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Linking open data and the crowd for real-time passenger information.

Corsar, David; Edwards, Peter; Nelson, John; Baillie, Chris; Papangelis, Konstantinos; Velaga, Nagendra

Authors

Peter Edwards

John Nelson

Chris Baillie

Konstantinos Papangelis

Nagendra Velaga



Abstract

The availability of real-time passenger information (RTPI) is a key factor in making public transport both accessible and attractive to users. Unfortunately, rural areas often lack the infrastructure necessary to provide such information, and the cost of deploying and maintaining the required technologies outside of urban areas is seen as prohibitive. In this paper we present the GetThere system developed to overcome such issues and to provide public transport users in rural areas with RTPI. An ontological framework for representing mobility information is described, along with the Linked Data approach used to integrate heterogeneous data from multiple sources including government, transport operators, and the public. To mitigate possible issues with the veracity of this data, a quality assessment framework was developed that utilises data provenance. We also discuss our experiences working with Semantic Web technologies in this domain, and present results from both a user trial and a performance evaluation of the system.

Citation

CORSAR, D., EDWARDS, P., NELSON, J., BAILLIE, C., PAPANGELIS, K. and VELAGA, N. 2017. Linking open data and the crowd for real-time passenger information. Journal of web semantics [online], 43, pages 18-24. Available from: https://doi.org/10.1016/j.websem.2017.02.002

Journal Article Type Article
Acceptance Date Feb 21, 2017
Online Publication Date Feb 28, 2017
Publication Date Mar 31, 2017
Deposit Date Jan 17, 2020
Publicly Available Date Jan 17, 2020
Journal Journal of Web Semantics
Print ISSN 1570-8268
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 43
Pages 18-24
DOI https://doi.org/10.1016/j.websem.2017.02.002
Keywords Semantic web; Ontology; Quality; Provenance; Transport; Citizen-sensing
Public URL https://rgu-repository.worktribe.com/output/816275

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