RGZ EMU: Semantic Taxonomy (Radio Galaxy Zoo EMU: Towards a Semantic Radio Galaxy Morphology Taxonomy)

The data used in - "Radio Galaxy Zoo EMU: Towards a Semantic Radio Galaxy Morphology Taxonomy" (Bowles et al. submitted) - "A New Task: Deriving Semantic Class Targets for the Physical Sciences" (Bowles et al. 2022: https://arxiv.org/abs/2210.14760) accepted at the Fifth Workshop on Machine Learning and the Physical Sciences, Neural Information Processing Systems 2022.

This data consists of images of galaxies, and plain English annotations of the features of the radio galaxies, as well as expert classifications using pre-existing scientific classes.

Additionally the data presented contains checkpoints of the data at various stages throughout the processing initially completed with https://github.com/mb010/Text2Tag.