Guidelines for the Management of Cultural Heritage using 3D models for the insertion of heterogeneous data - PhDData

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Guidelines for the Management of Cultural Heritage using 3D models for the insertion of heterogeneous data

The thesis was published by Bertacchi, Gianna <1990>, in March 2022, Universita di Bologna.

Abstract:

The Management of Cultural Heritage (MCH) is a very complex operation aimed at protecting the physical integrity of CH assets, while promoting their historical value and development of tourism industry. In recent years, the use of digital technologies has become an essential part of the MCH delicate process, but the use of 3D models is still limited to few academic research to date. Furthermore, very few supra-national standard guidelines regulating their use are available to date and the operator who decides to use a 3D model as a basis for management is faced with the scarcity and fragmentation of standards and guidelines.
The aim of the PhD research is to develop guidelines to produce 3D models for MCH, with the purpose to efficiently entry, store and manage digital data. The here provided guidelines investigate every aspect of the process leading from data acquisition to cataloguing and archiving, processing and creation of a simplified information system for the management. In order to elaborate guidelines that could be suitable for as many typologies of CH as possible an international approach was chosen, developing the thesis in joint supervision under the University of Bologna and the Universitat Politècnica de València, and by applying the state-of-the-art technologies of acquisition, processing and use of 3D models to a variety of case studies.
The investigation, by highlighting the problems inherent to the MCH, made it possible to identify the main open issues that need to be explored in future lines of research, such as the application of standards to a large number of cultural assets; the automatic classification of raw data; the processing of collected data for the creation of relations, strategies and methods for the classification, integration and optimisation of heterogeneous data.



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