Modern applications increasingly rely on dynamic geospatial data—from vehicles and pedestrians to environmental phenomena. Representing and processing these “moving features” in a scalable and interoperable way is a key challenge for developers building next-generation location-based services.

This workshop introduces OGC API–Moving Features (OGC API–MF), an open standard designed to handle spatiotemporal data in a consistent, developer-friendly manner. Participants will learn how to manage, query, and analyze moving feature data using standardized APIs that support filtering, sorting, and aggregation across space and time.

Going beyond static APIs, we will also explore the next-generation streaming extension of OGC API–MF. Using Apache Kafka and ksqlDB, we demonstrate how to build a real-time pipeline for ingesting, processing, and tracking moving objects—bridging the gap between standard-based data models and event-driven architectures.

This is a hands-on, end-to-end session where you will:

• Understand the core concepts of OGC API–MF and MF-JSON
• Deploy a fully functional API using pygeoapi
• Store and query trajectory data with MobilityDB / PyMEOS
• Validate implementations with test code
• Visualize spatiotemporal data using STINUUM (Cesium-based client)

All components are containerized with Docker, enabling quick setup and reproducible experimentation.

Whether you are building mobility platforms, digital twins, or real-time monitoring systems, this workshop provides practical insights and open-source tools to accelerate development with standardized moving feature data.