Benefits of Integrating Meta Data into a Context Model

Hönle, Nicola; Käppeler, Uwe-Philipp; Nicklas, Daniela; Schwarz, Thomas; Großmann, Matthias

doi:10.1109/percomw.2005.20

Cited by 45 publications

(39 citation statements)

References 5 publications

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“…Temporal, spatial and quality of service attributes represent types of meta-data that may be integrated into a context model to provide more intelligent and focused use of data [7]. This approach has been applied in the Nexus framework [8] which provides a common context model infused with spatial information to build world models that are distributed across spaces possessing rich context data sources, known as Augmented Areas.…”

Section: Related Workmentioning

confidence: 99%

Distributed Applications and Interoperable Systems

Kutvonen¹,

König

Tienari³

2006

Lecture Notes in Computer Science

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Abstract. Global smart spaces are intended to provide their inhabitants with context-aware access to pervasive services and information relevant to large geographical areas. Transportation is one obvious domain for such global smart spaces since applications can be built to exploit the variety of sensor-rich systems that have been deployed to support urban traffic control and highway management as well as within individual vehicles. This paper presents a spatial programming model designed to provide a standardised way to build contextaware global smart space applications using information that is distributed across independent (legacy, sensor-enabled, and embedded) systems by exploiting the overlapping spatial and temporal attributes of the information maintained by these systems. The spatial programming model is based on a topographical approach to modelling space that enables systems to independently define and use potentially overlapping spatial context in a consistent manner and in contrast to topological approaches, in which geographical relationships between objects are described explicitly. Moreover, this approach facilitates the incremental construction of global smart spaces since the underlying systems to be incorporated are largely decoupled. The programming model has been evaluated by building a context-aware service for multi-modal urban journey planning, as part of the development of an overall architecture for intelligent transportation systems in Dublin.

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Section: Related Workmentioning

confidence: 99%

Distributed Applications and Interoperable Systems

Kutvonen¹,

König

Tienari³

2006

Lecture Notes in Computer Science

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“…Therefore, our approach explicitly addresses the requirements arising from a heterogeneous computing environment. Metadata can be associated to context elements and also to context values similar to what is proposed by Hoenle et al [11], which comes as an appropriate mean to deal with the special properties of context information and also facilitates merging of context information when nodes have been partitioned. Last but not least, we incorporate some ideas from Henricksen and Indulska [6] [7] in order to ease the development task by employing an MDD approach.…”

Section: Discussionmentioning

confidence: 99%

“…In [11], Hoenle et al highlight the benefits of integrating meta-data into the context model. They argue, that meta-data facilitate important aspects like the assessment of the quality of context information, sensor fusion and data cleansing and provide more flexibility when dealing with context information.…”

Section: Existing Approaches On Context Modelingmentioning

confidence: 99%

A Comprehensive Context Modeling Framework for Pervasive Computing Systems

Reichle

Wagner

Khan

et al. 2008

Lecture Notes in Computer Science

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Abstract. Context management in pervasive computing environments must reflect the specific characteristics of these environments, e.g. distribution, mobility, resource-constrained devices, or heterogeneity of context sources. Although a number of context models have been presented in the literature, none of them supports all of these requirements to a sufficient extent at the same time. In this paper, we present a comprehensive and integrated approach for context modeling in pervasive computing environments. It combines the advantages of existing approaches and addresses the need for supporting effective software development. The proposed context model follows an ontology-based approach and has three layers of abstraction, i.e. conceptual layer, exchange layer, and functional layer. This layered approach facilitates a model-driven development of context-aware applications. Throughout the paper we compare our solution with the related work in order to clearly demonstrate why we needed to develop a new context management framework and where we have adopted existing ideas.

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“…From a conceptual point of view our research is related with knowledge engineering and knowledge integration techniques specialized for pervasive computations (Chen et al, 2004;Zhou et al, 2005;Hönle et al, 2005). In this area the concept of ontology plays now the leading role for knowledge representation.…”

Section: Formal Foundationsmentioning

confidence: 99%