Introduction

A Turing Data Story is an interactive mix of narrative, code, and visuals that derives insight from real world open data. They are written as pedagogic Jupyter notebooks that aim to spark curiosity and motivate more people to play with data.

Our project lives in Github in this repo.

The stories are published online and you can check them out here.
 

Project aims

Our aim is to help people understand the data driven world around us. We want to inspire an open community around a central platform. One that encourages people to harness the potential of open data by creating 'data stories'.

These 'data stories' mix computer code, narrative, visuals and real world data to document an insightful result. They should be educational and relate to society in a way that people care about. They must maintain a high standard of openness and reproducibility and be approved by the community in a peer review process. The stories will develop data literacy and critical thinking in the general readership.

Recent updates

Recent stories

  • When will the United Kingdom be fully vaccinated against COVID-19? By May 2021 the United Kingdom had fully vaccinated one third of the adult population. Based on the progress so far, we estimate when the whole population will be vaccinated. Published on May 2021.
  • Modelling mail-in votes in the 2020 US Election: Using hierarchical Bayesian modelling to predict outcomes and associated uncertainties in the 2020 US election. Published on February 2021.
  • Who was protected by the first COVID-19 lockdown in England?: A look at social deprivation and mortality rates across England during the first wave of the COVID-19 pandemic. Published on November 2020.

How to get involved

This project is ongoing and everyone is encouraged to help us build something that will be useful to many. There are several ways you can help:

Story ideas: Have an idea for an interesting story that could be told if you had the data, or knew how to analyse it? We can help.

Data: Stumbled across an interesting dataset, or perhaps mashed together several sources of data yourself? We want to hear about it.

Code: Are you an expert in Bayesian analysis? Do you have good data visualisation skills? Put that knowledge to work!

Peer review: Know a bit about data analysis? Good at communicating that knowledge? Interested in learning about how it can be applied to understanding society? We need reviews to make sure our stories are the best they can be.

Communication: Are you an amazing writer? Help us tell better stories.

Community: Don't fit in any of the above categories, but still want to hang out and be involved? We've got you, drop us a line.

Organisers

Researchers and collaborators

Contact info

Camila Rangel Smith
[email protected]