Big data is transforming terrestrial ecosystem science by enabling new approaches to model evaluation, development and prediction. Several examples are provided where large datasets on atmospheric measurements, remote sensing, and flux towers are integrated with models. This allows processes to be better understood from data analysis and provides opportunities to improve models. However, tools are still needed to easily facilitate comparison and assimilation of diverse data with models. The eMAST initiative aims to develop infrastructure for predictive ecosystem models that are fully informed by all relevant data.