Commercial Archaeology and 3D Web Technologies

Abstract

ABSTRACTThis contribution summarizes the multiple uses of 3D web technologies in commercial archaeology. Considering the breadth of this topic, we will describe each different branch of these technologies with the example of case studies based on work of the Italian company Arc-Team. Our overview begins with 3D visualization for scientific purposes, showing a project funded by the Autonomous Province of South Tyrol (Italy) in order to improve knowledge about WWI. Second, we analyze a similar project, funded by the Autonomous Province of Trentino (Italy), but with the aim to increase tourism at a high alpine WWI site. The third example is the development of another prototype for tourism: a 3D web-map for the cultural valorization of the historical border (1753) between the region Tyrol and the Most Serene Republic of Venice. In the forth case study, we discuss the implementation of 3D within web platforms for archaeological project management of RAPTOR (Ricerca Archivi e Pratiche per la Tutela Operativa Regionale), a webGIS developed to aid in preservation and conservation efforts of cultural heritage for the Italian Ministry of Cultural Heritage and Activities and Tourism (MiBACT). Fifth, we explore recent uses of 3D models for web-coworking during the process of excavation management, thanks to the developments of real-time 3D acquisition techniques based on SLAM algorithms and archeorobotic devices. Finally, 3D web-coworking is also analyzed illustrating some simple web tools that afford rapid feedback in data visualization, considering not only excavation field-work but also exploration projects. This overview, based on six different case studies, represents the four fields in which 3D web technologies are currently used in commercial archaeology: scientific communication; tourism improvement; preservation of cultural heritage; and real time field-work management. Some specific topics such as tourism improvement and field-work management are investigated in greater depth in order to allow us to analyze variables deriving from customer requests (e.g. restrictions regarding sensitive geolocation or preferences for specific web platforms) and from differences among data acquisition technologies based on various sensors.