Digital Innovation in Cultural Heritage: Trends in Italy and China
Politecnico di Milano · Xi’an Jiaotong University
Organizers’ contacts:
Prof. Giorgio Colombo — Full Professor of Drawing and Methods of Industrial Engineering
Department of Mechanics, Politecnico di Milano
Prof. Yingtao Qi — Associate Professor
Department of Architecture, School of Human Settlements and Civil Engineering, Xi’an Jiaotong University
Prof. Barbara Galli — Associate Professor of History of Architecture
Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano
Abstract
This special session explores digital innovation in cultural heritage through a comparative and cross-cultural perspective, with particular attention to current trends and research practices in Italy and China. The session focuses on data as a core component of cultural heritage knowledge, encompassing both tangible and intangible assets and supporting conservation, management, and long-term maintenance processes.
Data are conceived not as static repositories, but as dynamic and evolving systems capable of integrating heterogeneous information derived from surveys, diagnostics, historical sources, monitoring activities, and operational interventions. This approach promotes a process-oriented form of knowledge, adaptable to the changing conditions of heritage assets.
The session discusses advanced knowledge models, including ontology-based systems and knowledge graphs, combined with artificial intelligence tools to manage complexity, uncertainty, and incomplete data. Particular attention is devoted to the role of Extended Reality (XR) technologies as environments for visualization, simulation, and critical exploration of heritage assets and intervention scenarios.
Through engagement with international experiences—especially Italy–China research and educational collaborations—the session aims to reflect critically on how digital innovation can support adaptive, reversible, and context-sensitive approaches to cultural heritage knowledge and conservation.
Motivation
The increasing complexity of cultural heritage and conservation practices requires tools capable of managing heterogeneous, dynamic, and often incomplete data while maintaining interpretability and operational value. This session addresses the need to move beyond rigid data models toward flexible, integrated, and process-oriented approaches supported by emerging technologies.
Target Audience
Cultural heritage scholars and professionals, PhD candidates, archaeologists, architects, conservators, museum curators, digital humanists, data scientists, IT specialists, and experts in representation and simulation of the built environment.
Keywords
- Cultural Heritage Data
- Knowledge Models
- Artificial Intelligence
- Extended Reality (XR)
- Adaptive Conservation and Maintenance
- Representation and Simulation of the Built Environment