Course: Big Data and the Environment

Computer models can simulate the climate, producing predictions about temperature, rainfall and the probability of extreme weather events. The more models that are run, the more evidence we gather on …

Watch Dr Tom August, Computational Ecologist at the Biological Records Centre (BRC), highlight the value of volunteer contributions for monitoring and recording wildlife species in the UK. Tom introduces several …

The Earth Observation Applications department in Deimos Space UK develops systems and algorithms that derive information from satellite imagery. Watch Paula Marti explain how satellite data can be brought together …

In this video, Dr Jon Blower discusses a project which combined big and small, open and commercial data to investigate the areas around the Thames Estuary. He explains how access …

The Benefits Of Urban Nature To You (BOUNTY) was a visualisation project which aimed to improve decision making surrounding proposed, neighbourhood improvement projects. In this video, Barbara Percy, a software …

Professor Chen and Amos Golan, a Senior Associate, at Pembroke College, Oxford, identified four levels of visualisation in their 2015 paper ‘What may Visualisation Processes Optimize?’. This extract summarises the …

In an era of data deluge, the field of visualisation and visual analytics provides us with technologies and tools that can be used to support data intelligence in a wide …

So far you’ve focused on big data and the vast computing resources needed to store and process it, but small data is just as important. This article investigates four different …

In 2012, Harvard Business Review caused a splash by labelling data scientist as the sexiest job of the 21st Century. Data science has continued to be an emerging profession and …

How do you become a data scientist? Watch Tom Pinder, a graduate from the University of Reading who interned at the IEA, highlight his journey into data science. As you’ve …

Listen to IEA Data Scientist, Dr Ben Lloyd-Hughes, on the seven phases of a data science project. These are: 1. Problem Statement 2. Data Acquisition 3. Data Preparation 4. Data …

As you’ve worked through this course and watched industry experts discuss their big data projects, you’ve heard about many of the challenges when working with big data. Watch Dr Jon …

Watch Dr Debbie Clifford explain how open data from satellites, which monitor the Earth, can help us to understand the effect we’re having on our climate. A wide variety of …

Watch David Wallom, Associate Professor at Oxford e-Research Centre, explain the philosophy behind open data and how it can be applied to research. Are you aware of any projects which …

It’s important that you collect and use any data ethically. The project discussed in the previous Steps used ACORN groups for classification. A Classification Of Residential Neighbourhoods (ACORN) is a …