First, thank for all the works you have done to democratize Geometric Deep Learning!
In 2022, I have generated a dataset of 1000 RANS simulations of airflow around airfoils in a subsonic flight regime. This led to a publication in the Datasets and Benchmarks Track of NeurIPS 2022 (AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier–Stokes Solutions | OpenReview).
As it is a point cloud based dataset, I proposed to include it in PyTorch Geometric in 2023, which has been done since (torch_geometric.datasets.AirfRANS — pytorch_geometric documentation). Now, I wanted to know if it would be possible to make it available directly in DGL too?