ATKIS-DLM-KG: a unified knowledge graph framework for integrating and querying fragmented topographic-cartographic data in the German digital landscape model

The Authoritative Topographic-Cartographic Information System (ATKIS) Digital Landscape Model (DLM) forms the core of the German authoritative geospatial infrastructure, providing a standardized, object-oriented vector dataset for the detailed representation of landscape features. As a component of ATKIS, the DLM captures topographic features such as infrastructure, land cover, hydrography, and administrative boundaries with high semantic and geometric precision. These datasets serve as critical references for fundamental tasks, such as cartography, spatial planning, and spatial resource management. However, DLM data are distributed as disconnected Shapefiles segmented by thematic categories (e.g. Settlement, Area, Traffic) and geometry types, resulting in fragmented datasets that hinder integrated, cross-theme analysis. To address this challenge, we propose the ATKIS-DLM-KG framework, which integrates the thematic layers of DLM into a unified, semantically enriched Knowledge Graph (KG), enabling cross-domain relationships and context-aware querying. Experimental results show that by bridging thematic and geometric divides, this framework supports the formulation and efficient evaluation of complex queries that synthesize insights from previously disconnected themes.