Open Graph Benchmark: Datasets for Machine Learning on Graphs

Understand

We present the Open Graph Benchmark (OGB), a diverse set of challenging and realistic benchmark datasets to facilitate scalable, robust, and reproducible graph machine learning (ML) research.

• OGB datasets are large-scale, encompass multiple important graph ML tasks, and cover a diverse range of domains, ranging from social and information networks to biological networks, molecular graphs, source code ASTs, and knowledge graphs.
• For each dataset, we provide a unified evaluation protocol using meaningful application-specific data splits and evaluation metrics.
• In addition to building the datasets, we also perform extensive benchmark experiments for each dataset.