Before revision:  Our empirical investigation reveals the challenges of existing graph methods in handling large-scale graphs and predicting out-of-distribution data.
After revision:  In addition to building the datasets, we also perform extensive benchmark experiments for each dataset. Our experiments suggest that OGB datasets present significant challenges of scalability to large-scale graphs and predicting out-of-distribution data.