Digital art history in 2021

Abstract

The past decade has seen tremendous growth and innovation in the use of digital resources, methods, and tools in the history of art and architecture. While digital art history is less developed than text‐based disciplines, the emergence of new digital standards for visual and spatial data, and advances in computer vision are poised to revolutionize the field. This article provides a survey of recent developments in digital art history from the perspective of European and North American publications and conferences. I discuss the digitization of visual, spatial, and textual resources by museums, research centers, and individual researchers. Researchers have developed a variety of tools for digitally analyzing art and architecture, which can replicate or challenge traditional methods of formal, iconographic, and socio‐historical analysis. Trends in published research indicate uneven growth in the theoretical sophistication of digital art history scholarship. While digital methods are quickly moving into the training of art history professionals and students, digital art history communities in museums, research institutes, and universities remain somewhat fragmented. I conclude with a reflection on critiques of digital art history, several of which have not been fully addressed in recent scholarship.

Photogrammetry Enables the Critical Reinterpretation and Regeneration of Architectural Heritage

“…(Drucker 2013). Although digital art history is not as advanced as disciplines focused on textual analysis, the introduction of innovative, digital standards for visual and spatial data, along with advancements in computer vision, have the potential to bring about a transformative shift in the field (Brey, 2021). Photogrammetry is one such representative application in architectural research.…”

“…1-3). The photogrammetric survey of historical heritage has also become increasingly popular because it overcomes the weaknesses of the traditional highresolution topographic survey, namely the high cost of data acquisition and the fact that specialised third parties dominate (Brey, 2021). Instead, the photogrammetric technique of structure-frommotion (SFM) for creating high-resolution digital elevation models from extensive photo series taken with a consumer camera, offers a low-cost, userfriendly approach for researchers to collect data themselves (Westoby, 2012, p. 300).…”