## 4 Results
### Data Processing
#### 4.2.5 Data Enrichment with Textual Information  
To further enrich 3D models with text and image data, turning them into an interlinked dataset, we used labels or annotations [304]. Taken together, the annotations enable a time/space related to browsing source material, but can also support numeric analysis, eliminate bias, and ensure reproducibility [305].  
In the digital humanities, the Getty Art & Architecture Thesaurus (AAT) is well established and provides a hierarchy for architectural elements [306]. Furthermore, Wikidata  
Figure 14: Neural rendering of the Semperoper using exclusively historical photographs and NeuS Facto.  
Figure 15: An SfM reconstruction of the center of Budapest exclusively using historical photographs. Each red pyramid represents one photograph and its orientation and camera parameters.  
offers a variety of entities, classes, and corresponding semantic relations for art and architectural elements and is also used in cultural heritage [307]. Relevant terms were identified via text analyses of Zwinger literature and Baroque architecture, building history and building research [305]. Finally, a list of about 400 entries (including 140 architectural elements) was compiled, containing both AAT and Wikidata IDs. So far, several Wikipedia articles, scientific publications, and popular scholarly articles have been annotated. In the texts, words or word groups from the compiled term list and terms with a high semantic similarity were annotated (Figure 16) [308].  
In our case study, a detailed 3D model of the Kronentor (Crown Gate) from Dresden Zwinger was manually annotated in a modelling environment for testing purposes. In this model, most of the architectural elements are separate objects that carry the corresponding AAT or Wikidata ID in addition to the element name. Some objects are grouped and form a unit in the sense of a hierarchy of elements.  
As described in the previous section, 4000 photographs of Dresden have been spatialized in the 4D browser application, either manually or using a semi-automatic approach. Images were also manually segmented and annotated using Label Studio ([[https://labelstud.io/](https://labelstud.io/)]([https://labelstud.io/](https://labelstud.io/)) (accessed on 12 December 2023)), an application for labelling and annotating data which provides a standardized output format. Each annotation follows the scheme used for the 3D models and contains both AAT and Wikidata IDs (Figure 17). Automatic transfer of annotations from the 3D model to the located photographs is conceivable, but previous approaches have not yet achieved the desired level of reliability and accuracy.  
Figure 16: Example of an annotated Wikipedia article within the 4D browser application.  
Figure 17: Segmented and annotated image of the Kronentor (Crown Gate) of the Dresden Zwinger.  
The 4D browser displays annotations as a word cloud, indicating how often a term is mentioned in a text document, but also connects images, texts, and 3D information (Figure 18). The annotations are clickable in the text or image and the word cloud; clicking takes the user to linked external information like the AAT and Wikidata entries and features like searching for connected or similar annotations in other images, 3D models, and text passages within the platform.