Most control synthesis methods under temporal logic properties require a model of the system, however, identifying such a model can be a challenging task for complex systems. In this paper, we develop a direct data-driven controller synthesis method for linear systems subject to a temporal logic specification, which does not require this explicit modeling step. After collecting a single sequence of input-output data from the system, we construct a data-driven characterization of the system behavior. Using this data-driven characterization we show that we can synthesize a controller, such that the controlled system satisfies a signal temporal logic-based specification. The underlying optimization problem is solved by mixed-integer linear programming. We demonstrate applicability of the results through benchmark simulation examples.