The document discusses the challenges of preparing rich GML data for the deegree platform, emphasizing the complexities of managing large datasets and multiple transformation steps. It proposes using a Spatial ETL (Extract, Transform, Load) process involving various tools such as ogr2ogr and Python to streamline data conversion. Additionally, it highlights case examples such as Dutch addresses and the integration of national GML datasets into the deegree environment.