EUROPE - BRAZIL COLLABORATION OF BIG DATA SCIENTIFIC RESEARCH THROUGH CLOUD-CENTRIC APPLICATIONS

EUROPE - BRAZIL COLLABORATION OF BIG DATA SCIENTIFIC RESEARCH THROUGH CLOUD-CENTRIC APPLICATIONS

Project Vision

EUBra-BIGSEA is a project funded in the third coordinated call Europe – Brazil focused on the development of advanced QoS services for Big Data applications, demonstrated in the scope of the Massive Connected Societies.


The exponential increase of the available Open Data and the affordability of cloud computing resources are an excellent opportunity for the democratisation of Data analysis. However, the development of Data Analytic applications in the cloud is a complex task that faces essential challenges such as the Quality of Service and the minimisation of privacy risks, requiring high-level technical skills.

EUBra-BIGSEA developed a framework, a platform and a library to ease the development of highly-scalable, privacy-aware data analytic applications running on top of Quality of Service cloud infrastructures, reducing development cycles and deployment costs. While EUBra-BIGSEA targets Data Scientists in general in the context of the project timeline it has been demonstrated implementing a set of applications for analysing data transportation data, aiming at improving urban transportation users experience.

EUBra-BIGSEA has developed a Big Data application development framework that comprises three primary assets that are not available in the market:

The software is available in the project GitHub (https://github.com/eubr-bigsea) and DockerHub (https://hub.docker.com/u/eubrabigsea/), as well as in the EUBra-BIGSEA website (http://www.eubra-bigsea.eu) along with papers and presentations. Video demos are available on the youtube channel of the project (https://goo.gl/FTCq3g).

The work has required the collaboration of European and Brazilian experts combining their expertise on data analysis, application performance modelling, privacy management, data analytics, parallel processing and cloud services.