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dc.contributor.authorThakker, Dhaval*
dc.contributor.authorDimitrova, V.*
dc.contributor.authorCohn, A.G.*
dc.contributor.authorValdes, J.*
dc.date.accessioned2016-09-21T15:45:55Z
dc.date.available2016-09-21T15:45:55Z
dc.date.issued2015
dc.identifier.citationThakker D, Dimitrova V, Cohn AG et al (2015) PADTUN - using semantic technologies in tunnel diagnosis and maintenance domain. In: Gandon F, Sabou M, Sack H et al (Eds.) The Semantic Web. Latest Advances and New Domains. 12th European Semantic Web Conference, ESWC 2015, 31 May-4 Jun 2015, Portoroz, Slovenia. Switzerland: Springer International Publishing : 683-698.
dc.identifier.urihttp://hdl.handle.net/10454/9232
dc.descriptionYes
dc.description.abstractA Decision Support System (DSS) in tunnelling domain deals with identifying pathologies based on disorders present in various tunnel portions and contextual factors affecting a tunnel. Another key area in diagnosing pathologies is to identify regions of interest (ROI). In practice, tunnel experts intuitively abstract regions of interest by selecting tunnel portions that are susceptible to the same types of pathologies with some distance approximation. This complex diagnosis process is often subjective and poorly scales across cases and transport structures. In this paper, we introduce PADTUN system, a working prototype of a DSS in tunnelling domain using semantic technologies. Ontologies are developed and used to capture tacit knowledge from tunnel experts. Tunnel inspection data are annotated with ontologies to take advantage of inferring capabilities offered by semantic technologies. In addition, an intelligent mechanism is developed to exploit abstraction and inference capabilities to identify ROI. PADTUN is developed in real-world settings offered by the NeTTUN EU Project and is applied in a tunnel diagnosis use case with Société Nationale des Chemins de Fer Français (SNCF), France. We show how the use of semantic technologies allows addressing the complex issues of pathology and ROI inferencing and matching experts’ expectations of decision support.
dc.relation.isreferencedbyhttp://dx.doi.org/10.1007/978-3-319-18818-8_42
dc.rights© 2015 Springer International Publishing. Full-text reproduced in accordance with the publisher’s self-archiving policy.
dc.subjectTunnel diagnosis; ROI inferencing using semantics; Tunnel ontology
dc.titlePADTUN - using semantic technologies in tunnel diagnosis and maintenance domain
dc.status.refereedYes
dc.typeConference paper
dc.type.versionAccepted manuscript
refterms.dateFOA2018-07-25T14:09:06Z


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