Advancing Bio-Realistic Modeling via the Brain Modeling ToolKit and SONATA Data Format One of the major goals of the BRAIN Initiative is to distill complex, multi-modal data into predictive frameworks via theory/modeling. As the planning document "BRAIN 2025: A Scientific Vision" urges, “theory and modeling should be woven into successive stages of ongoing experiments, enabling bridges to be built from single cells to connectivity, population dynamics, and behavior.” However, data-driven, bio-realistic modeling is not widely practiced, in part because the field needs software supporting such complex modeling and standards for model sharing and reproducibility. The Allen Institute has developed two powerful tools addressing these needs. One is the Brain Modeling ToolKit (BMTK) – a software suite for model building and simulation at multiple levels of resolution, from networks of biophysically detailed neuronal models, to point-neuron networks, to population-statistics approaches. The other one is the SONATA (Scalable Open Network Architecture TemplAte) data format, which provides computationally efficient solutions for storing and exchanging data describing all stages of the modeling workflow (e.g., structure of model networks, configuration of simulations, simulation outputs). These tools were developed in coordination with many initiatives, such as NEURON, NEST, Neurodata Without Borders, NeuroML, PyNN, NetPyNE, and the Human Brain Project. As a result, BMTK and SONATA enable many applications and have generated substantial interest, with many users already employing these tools. Most recently, BMTK and SONATA were instrumental in integrating diverse data from the Allen Institute and from the literature into some of the most sophisticated and bio-realistic models of a brain region to date. We propose to build a comprehensive user support and dissemination platform for BMTK and SONATA and help integrate these tools into model building and simulation practices in the