Automated Reasoning in Temporal DL-Lite* We investigate the feasibility of automated reasoning over temporal DL-Lite (TDL-Lite) knowledge bases (KBs). We translate TDL-Lite KBs into a fragment of First Order temporal logic and then into LTL, and apply off-the-shelf LTL and FO-based reasoners for checking the satisfiability. We conduct various experiments to analyse the size of the LTL translation as well as the runtime performance of different reasoners on toy scenarios and on randomly generated TDL-Lite KBs. To improve the reasoning performance when dealing with large ABoxes, our work also proposes an approach for abstracting temporal assertions in KBs. We run several experiments with this approach to assess the effectiveness of the technique by measuring the gain in terms of the size of the translation, and the number of both ABox assertions and individuals. We also measure the runtime of the solvers on such abstracted KBs. Lastly, in an effort to make the usage of TDL-Lite KBs a reality, we present a fully-fledged tool with a graphical interface to design and reason over them. Our interface is based on conceptual modeling principles and it is integrated with our translation tool and a temporal reasoner. (*) This work has been submitted to the Journal of Automated Reasoning