Suggested by: Franz Welscher, Johannes Scholz
Keywords: Semantic Knowledge Graphs, GeoQA, Geospatial Data Integration, Raster and Vector Data, Spatial Querying
Objective: Develop an approach for integrating raster and vector geospatial data into a semantic knowledge graph, enabling structured and efficient querying through a GeoQA (Geospatial Question Answering) engine. The research will explore data modeling, indexing, and retrieval strategies to enhance geospatial decision-making in disaster and conflict management scenarios.
Short Description: This thesis investigates the integration of heterogeneous geospatial data—raster (e.g., satellite imagery, elevation models) and vector (e.g., administrative boundaries, infrastructure networks)—into a semantic knowledge graph to support advanced geospatial querying via a GeoQA engine. The study will develop and test a framework that enhances spatial reasoning, enabling users to retrieve and analyze geospatial information more effectively. A potential use case includes the PeaceEye initiative, focusing on disaster and conflict management applications.
Start:
As soon as possible
Prerequisites/qualification:
Knowledge in GIS and spatial data processing
Interest/Knowledge in Knowledge Graphs
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