# An Ontology-Based Representation of Valued System for HBIM
## 5 HBIM and Ontology Data Integration: Case Study  
This section presents the integration of different data types by using the ontology-based approach described in Section 4. In particular, here it is summarized the case of the abacus of the HBIM vaulted system in the Magio Palace, Cremona (Italy). The survey of Magio Palace combined different technologies. In particular, the geometric survey is carried out to integrate both laser scanning and photogrammetry. Laser scanning data were acquired at the intrados while photogrammetry was mainly used to acquire the extrados to get the 3D model and orthophoto of the brickwork arrangement, if visible. On the other hand, a material survey was performed at the intrados with infrared thermography (IRT) for the indirect detection of material and the texture arrangement. In particular, three different vaults are addressed in this study:  
* Manfredini Hall One, facing the road,
* Manfredini Hall Two, facing the court of the palace,
* The Stair Hall. These three vaults belong to the same \"cloister vault\" category at first sight. However, the construction technologies influence the simplified conceptual shape coming from the vault typology classification (barrel vault, cloister vault, sail vault, dome), generating typologies turned toward mixed typologies [49]. In the case of the Magio Palace the survey integration evidenced the different arrangements and components of the three different vault typology: (i) the Manfredini Hall, tuned to trompe (Figure 4--top); (ii) the Manfredini Hall Two, with the typical rectangular slices coming from the intersection of two conceptual cylindrical solids (Figure 4--center); (iii) the stair hall, a dome turned to a cloister (Figure 4--bottom) [50]. Starting form acquired data the modelling of the vaults was carried out to generate the vault HBIM object. The Non Uniform Rational Basis-Splines (NURBS) originated through the generative modeling and were parametrized [51]. Specific properties were added according to the classes identified in the vault ontology (Figure 5). Figure 3: A partial view of the survey ontology. Figure 4: The surveying Magio Palace vaults. Three different vaults apparently belonging to the cloister typology: the orthoimages (intrados), the extrados arrangements coming from the orthoimages at the extrados or intrados-infrared thermography (IRT) (details), and the different horizontal profiles from the point clouds. The Manfredini Hall One is covered by trompe vault (**top**), the Manfredini Hall Two by cloister vault (**center**) and the stair hall by the dome to cloister vault (**bottom**). Figure 5: The HBIM reconstruction of the Manfredini Hall One vault: (**a**) the properties (i.e., typology, sub-typology, arrangement, geometry, description, etc.) and (**b**) the 3D element. Starting from the previously defined HBIM model, the steps to create a knowledge base of vaulted systems are summarized in Figure 6:  
1. HBIM model: HBIM or historical building information model is created by designers using a BIM platform (e.g., Autodesk Revit) with added information which defines the class of the defined ontology. 2. HBIM ontology: HBIM ontology presented in this article provides the vocabulary for converting BIM data to RDF/OWL format before it can be saved in a vault knowledge base. 3. RDF/OWL Converter: the converter module in this paper uses the database generated in the BIM platform (e.g., Autodesk Revit) and the ontology editor FlientEditor 2015 (c). 4. RDF/OWL ontological database: the converted ontological database is saved in RDF/OWL format allowing the possibility to query it with a SPARQL endpoint interface that allows local and remote access to its data over the internet. 5. Reasoner: connection with a reasoner adds logical interface to the knowledge base. An ontology-based database is defined as a \"database model that enables the ontology and the data to be stored in a common and single model\" [52].