Problems in Context-Aware Semantic Computing

Abstract

Acknowledging the user context, e.g., position and activity, provides a natural way to adapt applications according to the user needs. How to actually capture and exploit context, however, is not self-evident and it is tempting to assign the related responsibilities to individual context-consuming applications. Unfortunately, this confuses the user, complicates application development and hinders context-aware semantic computing as a research discipline. In this article, we outline context-aware semantic computing research topics and the state-of-the-art mobile application development frameworks of special interest to us, acknowledging best practices for accessing and modeling sensor context. From the integrated point of view, context-aware semantic computing is demonstrated in terms of a software component called context engine. In order to better understand how theory is tied with practice, we also introduce a simple context engine prototype. Finally, we use the research background and the empirical setting to discuss the significant problems and relevant research directions in context-aware semantic processing.

Exploring Processes that are Used for Managing Knowledge in the Higher Education Environment: A Case Study in a Queensland Regional University

“…The sixth key theme identified in this research is knowledge capture. These results conform to the work of Bouguettaya et al (2012); Hoang (2016); Nalepa and Bobek (2014); Nykänen and Rodriguez (2014); Salminen, Jauhiainen, and Nurmeksela (2014) who point out that there is a necessary to capture knowledge in various methods such as "Direct sensor access", "Middleware infrastructure", and "Context server". Knowledge sharing is the seventh major theme mentioned by participants.…”

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“…66 Standard representation of context data in context-aware systems can be built upon semantic web metadata standards, such as Resource Description Framework (RDF) and OWL. 67 There are many modelling approaches: SNN, 61 SOCAM, 65 ASSL 65 and Process Mining. 65 Despite the technological advancements and research results, the realization and the role of complex context-aware computing are not clear in application ecosystem(s).…”

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“…Motivated by the current problems in context-aware semantic computing, Nykänen and Rivero-Rodriguez demonstrated an integrated point-of-view in terms of a software component, called the Context Engine (CE) [7]. It is a centralised software services that provides a point of access to a backend of context-aware computing tools and repositories.…”

“…However, we believe we can further exploit this notion to the benefit of context-awareness tools, such as the Context Engine (CE) software service of Nykänen and Rivero-Rodriguez [7].…”