Minimally invasive surgery is a highly complex and technically demanding alternative to open surgery. Surgical procedures based on this method are characterized by small incisions and allow for a fast recovery of the patient. Such techniques are challenging for surgeons since they do not have a direct view of the surgical area. Systems that provide surgical navigation are well established in clinical practice but depend on external markers allowing a mapping between a surgeon's tools and a patient's medical images. As of today, these systems are prone to inaccuracies, the reasons of which lie in their extensive technical requirements. The BIOPASS project aims to develop an alternative that works without external markers and indirect computation of locations. An ontology has been used to provide an adequate vocabulary describing situations and their temporal relationship. This ontology is expected to relate real time multimodal sensor data and static surgical process models in order to infer movement directions, subsequent actions and hidden anatomical structures that inhere risk for surgical interventions. However, the Web Ontology Language is not capable of modelling temporal conditions, which are necessary to provide such exhaustive situational descriptions as expected by a surgeon. This paper concerns an ontology design pattern developed to overcome this issue by the integration of dynamic ontological classes that are assigned according to the temporal relations between situations.
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