Nuclear data represents measured (or evaluated) probabilities of various physical interactions involving the nuclei of atoms. It is used to understand the nature of such interactions by providing the fundamental input to many models and simulations in nuclear physics and related subjects. Backing up simple nuclear models with real data provides a springboard for a more detailed understanding of the complexities of nuclear structure.

This book provides an intermediate treatment on the topic of nuclear structure focussing on an independent-particle motion view. It follows Nuclear Data: A Primer, which provided an introduction to nuclear structure. The book is divided into four main chapters which outline the necessary theory and critically review it in the light of available data. Structured exercises promote student learning and understanding.

This book follows a pathway that is useful to potential readers, particularly PhD students and advanced undergraduate students. Rather than starting with complex computational models, a data-driven approach is pursued to use the large resources of nuclear data available to understand whether it supports different aspects of collective motion in nuclei. This provides a more intuitive understanding and allows the student to explore their own investigations through guided exercises.