SCIMS: A Social Context Information Management System for Socially-Aware Applications

Abstract

Social Context Information has been used with encouraging results in developing socially-aware applications in different domains. However, users' social information is distributed over the web and managed by many different proprietary applications, which is a challenge for application developers as they must collect information from different sources and wade through a lot of irrelevant information to obtain the social context information of interest. Combining the social information from the diverse sources and incorporating richer semantics could greatly assist the developers and enrich the applications. In this paper, we introduce SCIMS, a social context information management system. It includes the ability to acquire raw social data from multiple sources; an ontology based model for classifying, inferring and storing social context information, in particular, social relationships and status; an ontology based policy model and language for owners to control access to their information; a query interface for accessing and utilizing social context information. We evaluate the performance and scalability of SCIMS using real data from Facebook, LinkedIn, Twitter and Google calendar, and demonstrate its applicability through a socially-aware phone call application.