Towards capturing social interactions with SDCF: an extensible framework for mobile sensing and ubiquitous data collection

Authors:
Martin Atzmueller;Katy Hilgenberg
Affiliations:
University of Kassel, Kassel, Germany;University of Kassel, Kassel, Germany
Venue:
Proceedings of the 4th International Workshop on Modeling Social Media
Year:
2013

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Abstract

Social media as well as mobile devices have woven themselves into everyday life, mediating various implicit and explicit social interactions. The analysis and modeling of the interaction data, including both physical and online social interactions is receiving increasing interest. A prerequisite is then given by effective approaches for data collection, covering both sensor data and social media artifacts. This paper describes the Sensor Data Collection Framework (SDCF), a compact, versatile and easily extensible open source framework for mobile sensing and ubiquitous data collection. It provides an overview on core concepts and architecture. Furthermore, we discuss first experiences and results of applying the framework in a collaborative workgroup context.