Scientists in many disciplines have progressively been using simulations to better understand the natural systems they study. Faster hardware, as well as increasingly precise instruments, allow the construction and simulation of progressively advanced models of various systems.

Governed by algorithms and equations, the spatial models at the core of simulations are changed and updated at every simulation step through spatial queries, implementing massive updates. Therefore, the efficient execution of these numerous spatial queries is essential.

Two reasons render current spatial indexes inadequate for simulation applications. First, to ensure quick access to data, most of the spatial models in simulations are stored in memory. Most spatial access methods, however, have been optimized for use on disk and are not efficient in memory. Second, in every time step of a simulation, almost all spatial elements change their position, challenging update mechanisms for spatial indexes.

In this paper we discuss how these challenges create opportunities for exciting data management research.