TY - JOUR
T1 - Linking open data and the crowd for real-time passenger information
AU - Corsar, David
AU - Edwards, Peter
AU - Nelson, John
AU - Baillie, Chris
AU - Papangelis, Konstantinos
AU - Velaga, Nagendra
N1 - Publisher Copyright:
© 2017 Elsevier B.V.
PY - 2017/3
Y1 - 2017/3
N2 - 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.
AB - 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.
KW - Citizen-sensing
KW - Ontology
KW - Provenance
KW - Quality
KW - Semantic web
KW - Transport
UR - http://www.scopus.com/inward/record.url?scp=85015317089&partnerID=8YFLogxK
U2 - 10.1016/j.websem.2017.02.002
DO - 10.1016/j.websem.2017.02.002
M3 - Article
AN - SCOPUS:85015317089
SN - 1570-8268
VL - 43
SP - 18
EP - 24
JO - Journal of Web Semantics
JF - Journal of Web Semantics
ER -