This volume explores the transformation of Digital Humanities (DH) research by AI and smart data, offering global perspectives on innovative methodologies and practices in cultural heritage, with contributions from Asia, Europe, North America, and South America.
Moving from big data to smart data and into the AI era, DH researchers continue to develop new concepts, methodologies, and practices. Smart data, which provides insights from trusted, contextualised, cognitive, predictive, and consumable data at any scale, will continue to hold significant value in our field with AI providing additional support. Addressing both approach and practice, this volume presents the latest advancements and trends in AI and smart data for cultural heritage in DH. It also makes a valuable contribution to critical theories, methods, and practices for leveraging these technologies in cultural heritage.
This book will be an essential reference for DH researchers, cultural heritage professionals, and AI practitioners working at the intersection of technology and humanities scholarship.
Table of Contents:
PART I: Global creative approaches 1. Open data adoption across the humanities: insights from the Journal of Open Humanities Data 2. Agentic AI for Data Discovery in the Social Sciences and Humanities 3. Managing Cultural Heritage Resources with the Arches Platform: Smart Data for Resource Inventories and Concept-based Thesauri 4. Smart data in collaborative web environments to access architectural and urban spaces images 5. Collections as Data Infrastructures: Perspectives from Germany and Australia 6. Community archives in Thailand and digital technology for cultural heritage 7. Enhancing Buddhist Scripture Research with Imperfect AI Outcomes: A Case Study of the SAT Text Database 8. Consideration of Ethical Design in the Development of Cultural Heritage Initiatives PART II: Innovative practices in China 9. From Dusty Pages to Living Essence: A Study on the Intelligent Development of Documentary Heritage in the Era of AI 10. A Knowledge Enhanced Multi-modal Large Language Model for Chinese Guqin Subtractive Notation Interpretation 11. Automatic Part-of-Speech Tagging of Intangible Cultural Heritage Based on Large Language Models 12. Digital Recreation and Revitalisation: Fine-tuning Diffusion Models for the Intelligent Generation of Chinese Bronze Vessel Images 13. Database construction and knowledge mining of ancient Chinese scientific and technological documents 14. Value Addition Driven Ontology Modeling of Beijing Traditional Villages from the Perspective of Smart Metadata 15. Reconstruction and Enhancement of the Palace Museum’s Collection Data
About the Author :
Xiaoguang Wang is Dean and Professor in School of Information Management at Wuhan University, China. He is also the Director of Intelligent Computing Laboratory for Cultural Heritage and Centre for Digital Humanities at Wuhan University. His research interests are digital asset management, knowledge organisation, semantic publishing, and digital humanities.
Marcia Lei Zeng is Professor of Information Science at Kent State University (USA), with a PhD from the University of Pittsburgh (USA). Her research interests include knowledge organisation systems, metadata, semantic technologies, and digital humanities. She has authored six books and over 100 research papers.
Jin Gao is Co-Director of UCL Centre for Digital Humanities (UCLDH), Lecturer in Digital Archives in the Department of Information Studies at UCL and Research Fellow at the V&A Museum. Her research interests focus on the Digital Humanities history, network analysis, digitisation, provenance studies, and data standards.
Ke Zhao is a PhD researcher at Wuhan University, China. She holds a PhD in Information Resource Management from Wuhan University, an MSc in Digital Humanities from UCL, a BFA and a BEng from China and South Korea. Her research interests focus on digital storytelling, digital humanities, and human-computer interaction.
