Big data from small animals: integrating multi-level environmental data in the Dog Aging Project

Environmental exposures can have large impacts on health outcomes. While many resources have been dedicated to understanding how humans are influenced by the environment, few efforts have been made to study the role of built and natural environment features on animal health. The Dog Aging Project (DAP) is a longitudinal community science study of aging in companion dogs. Using a combination of owner-reported surveys and secondary sources linked through geocoded coordinates, DAP has captured home, yard, and neighbourhood variables for over 40,000 dogs. The DAP environmental dataset spans four domains: 1) Physical and built environment; 2) Chemical environment and exposures; 3) Diet and exercise; and 4) Social environment and interactions. Together with biometric data, measures of cognitive function and behaviour, and medical records, DAP is attempting to use a big data approach to transform our understanding of how the world around us affects the health of companion dogs. Here, we describe the data infrastructure we have developed to integrate and analyse multi-level environmental data that can be used to better understand canine comorbidity and aging. DAP datasets are available upon request at https://dogagingproject.org/open_data_access.