This project supports the development of new cyberinfrastructure (CI) that enables rapid and efficient access to the massive datasets produced by computer simulations of galaxy formation. Such simulations are crucial for the development of new theories about where our galaxy came from and how it formed; for helping aid the interpretation of data from new telescopes like the James Webb Space Telescope; and for providing predictions for new surveys like the Legacy Survey of Space and Time that is being conducted by the Vera Rubin Observatory. Analyzing the data produced by these simulations is almost as demanding as running them because they produce petabyte-scale datasets representing hundreds of thousands or even millions of galaxies. Luckily, most analysis is only interested in a handful of objects at a time, but no software currently exists to let astronomers retrieve these critical subsets of the data easily or efficiently, leaving analysis siloed in massive high performance computing clusters. Socket addresses this problem, allowing easy selection of data subsets over a standard internet connection, significantly widening its audience. Socket will not only allow more people to do more research with this data more quickly but is also designed to empower modern Artificial Intelligence and Machine Learning-based research. Socket is an open, high-performance data access platform for adaptive particle simulations. It is primarily focused on cosmological galaxy formation si