Capturing and Leveraging Computational and Experimental Data in Materials Physics

In order to use artificial intelligence and machine learning for scientific advances, access to complex, multimodal, and accurate data is critical. In this talk, we will discuss efforts in generating, capturing, and leveraging computational and experimental data, with examples in generation of computational defect properties datasets, capturing microscopy data, and combining streams of computational and experimental data. We will also discuss concerted efforts at US Department of Energy Scientific User Facilities in data infrastructure.