Omkar2118/datasets huggingface dataset:
The Well: 15TB of Physics Simulations

Large-scale collection of machine learning datasets containing numerical simulations of a wide variety of spatiotemporal physical systems. The Well draws from domain scientists and numerical software developers to provide 15TB of data across 16 datasets covering diverse domains such as biological systems, fluid dynamics, acoustic scattering, as well as magneto-hydrodynamic simulations of extra-galactic fluids or supernova explosions. These datasets can be used individually or as part of a broader benchmark suite for accelerating research in machine learning and computational sciences.
MAVEN-Arg
Full name: MAVEN-Arguments

MAVEN-Arg is an advanced event argument extraction dataset, which offers three main advantages:

*  A comprehensive schema covering 162 event types and 612 argument roles, all with expert-written definitions and examples.
*  A large data scale, containing 98,591 events and 290,613 arguments obtained with laborious human annotation.
*  The exhaustive annotation supporting all task variants of EAE, which annotates both entity and non-entity event arguments at the document level.

Introducing paper: MAVEN-Arg: Completing the Puzzle of All-in-One Event Understanding Dataset with Event Argument Annotation