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).

Before downloading, please read NORA policies.

[thumbnail of ATU-DSS_Knowledge-Driven_Data_Integration_and_Reasoning_for_Sustainable_Subsurface_Inter-Asset_Management.pdf]

Preview

Text
ATU-DSS_Knowledge-Driven_Data_Integration_and_Reasoning_for_Sustainable_Subsurface_Inter-Asset_Management.pdf - Accepted Version
Download (525kB) | Preview

Official URL: http://dx.doi.org/10.1007/978-3-319-98192-5_2

Abstract/Summary

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.

Item Type:	Publication - Book Section
Digital Object Identifier (DOI):	10.1007/978-3-319-98192-5_2
ISSN:	0302-9743
Date made live:	03 May 2019 08:47 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/523184

Item Type:

Publication - Book Section

Digital Object Identifier (DOI):

10.1007/978-3-319-98192-5_2

ISSN:

0302-9743

Date made live:

03 May 2019 08:47 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/523184