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Querying Heterogeneous Personal Information On The Go

Publication Type: 
Refereed Conference Meeting Proceeding
Mobile devices are becoming a central data integration hub for personal information. Thus, an up-to-date, comprehensive and consolidated view of this information across heterogeneous personal information spaces is required. Linked Data off ers various solutions for integrating personal information, but none of them comprehensively addresses the specifi c resource constraints of mobile devices. To address this issue, this paper presents a uni ed data integration framework for resource-constrained mobile devices. Our generic, extensible framework not only provides a uni ed view of personal data from di fferent personal information data spaces but also can run on a user's mobile device without any external server. To save processing resources, we propose a data normalisation approach that can deal with ID-consolidation and ambiguity issues without complex generic reasoning. This data integration approach is based on a triple storage for Android devices with small memory foot-print. We evaluate our framework with a set of experiments on diff erent devices and show that it is able to support complex queries on large personal data sets of more than one million triples on typical mobile devices with very small memory footprint.
Conference Name: 
ISWC 2014
The Semantic Web–ISWC 2014
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Research Group: 
National University of Ireland, Galway (NUIG)
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