Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/17652
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dc.contributor.authorJovanovik, Milosen_US
dc.contributor.authorTrajanov, Dimitaren_US
dc.contributor.authorStojanov, Risteen_US
dc.contributor.authorNajdenov, Bojanen_US
dc.contributor.authorPetkovski, Goranen_US
dc.date.accessioned2022-05-18T08:10:34Z-
dc.date.available2022-05-18T08:10:34Z-
dc.date.issued2015-11-24-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/17652-
dc.description.abstractThe Linked Data approach in data publishing allows the users and their data-driven applications to have broader use cases which encompass various data sources, either publicly available on the Web, or in private repositories. The use of W3C standards in publishing such data enables uniform access across platforms. Transport information today has higher importance to the citizens and society than ever and accessing the right information at the right time can improve the quality of everyday life for many people in the world. In this paper, we describe our approach of building a system for automated Linked Data generation from the transportation domain. We used the data from the Swedish Transport Administration (STA) as a specific case study. For the purpose of RDF annotation, we developed the Transport Administration Ontology (TAO). The resulting five-star data enables advanced use case scenarios over the original STA data, which we also demonstrate with our web application.en_US
dc.publisherIEEEen_US
dc.subject— Automated Systems, Linked Data, Open Data, Transport Administration Ontology, Swedish Transport Administrationen_US
dc.titleAutomated Linked Data Generation from the Transport Administration Domainen_US
dc.typeProceeding articleen_US
dc.relation.conference23rd Telecommunications Forum (TELFOR), 2015en_US
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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