Cardiovascular disease (CVD) is a major cause of death and hospitalization in New Zealand, and there is evidence that some population groups are at greater risk than others, even after analyses adjust for clinical (e.g., high blood pressure, diabetes, cholesterol, smoking) and socio-demographic risk factors. The increasing availability of complex health and social databases are providing researchers with new opportunities to better understand the determinants of CVD health and its outcomes. Users of such large databases have the challenge of extracting knowledge from, and making sense of, complex socio-spatial patterns of disease. This paper introduces a new web mapping approach to visualize rich and multidimensional CVD data for the Auckland region in New Zealand, by incorporating innovative ringmaps into web mapping. Our results demonstrate that embedding ringmaps into interactive web maps provides a powerful way to reveal multivariate patterns and construct knowledge from large CVD datasets.