Healthy soils are a cornerstone of agricultural production and multiple other ecosystem services. To ensure the long-term productivity of this vital resource, it is fundamental to assess the soil health status, track changes over time, and consequently guide sustainable management practices. This is commonly achieved by measuring soil health indicators.In practice, the definition of soil health indicator reference values remains challenging for two reasons: a) indicator reference values depend on pedoclimatic conditions at the investigated location, which severely complicates unbiased soil health evaluations and b) many soil health indicators are known to vary partly strongly, depending on where in a field site and at which season the soil health indicator has been sampled. By combining experimental approaches, statistical analyses of existing databases and numerical soil-crop modelling, SHAING! will provide improved and new transfer functions for frequently used site-specific soil health indicators as well as novel insight into amplitude and scale of the spatio-temporal fluctuations of some of these indicators.