The ESA/Gaia space mission archive is a gargantuan database that comprises billions of individual entities, and a total of a petabyte of data, and visualizing all this data in 3D is an enormous challenge.
Our aim? To create the necessary technology to make it possible to visualize all this data interactivelly, in 3D, and using common computers and portable devices. Today this is simply impossible; it is even hard to do it using large supercomputers.
To make this possible we are using advanced space indexing schemes, machine-learning, clustering analysis, data sampling, software optimizations, parallel computing, off-loading, cloud computing resources and many other leading edge basic methods from basic research. We are bring all this knowledge to real world applications: after all, the Gaia satellite is already transfering data to the Earth, and by solving Gaia's archive problem, a generic big data challenge is also solved.
This project is partially funded by ESA, and our partners are the Universidade de Lisboa (SIM), Uninova CA3, and Universität Wien.