Springtime project aims to facilitate deriving meaningful insights and making most of the available data by providing interpretable models for spatiotemporal phenology research. For this purpose, the project will first streamline analytical workflows and allow to fetch, clean, and prepare datasets from various sources, formulate tasks, clarify performance measures and procedures, standardize flows, execute and track rungs, automate benchmarks, and develop visualizations. Then interpretable models will be developed for mixed effects that are useful for clustered data by using explainable boosting machines approach.