curate ZuantuSet, a dataset with over 71K visualizations and 108K illustrations. We analyze distinctive design patterns of historical Chinese visualizations and their potential causes within the context of Chinese history and culture. We illustrate potential usage scenarios for this dataset, summarize the unique challenges and solutions associated with collecting historical Chinese visualizations, and outline future research directions.

Problem

• Focuses on understudied Chinese historical visualizations
• Proposes a pipeline for collecting Chinese visual data
• Analyzes Chinese visualization design patterns and causes

Innovation

• Semi-automatic pipeline collects visualizations
• Dataset curated with 71K visualizations
• Analyzes design patterns in Chinese context