Case study

Transforming the speed and efficiency of data analytics on huge scales

Groundbreaking data science research at the University of Derby is delivering both technical and economic benefits for major organisations such as CERN.

Researchers at the University of Derby have pioneered new ways of extracting information from massive datasets in real time – applying their expertise to everything from physics experiments at CERN’s Large Hadron Collider to railway maintenance and virtual reality solutions for engineering.

Distributed Data-Stream Analytics

The work is spearheaded by the University’s Data Science Research Centre which has harnessed Distributed Data-Stream Analytics (DDSA) to help a range of partner organisations to fine-tune and expand their own research or to develop new commercial products and services.

The DDSA solution can reduce both network bandwidth requirements and platform costs - making maximum use of the computing resources available so that networks can respond to tasks and queries in real time. It adds up to smarter decision-making for organisations, enabling them to gain minute-by-minute business insights, uncover hidden patterns in data, spot opportunities and risks, and boost their competitiveness.

Research collaborations

The full potential of these advances in data science has been showcased through a prestigious collaboration with CERN, the European Organisation for Nuclear Research, where the University has contributed its expertise in high-performance analytics to the A Large Ion Collider Experiment (ALICE) collaboration.

Research developments

The automatic analysis of complex data sets is a challenge for massive physics experiments of this kind but the team has successfully applied scalable machine learning and statistical models to the huge amounts of data that ALICE is producing. The new system will be used in the ALICE experiment when the large hadron collider resumes operation in 2021/2. Initial testing has shown an increase in the data acquisition rate from 2.5 GB per second to 4 TB per second. The final data output is expected to increase by a factor of 10,000.

Benefiting businesses

The University’s research in the field has brought equally significant benefits for SMEs working in diverse sectors. In a partnership with Bloc Digital, an agency which develops augmented and virtual reality (AR/VR) hardware for industrial applications, the team applied DDSA to produce high-performance real-time visualisations of engineering models. This process could see the cost of premium industrial AR and VR solutions reduce from £200k to around £35k.

Benefiting the rail industry

DDSA has also paved the way for innovation in the rail industry. The University has worked with rail companies to help them exploit the Internet of Things (IoT) and high-performance data analytics, extracting maximum value from the information they gather.

This has included a collaboration with Fishbone Solutions, an engineering and commercial consultancy for the transport sector, allowing them to improve their data analytics ecosystem through DDSA. It has led to more efficient predictive maintenance regimes for trains, reducing the amount of time operations have to be halted. As a result, Fishbone Solutions has been able to bring a new product suite of equipment monitoring systems to market.

Research results

For all its partner organisations, the University’s data science expertise has delivered minute-by-minute business and research insights, enabling them to uncover hidden patterns in data, spot opportunities and risks, boost efficiency and ultimately achieve smarter decision-making.

Funders

  • European Regional Development Fund (ERDF)
  • Innovate UK Knowledge Transfer Partnership
  • Science and Technology Facilities Council (STFC)

Researchers

  • Dr Bo Yuan, Lecturer in Computing (2019-2022)
  • Dr Lee Barnby, Associate Professor (2016-present)
  • Dr Leonardo Stella, Lecturer in Computing (2019-2021)
  • Professor Ashiq Anjum, Professor of Distributed Systems and Director of the Data Science Research Centre (2011-2020)
  • Professor Nikos Antonopoulos, Pro Vice-Chancellor, Research and Innovation, Dean of College of Engineering and Technology, Professor and Head of School of Computing and Mathematics (2009-2019)
  • Professor Richard Hill, Professor of Intelligent Systems and Head of Department, Electronics, Computing and Mathematics (2010-2017)

Research papers

A student looking through data

Data Science Research Centre

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