Speaker
Description
Abstract
Ever-accelerating technologies, such as 3D scanning and AI open up new approaches to research history while challenging the development and narratives of visual representations. Correlating novel digital innovations and art history resulted in ‘digital art history’ as a collaboration between art history, digital humanities, and computer science (A. Bentkowska-Kafel et al. 2005; K. Brown 2020). Similar formulations remain largely absent in the historical debate surrounding architecture. Nevertheless, authors like Kemp (2006) and Carpo (2011; 2013) alluded to transhistorical connections between past technological advancements and the digital turn, yet scholarship did not propose an investigative framework for architecture as digital art history did. Hence, this paper explores how interdisciplinary digital approaches to architectural history help reconsider visual narratives while changing our engagement, perception and analysis of past architecture. To materialise such positions, the paper relies on Panofsky’s famed Iconography & Iconology (1939), as a principle to assess architectural form and meaning, via 3D scans and AI-generated images as illustrative cases. Such a conjoint reading allows for defining digital iconography in architecture as a response to ‘digital art history.’ Iconography’s oscillation between form and context revalidates its position in contemporary architectural debates and grounds well-established methods of architectural history in the digital realm. Thus, this paper questions and scrutinises the relationship between architectural history and digital technology by combining art historical methods of iconography with digital applications and computer science. The proposal of digital iconography posits a theoretical exploration to provide a framework and knowledgebase to explore interdisciplinarity in architectural history, mediating future possibilities for investigating form and meaning in the field.
Keywords
Architectural History; Digital Art History; Iconology; Interdisciplinarity; Generative AI