Imaging of stroke and neurovascular disorders has profoundly enhanced clinical practice and related research during the past 40 years since the introduction of computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography enabled mapping of the brain. Various imaging techniques have been developed to study stroke pathophysiology and inform medical decision-making in prevention, prehospital care, acute monitoring of revascularization, during the subacute ICU course, and recovery settings. The technology to acquire such imaging with sophisticated scanners, software for rapid postprocessing, analysis, computer vision methods, and telemedicine platforms to instantly beam such information around the world now warrant reconsideration of the potential of stroke imaging in the era of big data. These dramatic changes in neuroimaging and the vast potential to catapult stroke care depend on large-scale, multi-institutional research initiatives to establish their role. These initiatives would require that the current infrastructure and philosophy of translational research must be modernized to incorporate such advances. In this position paper, we describe the historical context, conceptual framework, current issues, logical analyses for strategic planning, and the proposed aims of future stroke imaging initiatives to advance data science with the recently established National Institutes of Health (NIH) StrokeNet.1 The StrokeNet consists of 25 regional stroke center hubs, each associated with a group of spoke hospitals that are capable of conducting stroke research. The network will be responsible for conducting future multicenter NIH stroke trials and represents an ideal setting to capture large volumes of invaluable neuroimaging data. Our perspective contrasts with the limited translational research use of imaging in most previous stroke trials, recognizing a unique opportunity to maximize data science and leverage this landmark NIH investment to transform stroke trials of prevention, acute treatment, and recovery. The tools already exist for widespread acquisition and transmission of image data, systematic real-time …