Experimental Magnetocaloric Properties of Perovskite Oxides: A Curated Dataset for Machine Learning Applications

This dataset presents a curated collection of experimental magnetocaloric properties of perovskite oxides compiled from peer-reviewed literature. The dataset is designed to support data-driven materials discovery and machine learning applications in magnetic refrigeration research. It includes structured tabular data on magnetocaloric performance metrics such as magnetic entropy change, magnetic phase transition characteristics, applied magnetic field conditions, and compositional information. Where available, additional structural parameters and synthesis-related details are included to enhance predictive modeling capability. All values are experimentally reported measurements extracted directly from published sources.