TRANSRAZ Data Model: Towards a Geosocial Representation of Historical Cities

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Date
2023
Volume
56
Issue
Journal
Series Titel
Studies on the Semantic Web ; 56
Book Title
Knowledge Graphs: Semantics, Machine Learning, and Languages
Publisher
Berlin : AKA
Link to publishers version
Abstract

Preserving historical city architectures and making them (publicly) available has emerged as an important field of the cultural heritage and digital humanities research domain. In this context, the TRANSRAZ project is creating an interactive 3D environment of the historical city of Nuremberg which spans over different periods of time. Next to the exploration of the city’s historical architecture, TRANSRAZ is also integrating information about its inhabitants, organizations, and important events, which are extracted from historical documents semi-automatically. Knowledge Graphs have proven useful and valuable to integrate and enrich these heterogeneous data. However, this task also comes with versatile data modeling challenges. This paper contributes the TRANSRAZ data model, which integrates agents, architectural objects, events, and historical documents into the 3D research environment by means of ontologies. Goal is to explore Nuremberg’s multifaceted past in different time layers in the context of its architectural, social, economical, and cultural developments.

Description
Keywords
cultural heritage, digital humanities, city exploration, knowledge graphs, archival documents, architecture
Citation
Bruns, O., Tietz, T., Göller, S., & Sack, H. (2023). TRANSRAZ Data Model: Towards a Geosocial Representation of Historical Cities (M. Acosta, S. Peroni, S. Vahdati, A.-L. Gentile, T. Pellegrini, & J.-C. Kalo, eds.). Berlin : AKA. https://doi.org//10.3233/SSW230012
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License
CC BY-NC 4.0 Unported