Exploring Database Quality Through Shapley Values: Application to Dynamic Soil Parameters Databases

Geotechnical engineering faces challenges related to data, especially the ones related to dynamic soil behavior (i.e., shear modulus reduction and damping ratio curves with strain), with only a few datasets in open-access format and a slow transition to a more data-driven method. This lack of data, combined with variations in data collection methods, makes it difficult to build accurate predictive models. These challenges arose while developing a model to predict the shear modulus curves, an important soil property to better understand seismic hazard from three different databases. Combining multiple databases can sometimes degrade model performance. To address this, a novel approach in geotechnics based on Shapley values computed from an XGBoostRegressor model is introduced. This game–theoretic method quantifies each database’s marginal contribution to the model’s R2 across all possible combinations, making it possible to identify which databases contribute most to improving performance. As the number of available databases continues to grow, this method will become increasingly useful. For shear modulus reduction curves, two out of three databases explored have Shapley values of 0.341 and 0.339, while the last one reaches only a value of 0.320. This suggests that the first two databases contribute more to the model’s performance.