Abstract. With the widespread of Internet of Things' devices, sensors, and applications the quantity of collected data grows enormously and the need of extracting, merging, analyzing, visualizing, and sharing it paves the way for new research challenges. This ongoing revolution of how personal devices are used and how they are becoming more and more wearable has important influences on the most well established definitions of end user and end-user development. The paper presents an analysis of the most diffused applications that allow end users to aggregate quantified-self data, originated by several sensors and devices, and to use it in personalized ways. From the outcomes of the analysis, we present a classification model for Internet of Things and new EUD paradigm and language that extends the ones existing in the current state of the art Internet of Things.