Supporting context-aware engineering based on stream reasoning

Kramer, Dean and Augusto, Juan Carlos ORCID: https://orcid.org/0000-0002-0321-9150 (2017) Supporting context-aware engineering based on stream reasoning. Modeling and Using Context: 10th International and Interdisciplinary Conference, CONTEXT 2017, Paris, France, June 20-23, 2017, Proceedings. In: CONTEXT'17: 10th International and Interdisciplinary Conference on Modeling and Using Context, 20-23 June 2017, Paris, France. ISBN 9783319578361. ISSN 0302-9743 [Conference or Workshop Item] (doi:10.1007/978-3-319-57837-8_37)

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Abstract

In a world of increasing dynamism, context-awareness gives promise through the ability to detect changes in the context of devices, environment, and people. Equally, with stream reasoning using languages including C-SPARQL, continuous streams of raw data in RDF can be reasoned over for context awareness. Writing many context queries and rules this way can however be error prone, and often contains boilerplate. In this paper, we present a context modelling notation designed to support the creation of context-awareness based on stream reasoning systems. In validating our language there is tool support which, amongst other benefits, can generate context queries in C-SPARQL and context aggregation rules for higher level context knowledge processing. An Android compatible mobile platform context reasoner was developed which can handle these deployable context rules. This methodology and associated tools has been validated as part of an EU funded project.

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