Benchmarking
Starting to work with georeferenced data can be a challenge. This page brings together tools and case studies, so that a new project can be compared with approaches that are already established.
Tools
Explore
GeoLAB Data Explorer
A map of twenty adult indicators calculated from SOEP-Core v41, including well-being, health, education and employment. The regional aggregates were reviewed for export by the SOEP Research Data Center on 22 October 2026.
Coverage varies by indicator, year and region. Unavailable or suppressed estimates remain missing. Historical observations use provider-recoded 2023 county geography and NUTS 2024 membership. The display includes confidence intervals; microdata and bulk downloads are not provided. This independent GeoLAB application replaces the link to the predecessor visualizer, which remains unchanged.
Analyse
Software toolbox
Four open-source R packages from the RegioHub, each solving one recurring step in regional analysis.
inkr: all of INKAR in a local DuckDB database, so the indicators can be queried offline instead of being downloaded from the portal one by one.nutscoder: geocoding to NUTS region codes, which is the join key most spatial linkages need.badata: regional labour-market data from the Bundesagentur für Arbeit.deairdata: a wrapper around the air-quality API of the Umweltbundesamt.
Further guidance
For guidelines, descriptions of geocoding and a discussion of the advantages and disadvantages of geodata, see Why Geodata?. Among other things, that page discusses
- changing administrative boundaries and the territorial reforms that break a time series,
- the assumption that everyone inside a boundary is exposed to the same context,
- the choice between distance-based, radius-based and grid-based measures,
- and what a residential coordinate cannot tell you.
Case studies
Case studies are in preparation and will be collected here.