Plant phenotyping studies or studies that monitor of animal or human behavior often rely on the collection and analysis of high-dimensional and (spatio-) temporal datasets. In this research project, probabilistic programming approaches will be developed that allow to incorporate prior knowledge on the study objects (e.g., shape or behavior) into the data analysis pipeline to make the analysis more robust.