Mining open and crowdsourced data to improve situational awareness for railway

Syed Sadiqur Rahman; John Easton; Clive Roberts

doi:https://doi.org/10.1145/2808797.2809369

Mining open and crowdsourced data to improve situational awareness for railway

Syed Sadiqur Rahman, John Easton, Clive Roberts

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

This paper describes on-going research developing a system to harvest and utilise open and crowdsourced data related to the UK railway systems. This system will allow the controllers and decision makers to listen to the messages posted on social networks by passengers or other members of the public and relate these messages to specific (physical) trains that are referred to in those messages, by fusing information from other open sources. This will enable the railway controllers to take prompt actions in case of any emergency or simply to improve the quality of customer service.

Original language	English
Title of host publication	Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
Publisher	Association for Computing Machinery (ACM)
Pages	1240-1243
ISBN (Electronic)	978-1-4503-3854-7
DOIs	https://doi.org/10.1145/2808797.2809369
Publication status	Published - Aug 2015

Keywords

Railway
Crowd-Sourcing
Open Data Intelligence
Data Fusion
Situation Awareness

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https://doi.org/10.1145/2808797.2809369

Cite this

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title = "Mining open and crowdsourced data to improve situational awareness for railway",

abstract = "This paper describes on-going research developing a system to harvest and utilise open and crowdsourced data related to the UK railway systems. This system will allow the controllers and decision makers to listen to the messages posted on social networks by passengers or other members of the public and relate these messages to specific (physical) trains that are referred to in those messages, by fusing information from other open sources. This will enable the railway controllers to take prompt actions in case of any emergency or simply to improve the quality of customer service.",

keywords = "Railway, Crowd-Sourcing, Open Data Intelligence, Data Fusion, Situation Awareness",

author = "Rahman, {Syed Sadiqur} and John Easton and Clive Roberts",

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booktitle = "Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)",

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Mining open and crowdsourced data to improve situational awareness for railway. / Rahman, Syed Sadiqur; Easton, John; Roberts, Clive.
Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). Association for Computing Machinery (ACM), 2015. p. 1240-1243.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - This paper describes on-going research developing a system to harvest and utilise open and crowdsourced data related to the UK railway systems. This system will allow the controllers and decision makers to listen to the messages posted on social networks by passengers or other members of the public and relate these messages to specific (physical) trains that are referred to in those messages, by fusing information from other open sources. This will enable the railway controllers to take prompt actions in case of any emergency or simply to improve the quality of customer service.

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KW - Crowd-Sourcing

KW - Open Data Intelligence

KW - Data Fusion

KW - Situation Awareness

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DO - https://doi.org/10.1145/2808797.2809369

M3 - Conference contribution

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BT - Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

PB - Association for Computing Machinery (ACM)

ER -

Mining open and crowdsourced data to improve situational awareness for railway

Abstract

Keywords

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