BIGSEA : a big data analytics platform for public transportation information
Andy S. Alic, Jussara Almeida, Giovanni Aloisio, Nazareno Andrade, Nuno Antunes, Danilo Ardagna, Rosa M. Badia, Tania Basso, Ignacio Blanquer, Tarciso Braz, Andrey Brito, Donatello Elia, Sandro Fiore, Dorgival Guedes, Marco Lattuada, Daniele Lezzi, Matheus Maciel, Wagner Meira Jr, Demetrio Mestre,...
Andy S. Alic, Jussara Almeida, Giovanni Aloisio, Nazareno Andrade, Nuno Antunes, Danilo Ardagna, Rosa M. Badia, Tania Basso, Ignacio Blanquer, Tarciso Braz, Andrey Brito, Donatello Elia, Sandro Fiore, Dorgival Guedes, Marco Lattuada, Daniele Lezzi, Matheus Maciel, Wagner Meira Jr, Demetrio Mestre, Regina Moraes, Fabio Morais, Carlos Eduardo Pires, Nadia P. Kozievitch, Walter dos Santos, Paulo Silva, Marco Vieira
ARTIGO
Inglês
Agradecimentos: The work shown in this article has been funded jointly by the European Commission under the Cooperation Programme, Horizon 2020 grant agreement No 690116 (EUBra-BIGSEA) and the Ministério de Ciência, Tecnologia e Inovação (MCTI) from Brazil
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...
Ver mais
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/)
Ver menos
Fechado
BIGSEA : a big data analytics platform for public transportation information
Andy S. Alic, Jussara Almeida, Giovanni Aloisio, Nazareno Andrade, Nuno Antunes, Danilo Ardagna, Rosa M. Badia, Tania Basso, Ignacio Blanquer, Tarciso Braz, Andrey Brito, Donatello Elia, Sandro Fiore, Dorgival Guedes, Marco Lattuada, Daniele Lezzi, Matheus Maciel, Wagner Meira Jr, Demetrio Mestre,...
Andy S. Alic, Jussara Almeida, Giovanni Aloisio, Nazareno Andrade, Nuno Antunes, Danilo Ardagna, Rosa M. Badia, Tania Basso, Ignacio Blanquer, Tarciso Braz, Andrey Brito, Donatello Elia, Sandro Fiore, Dorgival Guedes, Marco Lattuada, Daniele Lezzi, Matheus Maciel, Wagner Meira Jr, Demetrio Mestre, Regina Moraes, Fabio Morais, Carlos Eduardo Pires, Nadia P. Kozievitch, Walter dos Santos, Paulo Silva, Marco Vieira
BIGSEA : a big data analytics platform for public transportation information
Andy S. Alic, Jussara Almeida, Giovanni Aloisio, Nazareno Andrade, Nuno Antunes, Danilo Ardagna, Rosa M. Badia, Tania Basso, Ignacio Blanquer, Tarciso Braz, Andrey Brito, Donatello Elia, Sandro Fiore, Dorgival Guedes, Marco Lattuada, Daniele Lezzi, Matheus Maciel, Wagner Meira Jr, Demetrio Mestre,...
Andy S. Alic, Jussara Almeida, Giovanni Aloisio, Nazareno Andrade, Nuno Antunes, Danilo Ardagna, Rosa M. Badia, Tania Basso, Ignacio Blanquer, Tarciso Braz, Andrey Brito, Donatello Elia, Sandro Fiore, Dorgival Guedes, Marco Lattuada, Daniele Lezzi, Matheus Maciel, Wagner Meira Jr, Demetrio Mestre, Regina Moraes, Fabio Morais, Carlos Eduardo Pires, Nadia P. Kozievitch, Walter dos Santos, Paulo Silva, Marco Vieira
Fontes
|
Future generation computer systems v. 96, p. 243-269, July 2019 |