The goal of this chapter is to provide detailed insights into the field of Semantic Web-based context-aware computing for mobile systems. Readers will learn why context awareness will be a central aspect of future mobile information systems, and about the role semantic technologies can play in creating a context-aware infrastructure and the benefits they offer. The chapter introduces requirements, enabling technologies, and future directions of such systems. It presents a Semantic Web-based context-sensitive infrastructure that resembles concepts from graph theory and distributed transaction management. This infrastructure allows for an efficient acquisition, representation, management, and processing of contextual information while taking into account the peculiarities and operating environments of mobile information systems. Authors demonstrate how context-relevant data acquired from local and remote sensors can be represented using Semantic Web technologies, with the goal to replicate data related to the user’s current and future information needs to a mobile device in a proactive and transparent manner. In consequence, the user is equipped with contextually relevant information anytime and anywhere.
TopIntroduction
The availability and power of mobile devices has significantly increased data-centric mobile applications. Mobility not only influences the types of information we need, but also how we access it, and which tools and mechanisms to process them are at our disposal. To improve mobile application development and the usability of mobile devices in general it is crucial to understand the information needs of mobile users, as well as the interaction metaphors they apply (Sohn, Li, Griswold, & Hollan, 2008).
It is known that mobile search differs substantially from desktop search in terms of intra-query diversity (Kamvar & Baluja, 2006). The diversity of queries initiated in mobile setting is significantly lower compared to queries issued from the desktop. Additionally, query categorization reveals that context searching is similar to desktop, although query exploration is significantly lower. Further differences can be observed with respect to the effort needed to set up a query, and the total amount of queries initiated in one browsing session. Therefore, plain Internet access is often not sufficient for adequately addressing information needs of mobile users. Their situational contexts and current activities cannot be sufficiently addressed. Despite the benefits offered by mobile internet access, issues remain that hinder users from satisfying their information needs. These include impedimental interaction with the device while browsing for information, as well as the extensive attention needed for interaction and information seeking tasks (Sohn et al., 2008). Further, it was observed that mobile users sometimes do not know how to address a specific information need although they had the required resources and tools at their disposal (Sohn et al., 2008).
It has been shown that 72% of mobile information needs can be attributed or related to context (Sohn et al., 2008). This finding indicates that introducing context awareness into mobile information processing infrastructure can be of significant benefit to end-users. Context allows information processing tasks to focus on the user’s information needs, depending on their current situation. In a setting where data from various (internal and external) sources are processed on a mobile device, contextual information can help to determine the importance of data in relation to user tasks and activities.