Geospatial Ontology

Geospatial ontologies are structured representations of geographic knowledge, aiming to improve data interoperability and semantic understanding in diverse applications. Current research focuses on developing robust ontologies for various domains, including indoor/outdoor scenes, geological formations (like faults), and complex networks like food supply chains, often leveraging large language models and transformer-based neural networks for automated ontology construction and improved toponym resolution. These advancements facilitate better data integration, analysis, and knowledge discovery across different geospatial datasets and applications, ultimately enhancing the accuracy and efficiency of geographic information systems and related fields.