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Web Services APIs

SkenData offers two APIs:

  1. Geodata-based: Provides accurate energy metrics based on real-world geospatial data.
  2. Statistical Model-based: Uses average statistical models to estimate energy metrics for buildings without geospatial data.

Both APIs cater to different needs, offering flexible and precise calculations.

The image illustrates two different approaches offered by our APIs for estimating building energy performance:

Geodata vs. Approximation

Left: Building-Prefill-API

The left side is based on actual geodata of a real-world building.

  • Aerial view with the building's outline highlighted.
  • Energy metrics such as building area, energy efficiency class, CO₂ equivalent, and primary energy demand are based on real data.
  • This API provides highly accurate results because it relies on verified, real-world data.

Right: Approximation API

The right side illustrates an approximation using a statistically average building.

  • The depicted building does not exist in reality—it is a symbolic model within a generated map section.
  • Energy metrics are provided, but based on typified, average values.
  • This API can offer increasingly accurate results with more detailed building descriptions (e.g., year of construction, building type, roof shape).

This comparison clearly shows that the Real Data API provides more precise results, while the Approximation API offers a flexible alternative when real building data is unavailable—and it can be refined with additional inputs.