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ATU-DSS: knowledge-driven data integration and reasoning for sustainable subsurface inter-asset management

Wei, Lijun; Du, Heshan; Mahesar, Quratul-ain; Clarke, Barry; Magee, Derek R.; Dimitrova, Vania; Gunn, David; Entwisle, David; Reeves, Helen; Cohn, Anthony G.. 2018 ATU-DSS: knowledge-driven data integration and reasoning for sustainable subsurface inter-asset management. In: Gangemi, Aldo, (ed.) The Semantic Web: ESWC 2018 Satellite Events. Springer, 8-13. (Lecture Notes in Computer Science, 11155, 11155).

Abstract
Urban infrastructure assets perform critical functions to the health and well-being of the society. In this paper, we present a prototype decision support system for sustainable subsurface inter-asset management. To the best of the authors’ knowledge, this work is the first on assessing the underground space by considering the inter-asset dependencies using semantic technologies. Based on a family of interlinked city infrastructure asset ontologies describing the ground, roads and buried utilities (e.g. water pipes), various datasets are integrated and logical rules are developed to describe the intra-asset and inter-asset relationships. An inference engine is employed to exploit the knowledge and data for assessing the potential impact of an event. This system can be beneficial to a wide range of stakeholders (e.g. utility incident managers) for quickly gathering of the localised contextual data and identifying potential consequences from what may appear as an insignificant trigger. A video demonstrating the prototype is available at: http://bit.ly/2mdyIY4.
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Programmes:
BGS Programmes 2018 > Engineering Geology & Infrastructure
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