The Open Graph Benchmark (OGB) is a collection of realistic, large-scale, and diverse benchmark datasets for machine learning on graphs.
OGB datasets are automatically downloaded, processed, and split using the OGB Data Loader, which is fully compatible with Pytorch Geometric and DGL. The model performance can be evaluated using the OGB Evaluator in a unified manner.
OGB is a community-driven initiative in active development. We expect the benchmark datasets to evolve. Subscribe to our google group to ask us questions and keep up to date with major changes to the datasets.
OGB provides a diverse set of challenging and realistic benchmark datasets that are of varying sizes and cover a variety graph machine learning tasks, including prediction of node, link, and graph properties.