Synergistic User <-> Context Analytics

Hossmann, Andreea Maria; Li, Zan; Zhao, Zhongliang; Braun, Torsten; Marios Angelopoulos, Constantinos; Evangelatos, Orestis; Rolim, José; Papandrea, Michela; Garg, Kamini; Giordano, Silvia; C. Y. Tossou, Aristide; Dimitrakakis, Christos; Mitrokotsa, Aikaterini (October 2015). Synergistic User <-> Context Analytics. Advances in Intelligent Systems and Computing, 399, pp. 163-172. Springer International Publishing 10.1007/978-3-319-25733-4_17

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Various avours of a new research field on (socio-)physical or personal analytics
have emerged, with the goal of deriving semantically-rich insights from people's low-level physical sensing combined with their (online) social interactions. In this paper, we argue for more comprehensive data sources, including environmental (e.g. weather, infrastructure) and application-specific data, to better capture the interactions between users and their context, in addition to those among users. To illustrate our proposed concept of synergistic user <-> context analytics, we first provide some example use cases. Then, we present our ongoing work towards a synergistic analytics platform: a testbed, based on mobile crowdsensing and the Internet of Things (IoT), a data model for representing the different sources of data and their connections, and a prediction engine for analyzing the data and producing insights.

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