Big Data Archives

Informal learning experiences with big data visualisation

Written by

To enhance visitors’ experience, the CRE team recommend using easy-to-understand, well-designed data visualisations.

Professor Joe E Heimlich and his colleagues from the Center of Science and Industry, a science museum in Columbus, Ohio, USA, are investigating how we learn when we visit informal learning institutions such as museums and aquariums. This project involved a series of studies spanning eleven years that focus on visitors’ experiences of visualisations together with their learning behaviour and […]

The EUB SuperHub Online Platform: Towards a smart and sustainable construction future

Written by

The EUB SuperHub platform is an integrated cloud data hub for building information.

Imagine how much easier life would be with an online repository containing all relevant information about a building over its lifecycle while also connecting all stakeholders, from developers and contractors to tenants and maintenance teams. Moving from imagination to reality, Ahmed Khoja, senior researcher at Munich University of Applied Sciences, Germany, and Dr Marina Malinovec Puček, lead consultant at the […]

Using Artificial Intelligence to improve prediction and prevention of violence

Written by

Drs Gary Chaimowitz and Mini Mamak of McMaster University and St. Joseph’s Healthcare, Hamilton, Canada have developed the Electronic Hamilton Anatomy of Risk Management (eHARM) platform. It is an innovative risk assessment and management tool for violence and aggression which can be used in a variety of mental health areas, including but not limited to forensic psychiatry. The validity of […]

Understanding statistical significance of subgroups in the data science era

Written by

Statistical models are routinely used to derive inferences from large amounts of data. They directly impact several disciplines, including precision medicine and individualised learning, which rely on information concerning individuals and groups to make predictions on the expected effects of a specific intervention on population subgroups. Although it is relatively easy to find impressive-looking associations in big data, for instance […]

The Tommie Science Network: A high-speed network for high-level research

Written by

As science research projects increasingly focus on utilising ‘big data’, universities and research centres have needed to upgrade their research networks in order to facilitate the management and sharing of large and unwieldy datasets internally and externally. The University of St. Thomas, Minnesota has recognised this need, and Chief Information Officer and Vice President of Innovation & Technology Services Ed […]

Open-source bioinformatic solutions for ‘Big Data’ analysis

Written by

In this research article: Drs Griffin and Jagtap’s research focuses on the Galaxy-P project – developing, testing, optimising and applying multi-omics software tools to a variety of biological questions, including cancer and big data research.

Drs Tim Griffin and Pratik Jagtap along with the Galaxy-P team from the University of Minnesota are working to develop workflows on an open source platform for the analysis of multi-omic data. They are currently focusing on using a Galaxy-based framework to investigate the integration of genomic datasets with mass spectrometry-based ‘omics’ data. But in the long term, they aim […]

Biases from Big Data: the prejudiced computer

Written by

In this article Professor Nasraoui’s work focuses on Big Data. She examines how Machine Learning can lead to unreliable and biased models, problems around explainability and whether increased personalisation contributes to polarisation of opinions.

Big Data and Machine Learning seem to be the modern buzzword answers for every problem. Areas such as healthcare, fraud prevention and sales are just a few of the places that are thought to benefit from self-learning and improving machines that can be trained on huge datasets. However, how carefully do we scrutinise these algorithms and investigate possible biases that […]