Human genetic diversity has been shaped by demographic events and exposure to diverse environments. Genetic diversity should be analyzed considering different temporal and spatial scales since all can be relevant for biomedical research. Despite the great progress achieved with initiatives such as the human Pangenome and large biobanks that aim for a better representation of human diversity, important challenges remain. We should focus on diversifying methodologies, sampling locations of the datasets, as well as genetic and non-genetic characteristics of the participants such as ancestries, socioeconomic status, gender, and living environments among others. This will allow us to understand the genetic architectures and etiologies of complex traits and diseases in different contexts, identifying region-specific variants and effects, as well as gene-by-environment interactions. Overcoming existing bias in genetic and biomedical research can aid global accessibility to preventive and personalized medicine. In this talk, I will walk us through the creation of and inferences made to-date from the Mexican Biobank with respect to (dynamic) genetic structure and its impact on complex trait and disease variation. I will close by providing a new framework and interactive web browser to consider and visualize relationships and genetic similarity amongst cohorts sampled across the world, this in the interest of helping move human genetics towards relational thinking and past typological frameworks.