Patterns in data

In recent years, phrases like ‘big data’, ‘machine learning’, ‘algorithms’ and ‘pattern recognition’ have started slipping into everyday discussion. We’ve worked with researchers and experts to generate an open and informed public discussion on patterns in data across a wide range of projects.

Data Science: A guide for society

According to the headlines, we’re in the middle of a ‘data revolution: large, detailed datasets and complex algorithms allow us to make predictions on anything from who will win the league to who is likely to commit a crime. Our ability to question the quality of evidence – as the public, journalists, politicians or decision makers – needs to be expanded to meet this. To know the questions to ask and how to press for clarity about the strengths and weaknesses of using analysis from data models to make decisions. This is a guide to having more of those conversations, regardless of how much you don’t know about data science. To view the guide click here

Algorithms in decision-making

The House of Commons science and technology committee launched an inquiry into ‘Algorithms in decision-making’ following a fantastic pitch from our policy manager Dr Stephanie MathisenAlgorithms . As Steph argues, algorithms — quite rapidly and without debate — have come to replace humans in making decisions that affect many aspects of our lives, from criminal justice to education. in themselves are neither ‘good’ nor ‘bad’, but where the public has little access to information about the workings of algorithms in decision-making, there is a serious lack of transparency and therefore accountability and choice. We look forward to the committee’s report in 2018.


In 2016 AllTrials launched an automated clinical trial tracker, that identified who is and isn’t publishing their trials. The tracker uses data from the largest clinical trial register,, and is clear and open about the data and methodology used to identify missing trials. It is also automatically updated when trials are added to the register.

Understanding Children's Heart Surgery Outcomes

Understanding Children’s Heart Surgery Outcomes publishes the results of survival data from different surgical units in the UK and Ireland in a way that allows parents, patients, regulators and doctors to see and understand what it means. This public engagement partnership put the raw data into the context of why a hospital’s survival rate for children’s heart surgery needs to take into account how severely ill their patients were. We took a good look at all the voices, questions and concerns in public discussion about children’s heart surgery, created and user-tested a website to ‘speak’ to those discussions. The website development was part of a project funded by the NIHR, led by Dr Christina Pagel, a mathematician from University College London.

The UK Longevity Explorer (UbbLE)

A public-facing website that generates the risk of mortality for an individual based on a series of questions. The research behind the risk calculator and association explorer from the website used data from the UK Biobank which included measurements from over half a million UK volunteers. Our role was to enable the public to use the findings of the research, and to convey the risks, using clear visuals. The project was a collaboration with Professor Erik Ingelsson, Uppsala University, Sweden and Dr Andrea Ganna, Karolinska Institutet, Sweden who funded the project.

Environment and Health Atlas

A partnership with the Small Area Health Statistics Unit (SAHSU) – the Atlas maps potential environmental agents and a range of diseases across the UK over a 25-year period. SAHSU pulled together data from the Office of National Statistics, Met Office, water companies and others to create an atlas that can be a tool for the public, policymakers and researchers. When working on the project and during the launch, we made sure to be just as clear about what these maps could not be used to infer.

Making Sense of Statistics

A guide to what statistics tell you and how to ask the right questions. Statistics are used to measure and make sense of the world and often crop up in headlines and news stories on any number of topics. This guide is not a lesson in statistics. It provides the questions to ask – how has the data been collected for example, and identifies the pitfalls to avoid to help you get behind news stories that use statistics. A collaboration with Straight Statistics (now part of Full Fact) and the Royal Statistical Society.

Published: 19 December 2017