Recent developments in wireless technology, mobility and networking infrastructures increased the amounts of data being captured every second. Data captured from the digital traces of moving objects and devices is called trajectory data. With the increasing volume of spatiotemporal trajectories, constructive and meaningful knowledge needs to be extracted. In this paper, a conceptual framework is proposed to apply data mining techniques on trajectories and semantically enrich the extracted patterns. A design science research approach is followed, where the framework is tested and evaluated using a prototypical instantiation, built to support decisions in the context of the Egyptian tourism industry. By applying association rule mining, the revealed time-stamped frequently visited regions of interest (ROI) patterns show that specific semantic annotations are required at early stages in the process and on lower levels of detail, refuting the presumption of cross-application usable patterns