Enabling Knowledge Extraction on Bike Sharing Systems Throughout Open Data

Bike Sharing Systems (BSS) have changed urban mobility patterns. Their study as part of the overall transport system in cities is attracting growing attention in recent years. Nevertheless, some deficiencies such as the lack of convention in data serving tools and the absence of historical informati...

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Detalles Bibliográficos
Autores: Marquez-Saldaña, Francisco J., Aranda-Corral, Gonzalo A., Borrego Díaz, Joaquín
Tipo de recurso: capítulo de libro
Estado:Versión aceptada para publicación
Fecha de publicación:2022
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/171616
Acceso en línea:https://hdl.handle.net/11441/171616
https://doi.org/10.1007/978-3-031-04987-3_39
Access Level:acceso abierto
Palabra clave:Data acquisition
Big data in mobility
Bike sharing platforms
ETL
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spelling Enabling Knowledge Extraction on Bike Sharing Systems Throughout Open DataMarquez-Saldaña, Francisco J.Aranda-Corral, Gonzalo A.Borrego Díaz, JoaquínData acquisitionBig data in mobilityBike sharing platformsETLBike Sharing Systems (BSS) have changed urban mobility patterns. Their study as part of the overall transport system in cities is attracting growing attention in recent years. Nevertheless, some deficiencies such as the lack of convention in data serving tools and the absence of historical information difficult the analysis and improvement of realistic BSS digital platforms. Additionally, other challenges related to the Big Data nature of the analysis, have hindered an integral data analysis. This paper outlines solutions for both problems, based on a sound addressing for the Big Data Extraction-Transformation-Loading (ETL) problem of storing historical BSS data. In particular, consumption tools have been provided. They not only allow handling recorded information but also allow enhancing BSS knowledge. This way the overall system can manage other relevant information (KPIs and statistics in nature). The Big Data-inspired solution proposed in this paper solves this kind of issue, showing how it can manage more data collected during a period of about six years and from twenty-seven systems. Such data have been stored and enabled for both machine-machine communication and Human-Computer Interaction.PID2019-109152GB-I00/AEI/ 10.13039/501100011033Springer NatureCiencias de la Computación e Inteligencia ArtificialAgencia Estatal de Investigación. España2022info:eu-repo/semantics/bookPartinfo:eu-repo/semantics/acceptedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/171616https://doi.org/10.1007/978-3-031-04987-3_39reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésHCI in Mobility, Transport, and Automotive Systems. Lecture Notes in Computer Science (LNCS,volume 13335)https://link.springer.com/chapter/10.1007/978-3-031-04987-3_39info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1716162026-06-17T12:51:07Z
dc.title.none.fl_str_mv Enabling Knowledge Extraction on Bike Sharing Systems Throughout Open Data
title Enabling Knowledge Extraction on Bike Sharing Systems Throughout Open Data
spellingShingle Enabling Knowledge Extraction on Bike Sharing Systems Throughout Open Data
Marquez-Saldaña, Francisco J.
Data acquisition
Big data in mobility
Bike sharing platforms
ETL
title_short Enabling Knowledge Extraction on Bike Sharing Systems Throughout Open Data
title_full Enabling Knowledge Extraction on Bike Sharing Systems Throughout Open Data
title_fullStr Enabling Knowledge Extraction on Bike Sharing Systems Throughout Open Data
title_full_unstemmed Enabling Knowledge Extraction on Bike Sharing Systems Throughout Open Data
title_sort Enabling Knowledge Extraction on Bike Sharing Systems Throughout Open Data
dc.creator.none.fl_str_mv Marquez-Saldaña, Francisco J.
Aranda-Corral, Gonzalo A.
Borrego Díaz, Joaquín
author Marquez-Saldaña, Francisco J.
author_facet Marquez-Saldaña, Francisco J.
Aranda-Corral, Gonzalo A.
Borrego Díaz, Joaquín
author_role author
author2 Aranda-Corral, Gonzalo A.
Borrego Díaz, Joaquín
author2_role author
author
dc.contributor.none.fl_str_mv Ciencias de la Computación e Inteligencia Artificial
Agencia Estatal de Investigación. España
dc.subject.none.fl_str_mv Data acquisition
Big data in mobility
Bike sharing platforms
ETL
topic Data acquisition
Big data in mobility
Bike sharing platforms
ETL
description Bike Sharing Systems (BSS) have changed urban mobility patterns. Their study as part of the overall transport system in cities is attracting growing attention in recent years. Nevertheless, some deficiencies such as the lack of convention in data serving tools and the absence of historical information difficult the analysis and improvement of realistic BSS digital platforms. Additionally, other challenges related to the Big Data nature of the analysis, have hindered an integral data analysis. This paper outlines solutions for both problems, based on a sound addressing for the Big Data Extraction-Transformation-Loading (ETL) problem of storing historical BSS data. In particular, consumption tools have been provided. They not only allow handling recorded information but also allow enhancing BSS knowledge. This way the overall system can manage other relevant information (KPIs and statistics in nature). The Big Data-inspired solution proposed in this paper solves this kind of issue, showing how it can manage more data collected during a period of about six years and from twenty-seven systems. Such data have been stored and enabled for both machine-machine communication and Human-Computer Interaction.
publishDate 2022
dc.date.none.fl_str_mv 2022
dc.type.none.fl_str_mv info:eu-repo/semantics/bookPart
info:eu-repo/semantics/acceptedVersion
format bookPart
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/171616
https://doi.org/10.1007/978-3-031-04987-3_39
url https://hdl.handle.net/11441/171616
https://doi.org/10.1007/978-3-031-04987-3_39
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv HCI in Mobility, Transport, and Automotive Systems. Lecture Notes in Computer Science (LNCS,volume 13335)
https://link.springer.com/chapter/10.1007/978-3-031-04987-3_39
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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