Pervasive, context-aware computing technologies are essential drivers of next generation applications and appliances that will profoundly impact the way we work and play, conduct research, impart education, govern ourselves and care for our health. In order to support context-aware applications and achieve multidevice interoperability, it is important to develop an effective framework and representation language(s) for capturing and representing activity and context information, reasoning about the information and moving such information across devices in a secure and efficient manner. Our intent was as follows: First, discuss and review existing and novel Activity Context Representation and Exchange Languages. Discuss results from creation of solution architectures and proposals for languages, data structures, operations to enable top use-case categories. Second, discuss papers and proposals for new research areas and review work building on key research themes with specific opportunities for collaborative work in the next two-three years in this academically and commercially important area, with topics including, but not limited to semantic computing, task modeling, context representation, and activity recognition.

In this paper, we present some of our work in mobile user modeling following the three steps in a general user modeling process. First, we outline a framework for mobile user activity logging. The framework integrates various hardware and software sensors on smartphones. Second, we have worked on learning relevant user locations for personal information management and recognizing user activities from sensor data to analyze the collected data. Third, the user model can be used to adapt mobile information access, for example in mobile recommender systems. The paper also outlines some requirements for an Activity Context Representation and Exchange Language from the perspective of mobile user modeling.