The paper aims at investigating modelling strategies in HBIM context to identify at what extent the final use of the model might affects, or should affect, the modelling approach itself. Moreover, the discussion wants to shed light on the possibility of connecting in just one digital environment several instances connected to the building. These aims will be discussed presenting and evaluating two different modelling approaches: the “black box” modelling and the “white box” model-ling. The two terms are partially borrowed from computer science to explain two types of testing. The “black box” testing is performed without any preliminary knowledge about the system functionality and internal components; on the contrary, the “white box” testing, implies a full knowledge of the system. These two approaches will be compared to two ways of conceiving a building information model. In conclusion, the paper will investigate the possibility to integrate in just one model, the grey box model, the two ones previously discussed.

BIM represents a significant step towards digitalization and innovation in the public construction sector in Italy, and as of 1 January 2025, its adoption became mandatory for all public work. Recognizing the importance of this shift, the Sapienza University of Rome developed a set of standards and guidelines between 2018 and 2024. These guidelines have now been officially adopted by the Buildings Maintenance Area of Sapienza for the application of BIM in service and work contracts. They are consolidated into a document known as the Sapienza Protocol, which serves as a reference for the creation of information-rich models of university heritage buildings, encompassing both existing structures and those to be constructed from scratch. The Sapienza Protocol outlines a modeling process that integrates surveying, geometric modeling, and an informational framework, combining theoretical principles with methodological approaches tested in the HBIM research domain. This approach ensures that both the technical and historical characteristics of buildings are appropriately represented. The purpose of this manuscript is to describe the evolution of the Sapienza Protocol, from its initial version to its current form. It highlights operational procedures and technical solutions, showcasing how the protocol has adapted to address the complex needs of managing and preserving architectural heritage in a digital context.

In the Middle Ages a chain suspended between two towers defended the entrance of Kyrenia’s little harbour, like the chain across the Golden Horn in Constantinople. William de Oldenburg, who visited Cyprus in 1211 during the reign of King Hugh I, referred to Kyrenia as “a small town well-fortified, which has a castle with walls and towers”. He perceived the chain tower as part of Kyrenia’s fortification system in that time. The Byzantines had already fortified the city, but in the thirteenth century, during the Longobard war, before the siege of the city, Frederick II’s party, under the direction of Captain Philippo Genardo, improved the defences of the city. The chain tower is still visible today in the north side of the old Kyrenia harbour. It consists of an 8,15 m diameter cylindrical tower and a 1,5 m diameter pillar on top of it. The tower was supporting a chain attached on the other side to another structure. The fortifications on the north side terminated against the harbour in a square tower or bastion holding the chain to be raised and lowered by means of a windlass. The paper includes the digital photogrammetric survey of the chain tower using a structure from motion software, the historical research and the comparison with other coeval harbour defence constructions of the eastern Mediterranean.

This paper presents a semantic classification workflow applied to the UNESCO World Heritage site of Aachen Cathedral, integrating 3D survey data and Machine Learning (ML) techniques. The research focuses on the Westwerk area and combines Terrestrial Laser Scanning (TLS) and photogrammetric point clouds for material and construction technique identification. A hybrid approach was adopted: 3D geometry-based classification using supervised algorithms (Random Forest) and 2D image segmentation via META’s Segment Anything Model (SAM). The 3D method proved suitable for distinguishing features with strong morphological differentiation, while the 2D approach was more effective for visually subtle or geometrically similar elements. Annotated 2D masks were projected onto the 3D model to improve classification reliability.The study demonstrates the potential of integrating spatial and radiometric data for scalable, semi-automatic classification of historic masonry. Results contribute to the development of enriched, semantically annotated 3D datasets supporting documentation, conservation planning, and future research on complex heritage sites.

The knowledge and study of built heritage is now deeply connected to methodologies associated with the capture of surface details via the production of point-data. These methodologies enable researchers to gather a wider range of information, which is increasingly more connected to technological advances. Such approaches influence the management of data, and these data are often redundant due to the ways in which they are captured. Massive data capture does not include preliminary selection based on metric, geometric, and material features of the object. A multi-scalar approach, in which the criteria for data capture depends on the goals of the survey, is needed to optimize the relationship between information and the scale of the models to be built. This case study involving a selection of fountains in Rome aims to apply these principles to urban contexts defined by a strong spatial connection between architectural and sculptural elements. Survey can express this distinctiveness through complex, dynamic, and effective digital models.