Many research groups are performing high-fidelity simulations of atomizing jets that are taking advantage of the continually increasing speed and size of computational resources and advances in numerical methods. These high-fidelity simulations produce extremely large data sets characterizing the flow and giving the ability to gather a better understanding of atomization. However, a significant challenge with these data sets is their large size, which limits the usefulness of the results. The main goal of the present work is to create a physics extraction technique to compute the genealogy of atomization and store the data in a format that can be easily and quickly queried. This information will characterize the process of the coherent liquid core breaking into droplets and ligaments, which may proceed to break up further. Each event in the atomization process will be combined with detailed information, such as droplet size, shape, flow field characteristics, etc. The extracted information is stored in a neo4j database that allows queries. The ultimate goal of the work is to use this information to improve our understanding of atomization and enhance the development and testing of low-fidelity atomization models.