The development and evaluation of new data mining methods for ubiquitous environments and systems requires real data that were collected from real users. Here, we present an open smartphone utilization and mobility data set that was generated with several devices and participants during the SFB876 summer school 2012. It may be categorized into high-level user context, external sensing, and system internals. High-Level User Context is utilization data that contains direct hints to the participant’s current activity and context. This includes the state of the display (on/off, brightness) and the phone (idle, ringing, or off the hook). Sensing data is obtained from various physical sensors as well as positioning and communication hardware. The physical sensors measured acceleration, magnetic field strength, orientation and light intensity. A particularity of this data set is the inclusion of low-level operating system data. System Internal data mainly describes the overall usage of the system’s resources like the CPU, the battery, the main memory and the network interfaces. The use of Android wakelocks also belongs to this category. A more detailed description of the data set, a description of the collection process and the privacy measures we applied can be found in [Streicher/etal/2013b].