We propose a computational model based on OWL/SWRL enabled ontologies, which can shape the development of an automated software tool for the purpose of providing patient-specific reminders, advice and action-items in preventing the development of diabetic foot in diabetic patients. The tool is aimed at both: (i) patients who would like to manage their illness efficiently by being informed and alerted to the significance of any change(s) they detect in their feet and (ii) healthcare professionals who can disseminate their knowledge to patients more effectively, and thus prevent the development of diabetic foot, which may cause the premature death of diabetic patients. The advantages of using OWL/SWRL enabled ontologies in our computational model are numerous. They range from the power to store, manage and reason effectively upon knowledge and information related to diabetic foot problems and their prevention through OWL/SWRL computations, to the feasibility of including such computations into software applications, which may run as a set of Apps on Android devices or on personalized healthcare iClouds. Consequently in the core of our proposal are (a) the OWL ontological model and its constraints which define and store the semantics of symptoms and observations of the changes in diabetic patient's feet and (b) a reasoning process which uses the semantics and the power of ontological matching through SWRL for the purpose of delivering functionalities of the tool.