Coxiella burnetii is an important zoonotic bacterial pathogen of global importance, causing the disease Q fever in a wide range of animal hosts. Ruminant livestock, in particular sheep and goats, are considered the main reservoir of human infection. Vaccination is a key control measure, and two commercial vaccines based on formalin-inactivated C. burnetii bacterins are currently available for use in livestock and humans. However, their deployment is limited due to significant reactogenicity in individuals previously sensitized to C. burnetii antigens. Furthermore, these vaccines interfere with available serodiagnostic tests which are also based on C. burnetii bacterin antigens. Defined subunit antigen vaccines offer significant advantages, as they can be engineered to reduce reactogenicity and co-designed with serodiagnostic tests to allow discrimination between vaccinated and infected individuals. This study aimed to investigate the diversity of antibody responses to C. burnetii vaccination and/or infection in cattle, goats, humans, and sheep through genome-wide linear epitope mapping to identify candidate vaccine and diagnostic antigens within the predicted bacterial proteome. Using high-density peptide microarrays, we analyzed the seroreactivity in 156 serum samples from vaccinated and infected individuals to peptides derived from 2,092 open-reading frames in the C. burnetii genome. We found significant diversity in the antibody responses within and between species and across different types of C. burnetii exposure. Through the implementation of three different vaccine candidate selection methods, we identified 493 candidate protein antigens for protein subunit vaccine design or serodiagnostic evaluation, of which 65 have been previously described. This is the first study to investigate multi-species seroreactivity against the entire C. burnetii proteome presented as overlapping linear peptides and provides the basis for the selection of antigen targets for next-generation Q fever vaccines and diagnostic tests.