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Workshop: Data Quality Improvement

Open In Colab

This interactive workshop demonstrates the complete workflow for improving OpenStreetMap power plant data quality using the osm-powerplants package.

What You'll Learn

  1. Extract power plant data from OpenStreetMap
  2. Analyze why certain plants fail validation (rejection tracking)
  3. Export issues as GeoJSON for fixing in JOSM
  4. Visualize data on interactive maps
  5. Verify improvements after OSM edits

Prerequisites

  • Basic Python knowledge
  • Google account (for Colab) or local Python environment
  • Optional: JOSM for editing OSM data

Running the Workshop

Click the "Open in Colab" badge above to run the workshop in your browser. No installation required!

Option 2: Local Environment

pip install osm-powerplants folium jupyter
jupyter notebook notebooks/workshop_data_quality.ipynb

Workshop Sections

1. Setup

Install the package and import required modules.

2. Extract Power Plant Data

Fetch data for a small country (Malta) to demonstrate the extraction process.

3. Rejection Analysis

The key feature! Learn why OSM elements fail validation:

  • Missing source type → Add plant:source tag
  • Missing technology type → Add plant:method tag
  • Missing output tag → Add plant:output:electricity tag
  • And more...

4. Export for JOSM

Generate GeoJSON files that can be loaded into JOSM as a hint layer for fixing issues.

5. Interactive Maps

Visualize both rejected elements and valid plants on interactive Folium maps.

6. Verification

Re-run the extraction after making OSM edits to measure improvements.

The Feedback Loop

osm-powerplants → Identify Issues → Fix in JOSM → Upload to OSM → Verify Improvements
       ↑                                                                    │
       └────────────────────────────────────────────────────────────────────┘

This workflow enables continuous improvement of OSM power plant data, which ultimately improves energy system models built with powerplantmatching and PyPSA-Eur.