Visualization Team

The rise of Big Data has provided researchers and industry with new opportunities to discover insight. One key tool for exploring and communicating data is data visualisation. While with the rise of tools such as Hadoop and Spark has enabled data processing to scaled to support the big data revolution data visualisation has not undergone a similar revolution. It is the goal of the Data Science Institute’s Visualisation team to visualise the Big Data revolution.

To enable visualisation to scale to support the Big Data revolution we designed and built the KPMG Data Observatory, an immersive data visualisation environment. The facility provides a social interdisciplinary environment which:
1) Enables researchers to make sense of Big Data
2) Supports quantitative decision making
3) Allows research into how decisions are made

Within the Visualisation Team we conduct three key types of research:
1) Tools and techniques to support the scalability of data visualisation to Big Data 
2) Explorative data-dense visualisation for exploring Big Data 
3) Presentation of research results 

We are very keen to collaborate with researchers and industry on all areas of our research and are always excited by data science problems where visualisation could help. Please do get in touch with David.Birch@imperial.ac.uk to explore opportunities.

Foundation of Data Science: Visualizing Data 

newsVisualisation is a critical part of the data science for two reasons. Firstly, the human visual system excels at pattern recognition and we are best able to make sense of big data sources through the visualisation of data and subsequent analytics. Secondly, once insight has been gained from data visualisation, visual representations of data as well as analysis results are typically the most effective means of communicating results.

The Institute has built a Global Data Observatory in partnership with KPMG. This consists of a visualisation studio allowing teams of researchers and analysts to collaborate in the exploration of data and the derivation of actionable insight in real time with a cutting edge visualisation environment.

 

Multidisciplinary Applications

Understanding Nature

In recent years, technological advances have dramatically increased the quality and quantity of data available to astronomers.  Newly launched or soon-to-be launched space-based telescopes are tailored to data-collection challenges associated with specific scientific goals. These instruments provide massive new surveys resulting in new catalogues containing terabytes of data, high resolution spectrograph and imaging across the electromagnetic spectrum, and incredibly detailed movies of dynamic and explosive processes in the solar atmosphere. These new data streams are helping scientists make impressive strides in our understanding of the physical universe, but at the same time are generating massive data-analytic and data-mining challenges for scientists who study them.

The Data Science Institute is working with researchers from the Imperial SpaceLab, and the Imperial Centre for Inference and Cosmology (ICIC), on utilising new technological advances in data science for their work.

We also have some current projects working on visualization of Mars and the stars, planets and galaxies in space!

 

Economics, finance and value

Some the visualization of data helps with the business and financial world to make the data more understable to a wider audience. Data in financial markets is constantly generated and quickly changing, where traditional statistical models quickly become out-of-date, and increasingly high performance real time machine learning algorithms that can adapt and change based on the new data are giving a new edge to trading. This is an active area of research where the DSI and Imperial College’s quantitative financial researchers are working together to make exciting progress. Beyond using data science for exploring competitive advantages in economies, new models for the economy itself are emerging.

For example, money itself is increasingly exchanged digitally, which brings new research questions such as: How to realise a new commercial structure with digital money? Does digital money adoption make a difference? What are the big data implications of digital money? Is it possible to quantify the benefits to governments, corporations and individuals? What are the factors that affect the outcome of a digital money initiative? Going beyond this, data itself could be considered a currency. At the DSI we are beginning to investigate new models for the digital economy as well as supporting data-driven research in economics and finance.