Co-located Collaboration Analysis Based on Group Traces

Group collaboration often quickly shifts between the remote and the co-located environment. The process of group co-located collaboration (CC) involves a series of synchronous interactive activities in a shared physical workspace. Although the popularization of smart devices, intelligent sensor technology and stable high-speed networks makes CC more efficient and recordable, the resulting large amount of multimodal data also creates more challenges for the analysis process. Moreover, the individual understanding of co-located activities relating to the past is susceptible to changes over time. In this article, five elementary categories of information are introduced with the discussion of five basic questions concerning awareness information and the classification of sensor indicators. A framework for CC analysis based on group traces is proposed and explained, which contains the basic information mentioned above. Taking advantage of device and face recognition technique, the framework is applied and validated in the web-based collaborative working environment MCWE2.0 with an actual group meeting example.