Statistical and machine learning techniques are essential for contemporary microbiome studies. The increasing availability of spatial, longitudinal, and multi-omic profiling data is opening up new research opportunities as well as challenges for computational methodology. This talk will cover contemporary topics in microbiome data science and associated open science frameworks, with a particular focus on modeling spatial and temporal change in large-scale population cohort studies.