Building an OSM to RDF Pipeline for AI Agents: A Practical Guide

This project showcases the development and application of an OSM (OpenStreetMap) data extraction tool tailored for specific use cases, such as maritime features and construction sites. The key steps involved in building this tool include:

1. Command-line Interface (CLI): A Python script (osm-extract) was created to process command-line arguments, allowing users to specify the area of interest via bounding box coordinates or a file containing multiple areas.

2. Configuration Files: YAML files define filters and tags for specific categories like maritime features or construction sites. This allows users to customize what data is extracted based on their needs.

3. Filter Building: The tool dynamically constructs filter strings used by osmfilter, an OSM processing utility, based on the configuration provided in the YAML file.

4. Tag Control: Users can specify which tags should be included in the output files, reducing noise and focusing on relevant data for their use case.

5. Idempotency and Safety: Features like idempotent execution (re-running does not change results), directory handling, dry-run mode, and overwrite control ensure that the tool is safe to run repeatedly without unintended side effects.

6. RDF Conversion: The extracted OSM

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