Situation Awareness is a key concept in activities in which cognitive and physical tasks are being performed in a complex system consisting of multiple humans and artifacts, under quickly changing conditions. The spread, in sports, of wearable technologies that can record and return in real time a wide variety of data related to the athlete and to the context provides a great opportunity to increase the level of Situation Awareness. Often, however, we are dealing with heterogeneous devices that work on very specific elements and, taken individually, are not sufficient to build an effective representation of the complexity of the phenomenon. The set of raw data in different formats and different levels of detail coming from the different wearable devices acquire real information value in the moment in which they are modeled according to semantic techniques. This paper proposes a framework that, due to semantic techniques, allows to transform a set of heterogeneous devices in a network of sensors that can guide decision making.
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