District-Scale Data Integration by Leveraging Semantic Web Technologies – a Case in Smart Cities

Tracking #: 1610-2822

This paper is currently under review
Authors: 
Hendro Wicaksono
Kiril Tonev
Simon Kappe
Preslava Krahtova

Responsible editor: 
Guest Editors ST Built Environment 2017

Submission type: 
Full Paper
Abstract: 
Smart city initiatives aim at a more sustainable city characterized by integrated technologies and services related to energy efficiency such as smart metering and monitoring, building energy simulation, energy consumption prediction, and de-mand-response management. Achieving these aims also relies on the active and synergetic involvement from multiple stake-holders: citizens, utility companies, policy makers and energy providers. Central to this cooperation is the access and efficient processing of up-to-date and comprehensive information from multiple, originally unrelated domains. The technologies of the Semantic Web stack promise to alleviate some of the challenges related to data integration on a massive scale and high level of heterogeneity. This paper explores their application in the smart cities domain with a focus on energy efficient districts. First, we develop an ontology grounded in several well-established vocabularies to leverage their shared semantics and facilitate data interoperability. We apply the developed ontology to integrate state-of-the-art energy simulation facilities into a general district-level monitoring framework. Next, we develop a highly-consumable RESTful interface driven by semantic technologies to provide up-to-date access to the integrated data without restricting its potential to achieve internet-scale. A third contribution demonstrates the assessment of data quality based on the linked data approach to validate the integrated dataset against a set of use cases. The framework has been validated within the European research project DAREED.
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