Social networks are perhaps the purest example of “Web 2.0 ” services, and offer a sophisticated tool for accessing the preferences and properties of individuals and groups. Thus, they potentially allow up-to-date, richly annotated contextual data to be acquired as a side effect of users ’ everyday use of the services. In this paper, we explore how such “social sensing ” could be integrated into pervasive systems. We frame and survey the possible approaches to such an integration, and eventually discuss the open issues and challenges facing researchers. 1

As pervasive computing meets social networks, there is a fast growing research field called Pervasive Social Computing. Applications in this area exploit the richness of information arising out of people using sensor-equipped pervasive devices in their everyday life combined with intense use of different Social Networking Services. We call this set of information Pervasive Social Context. We provide a taxonomy to classify Pervasive Social Context along the dimensions space, time, people, and information source (STiPI) as well as commenting on the type and reason for creating such context. A survey of recent research work shows the applicability and usefulness of the taxonomy in classifying and assessing applications and systems in the area of Pervasive Social Computing. Finally, we present some research challenges in this area and illustrate how they affect the systems being surveyed.

Abstract — The success of Web Services as a tool to decouple and distribute different processes is beyond any doubt. On the one hand, their distributed nature makes them perfect to deploy our applications in a network. On the other hand, the service abstraction provides an easy way to develop large scale solutions by using other’s software components. However, to reach the full potential of Web Services, the need for an accurate search approach arises. Semantic ones use ontologies to describe what services do, but, what does happen when providers and requesters of services do not use the same ontologies, i.e., the same semantic vocabulary? In this paper, we propose an approach to enhance the discovery of Web Services based on the semantic reconciliation of providers and requesters before the discovery process itself. Our system reuses and integrates ontological information extracted from several online pools of ontologies to make possible to: 1) add semantics easily to existing non-semantic services; and, 2) perform a semantic keywordbased search independently of the ontologies used by the provider. Thus, our proposal bridges the semantic gap between requesters and providers.