Querying Heterogeneous Personal Information On The Go
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 offers various solutions for integrating personal information, but none of them comprehensively addresses the specific resource constraints of mobile devices. To address this issue, this paper presents a unied data integration framework for resource-constrained mobile devices. Our generic, extensible framework not only provides a unied view of personal data from different 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 different 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.
The Semantic Web–ISWC 2014
Digital Object Identifer (DOI):
National University of Ireland, Galway (NUIG)
OpenIoT: Open Source Blueprint for Large Scale Self-organizing Cloud Environments for IoT Applications
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