Advances in data acquisition—through more powerful supercomputers for simulation or sensors with better resolution—help scientists tremendously to understand natural phenomena. At the same time, however, it leaves them with a plethora of data and the challenge of analysing it. Ingesting all the data in a database or indexing it for an efficient analysis is unlikely to pay off because scientists rarely need to analyse all data. Not knowing a priori what parts of the datasets need to be analysed makes the problem challenging. Tools and methods to analyse only subsets of this data are rather rare. In this paper we therefore present Space Odyssey, a novel approach enabling scientists to efficiently explore multiple spatial datasets of massive size. Without any prior information, Space Odyssey incrementally indexes the datasets and optimizes the access to datasets frequently queried together. As our experiments show, through incrementally indexing and changing the data layout on disk, Space Odyssey accelerates exploratory analysis of spatial data by substantially reducing query-to-insight time compared to the state of the art.