Exploiting “Big Data” is a prominent part of Europe’s digital agenda for targeting innovation in information products, services, business intelligence, health, logistics, manufacturing, environment, and many other sectors. Future knowledge-based economies rely on the added value of advanced analytics of Big Data in order to increase efficiency, reduce costs and speed up innovation.
To meet this need, Bournemouth University (BU) is working with partners in Spain, Germany and the UK on a new project – PROTEUS – which is designed to address fundamental scientific challenges related to the scalability and responsiveness of analytics capabilities. As a result, the team will develop an enhanced version of Apache Flink, the European Big Data platform.
Project lead, Dr Hamid Bouchachia explains the project in more detail: “Specifically, PROTEUS will investigate and develop ready-to-use scalable online machine learning algorithms and real-time interactive visual analytics to deal with extremely large data sets and data streams.
PROTEUS will contribute to the improvement of the Apache Flink platform by accommodating batch and streaming processing to better fit scalable real-time processes. The developed algorithms will be integrated as a machine learning library to be part of an enhanced version of the platform.”
The requirements of the project were inspired and motivated by an industrial use case supplied by the world leading steelmaker, ArcelorMittal. The techniques to be developed in the context of PROTEUS are however, general, flexible and portable to any industry characterised by high-speed big data streams.
Bournemouth University will be leading on the development of real-time, scalable machine learning for massive, high-velocity and complex data stream analysis. BU will also be contributing to PROTEUS’ work around the implementation of the new algorithms for Apache Flink and real world application of PROTEUS’ outcomes in industry.
What will be the impact of PROTEUS?
“It will have a strategic impact as it will reduce our knowledge gap and dependence on US technology by further developing our own European platforms,” explains Dr Bouchachia. “We will be developing original hybrid and streaming analytic architectures which will enable scalable online machine learning strategies and advanced interactive visulisation techniques. We hope these will also be adaptable to other industries and contexts.
“We believe the project will have an economic impact as the effective use of big data will help to reduce production costs in a variety of industries,” continued Dr Bouchachia. “We also hope it will lead to the development of new skills and new jobs through the creation of new technologies to support industry.
By working with our industry partners throughout the project, we will be taking into account real-world requirements and validating our end results by applying them in an industrial context.”