Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/337741
Type: Artigo
Title: BIGSEA: a big data analytics platform for public transportation information
Author: Alic, Andy S.
Almeida, Jussara
Aloisio, Giovanni
Andrade, Nazareno
Antunes, Nuno
Ardagna, Danilo
Badia, Rosa M.
Basso, Tania
Blanquer, Ignacio
Braz, Tarciso
Brito, Andrey
Elia, Donatello
Fiore, Sandro
Guedes, Dorgival
Lattuada, Marco
Lezzi, Daniele
Maciel, Matheus
Meira Jr, Wagner
Mestre, Demetrio
Moraes, Regina
Morais, Fabio
Pires, Carlos Eduardo
Kozievitch, Nadia P.
Santos, Walter dos
Silva, Paulo
Vieira, Marco
Abstract: Analysis 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 nontrivial 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. All developments are available under Open Source licenses (http://github.org/eubr-bigsea, https://hub.docker.com/u/eubrabigsea/)
Subject: Big data
Country: Holanda
Editor: Elsevier
Rights: Fechado
Identifier DOI: 10.1016/j.future.2019.02.011
Address: https://www.sciencedirect.com/science/article/pii/S0167739X18304448
Date Issue: 2019
Appears in Collections:Cotil - Artigos e Outros Documentos
FT - Artigos e Outros Documentos

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