## 4 Results
### Data Processing  
#### 4.2.1 Building Footprint Extraction from Historical Maps  
The initial step is to georeference historical plans and to extract building footprints. This step is currently in testing for one historical map of Jena via testing two different approaches--the Deep Learning module of ArcGIS Pro and Segment Anything. For the first proof of concept, a historical map of Jena in 1936 was provided by the Thuringian State Library (Figure 5). To verify the building footprint extraction with a contemporary map, the historical map was georeferenced by determining multiple control points visible in both maps. \begin{table}
\begin{tabular}{p{142.3 pt} p{142.3 pt} p{142.3 pt}} \hline
**Tell Us What It Was Like: Oral History Project** & **Objects Tell Stories, We Listen** & **Culture of Remembrance Rethoutib: Digitization of Stolpersteine** \\ \hline
**Topic**: Young people critically examine the oral history method, research topics in modern history, conduct contemporary witness interviews, and prepare them using digital tools. & **Topic**: Children select historical everyday objects such as old kitchen utensils or tools; examine their function and history; and describe, draw, and digitize them using photography and 3D scans. & **Topic**: Pupils research the life stories of Holocaust victims commemorated by Stolpersteine (“stumbling stones”), create short biographies, and present them on the web. \\
**Objectives**: Understand the construct nature of historical narratives and be able to research independently using digital resources and critically reflect on the information obtained. & **Objectives**: Acquire a basic understanding of source-oriented historical learning and get to know and reflect on the first methods of digitization. & **Objectives**: Learn about regional remembrance culture in a creative way and acquire skills in digital source research and text presentation on the web. \\
**Realization**: Project week in a youth center, 5 days, participants aged 13–18 & **Realization**: Afternoon work group in the DH Lab, six sessions, participants aged 7–10 & **Realization**: Afternoon working group in the DH Lab, six sessions, participants aged 11 \\
**Results**: Contemporary witness interviews; POIs in the 4D City application; results of application; self-evaluation; results of qualitative surveys of teachers and learnersers & **Results**: Drawings, photos, 3D scans; POIs in the 4D City application; results of qualitative surveys of teachers and learnersers; self-evaluation & **Results**: Texts, images; POIs in the 4D City application; results of qualitative surveys of teachers and learnersers & **Results**: Texts, images; POIs in the 4D City application; results of qualitative surveys of teachers and learnersers & City application; results of qualitative surveys of teachers and learnersers & **Results**: Texts, images; POIs in the 4D City application; results of qualitative surveys of teachers and learnersers & **Results**: Texts, images; POIs in the 4D City application; results of qualitative surveys of teachers and learnersers & City application; results of qualitative surveys of teachers and learnersers & **Results**: Texts, images; POIs in the 4D City application  
Automatic segmentation of historical maps is considered a difficult challenge due to vast changes in appearance between maps of different epochs [164,288]. While one approach may be successful for the 1936 map, it may easily fail for another map. For the Jena map, two different strategies were investigated. The first approach involves using the Detect Objects Using Deep Learning module of ArcGIS Pro. This requires users to manually vectorize several building footprints in the historical map and use them as training data [80]. In our research, reasonable results could only be obtained after labelling approximately 50% of the complete map. Still, the post-processing tool Regularize Building Footprints had to be used to create proper edges. In the second approach, Segment Anything [289] was applied to the historical map.