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BIGSEA: A Big Data analytics platform for public transportation information

AutorAlic, Andy S.; Almeida, Jussara; Aloisio, Giovanni; Andrade, Nazareno; Antunes, Nuno; Ardagna, Danilo; Badia, Rosa M.; Basso, Tania; Blanquer, Ignacio CSIC ORCID; Braz, Tarciso; Brito, Andrey; Elia, Donatello; Fiore, Sandro; Guedes, Dorgival; Lattuada, Marco; Lezzi, Daniele; Maciel, Matheus; Meira, Wagner; Mestre, Demetrio; Moraes, Regina; Morais, Fabio; Pires, Carlos Eduardo; Kozievitch, Nádia P.; Dos Santos, Walter; Silva, Paulo; Vieira, Marco
Fecha de publicaciónjul-2019
EditorElsevier
CitaciónFuture Generation Computer Systems 96: 243-269 (2019)
ResumenAnalysis of public transportation data in large cities is a challenging problem. Managing data ingestion, data storage, data quality enhancement, modelling and analysis requires intensive computing and a non-trivial amount of resources. In EUBra-BIGSEA (Europe–Brazil Collaboration of Big Data Scientific Research Through Cloud-Centric Applications) we address such problems in a comprehensive and integrated way. EUBra-BIGSEA provides a platform for building up data analytic workflows on top of elastic cloud services without requiring skills related to either programming or cloud services. The approach combines cloud orchestration, Quality of Service and automatic parallelisation on a platform that includes a toolbox for implementing privacy guarantees and data quality enhancement as well as advanced services for sentiment analysis, traffic jam estimation and trip recommendation based on estimated crowdedness.
Versión del editorhttp://dx.doi.org/10.1016/j.future.2019.02.011
URIhttp://hdl.handle.net/10261/197440
DOI10.1016/j.future.2019.02.011
ISSN0167-739X
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