Data- and model-driven computer simulations are increasingly critical in many application domains. These simulations may track 100s or 1000s of inter-dependent parameters, spanning multiple layers and spatial-temporal frames, affected by complex dynamic processes operating at different resolutions. Because of the size and complexity of the data and the varying spatial and temporal scales at which the key processes operate, experts often lack the means to analyze results of large simulation ensembles, understand relevant processes, and assess the robustness of conclusions driven from the resulting simulations. Moreover, data and models dynamically evolve over time requiring continuous adaptation of simulation ensembles. The simDMS platform aims to address the key challenges underlying the creation and use of large simulation ensembles and enables (a) execution, storage, and indexing of large ensemble simulation data sets and the corresponding models; and (b) search, analysis, and exploration of ensemble simulation data sets to enable ensemble-based decision support.