Hibernation is one of the most striking survival strategies in animals, a state in which metabolism drops to levels that would ordinarily threaten viability while tissues remain unexpectedly stable. Although the research to date has described many relevant molecular and physiological features of significance, most studies have examined these layers in isolation, which has limited our ability to understand how the process unfolds across time and across biological scales. In this review, we trace the historical trajectory of hibernation research and examine hibernation across complementary omics dimensions, introducing Hibernomics as a research framework that studies the phenomenon of hibernation through the dynamic integration of multi-omic technologies and approaches. This perspective allows hibernation to be viewed not as a collection of independent traits but as a coordinated and highly structured adaptation, shaped by its temporal rhythm. When examined through this lens, three interlinked core research threads emerge: energy metabolism, focusing on hypothermic metabolic reprogramming from genome to metabolites; neuroendocrine-immune regulation, centered on integrating environmental cues, endocrine signaling and immune remodeling to coordinate systemic physiological transitions; and cold tolerance, concentrating on the preservation of tissue integrity and functional resilience during prolonged hypothermia and rewarming. These themes appear across species even though individual mechanisms vary, which suggests that evolution has assembled different workable solutions to the same physiological challenge. Important gaps remain, including the difficulty of harmonizing heterogeneous datasets, incomplete grasp of the neural events that initiate hibernation, the technical obstacles in terms of resolution, dynamics, and different species, the wide translational gap from animal models to human application, and certain enduring enigmas of basic physiology and evolution. Advances in high-resolution technologies such as single-cell and spatial omics coupled with strategies for dynamic sampling and monitoring, are beginning to address these challenges, which are further being empowered by novel experimental platforms such as organoids and organs-on-chips, targeted perturbation tools, and computational methods capable of inferring or proving causal relationships. Together, these developments position Hibernomics to move from descriptive synthesis towards a predictive, mechanism-oriented framework, one that may eventually guide innovations in organ preservation, metabolic medicine, trauma care and the management of long-duration spaceflight towards transformative applications.