Context' is a significant element in the field of context-aware and pervasive computing. Thereby, a context meta-model defines context on an abstract level. Simultaneously, a context meta-model builds the basis for specific context models that support system designers in their decisions which context variables to integrate in a particular intelligent context-adaptive system. This paper compares 13 meta-models with respect to their scope. Taking an empirical approach, we matched the meta-models against context variables used in research practice. On the one hand, the meta-models find themselves well reflected by research practice, in a sense that the models context categories can be described by context variables reported in research. On the other hand, the results clearly indicate that each of the 13 context meta-models fails to describe the full landscape of context. Many context variables used in reported research are not covered by any of the analysed context meta-models. Accordingly, this paper calls on the research community to advance its basic theories continuously because the research field needs theories that reflect reality.
Bauer, Christine, "A COMPARISON AND VALIDATION OF 13 CONTEXT META-MODELS" (2012). ECIS 2012 Proceedings. Paper 17.