A software engineering framework for context-aware pervasive computing

There is growing interest in the use of context-awareness as a technique for developing pervasive computing applications that are flexible, adaptable, and capable of acting autonomously on behalf of users. However, context-awareness introduces various software engineering challenges, as well as privacy and usability concerns. In this paper, we present a conceptual framework and software infrastructure that together address known software engineering challenges, and enable further practical exploration of social and usability issues by facilitating the prototyping and fine-tuning of context-aware applications.

A reference methodology for conducting ontological analyses

The ontological analysis of conceptual modelling techniques is of increasing popularity. Related research did not only explore the ontological deficiencies of classical techniques such as ER or UML, but also business process modelling techniques such as ARIS or even Web services standards such as BPEL4WS. While the selected ontologies are reasonably mature, it is the actual process of an ontological analysis that still lacks rigor. The current procedure leaves significant room for individual interpretations and is one reason for criticism of the entire ontological analysis. This paper proposes a procedural model for the ontological analysis based on the use of meta models, the involvement of more than one coder and metrics. This model is explained with examples from various ontological analyses.