In the last years, technologies such as GPS, sensors and embedded computing systems became ubiquitous. There are countless applications today that are based on these technologies, e.g., in domains such as transportation, climate and meteorology, health, energy, etc. In this context, enormous amounts of spatiotemporal data are produced every day. The data flows from mobile sensors (e.g., installed in vehicles) or fixed (e.g., sensors for environmental monitoring) need to be interpreted and analyzed. The existing database management systems are offering limited capabilities to manage such data. Therefore, an important problem that needs to be considered by the database research community is to find appropriate models and efficient algorithms for managing spatiotemporal sensor data.