# A Digitally Enhanced Ethnography for Craft Action and Process Understanding
## 1 Introduction
### Contributions of This Work  
This study contributes to the field of ethnography and CH documentation by bridging traditional ethnographic methods with advanced digital tools. By enhancing how craft practices are observed, recorded, and analyzed, our approach supports both the preservation of Intangible Cultural Heritage (ICH) and the development of innovative research methodologies.  
One of the key contributions of this work is the preservation of craft knowledge. The study provides a structured approach to documenting artisanal techniques, ensuring that they are recorded, studied, and made accessible. Although the use of moving images in ethnographic practices is well established, this research integrates multimodal data such as MoCap, 3D scanning, and a novel use of video recordings to create a richer and more immersive representations of craft traditions.  
Additionally, another contribution of this research is the interdisciplinary collaboration enabled by bringing together ethnographers, digital humanists, engineers, and craft practitioners. Through this shared knowledge framework, experts from different domains can contribute to the study and preservation of craft techniques. The study also incorporates Life Course Theory (LCT) to examine how artisans develop their expertise over time, linking technical knowledge to personal narratives and career trajectories.  
Further to the abovementioned contribution, the enhancement of ethnographic methods should also be highlighted. This research extends traditional ethnography by integrating structured workflows, digital tools, and expert-driven annotation, making ethnographic studies more systematic and reproducible. It provides a methodological foundation for future research, demonstrating how digital tools can complement and enhance traditional fieldwork.  
On a technical level, the study introduces a digitally enhanced ethnographic framework that combines MoCap, 3D scanning, audiovisual recording, and semantic knowledge representation. It refines the traditional ethnographic approach by distinguishing between endurant entities, such as tools and materials, and perdurant entities, such as gestures and transformations, offering a hierarchical and systematic classification of craft knowledge.  
The study also advances multimodal data collection and analysis by integrating both marker-based and markerless MoCap technologies to precisely track craft gestures. This enables the more detailed examination of the biomechanics of artisanal movements. Additionally, the use of video elicitation techniques allows practitioners to reflect on their movements, providing valuable insights into the cognitive and experiential aspects of craft practice.  
To ensure the structured representation of craft knowledge, this research develops an ontology-based framework that facilitates searchability, retrieval, and reusability across different disciplines, including digital humanities, artificial intelligence, and education. This approach allows craft knowledge to be not only recorded but also systematically structured for computational analysis and future research applications.  
The methodology proposed in this study was tested across eight European craft traditions, demonstrating its adaptability and scalability across different materials, tools, and cultural contexts. By applying this comparative perspective, the study highlights shared techniques and material behaviors across various craft domains.  
By integrating ethnographic research with cutting-edge digital methodologies, this work contributes both to the documentation of ICH and the advancement of interdisciplinary research methodologies. The framework developed in this study provides a scalable and reproducible approach for future ethnographic research, ensuring that craft knowledge remains a living and evolving resource.