Our pandemic lives are deeply entwined with data visualizations. From instructional hand-washing infographics, to calls to ‘flatten the curve,’ data visualisations are telling us how to live, and predicting our possible futures. As the cascade of open data relating to the COVID-19 virus grows, so too do the charts and graphs claiming to decipher, decode, and translate this data for everyday understanding.
In response to this data visualisation of our everyday lives, designers and data storytellers are working hard to fight graphics that represent ‘fake news’ and educate journalists, analysts and commentators to create better data visualisations.
We created this webcomic to share some of their work and help empower audiences to better understand the COVID-19 data visualisations that now fill our everyday lives.
Thank you so much for reading! This is a living webcomic so please feel free to send feedback and ideas.
Get in touch with Alex at firstname.lastname@example.org Alex is a PhD candidate in Graphic Medicine and research illustrator. Or Anna at email@example.com Anna is an Associate Professor in digital storytelling and co-author of The Data Storytelling Workbook (Routledge 2020)
FURTHER READING AND SOURCES:
What’s a Numerator and Denominator?
What’s the Problem?
How rates will affect the UK lockdown: https://news.sky.com/story/coronavirus-the-four-factors-that-will-decide-when-the-uks-lockdown-can-end-11969844
Bring Us Denominators!
Randy Au’s work on data literacy: https://towardsdatascience.com/data-literacy-via-covid-19-38965538f390
What’s in a Numerator?
Behind Italy’s death rate: https://www.telegraph.co.uk/global-health/science-and-disease/have-many-coronavirus-patients-died-italy/
BBC postcode and COVID-19 map: https://www.bbc.co.uk/news/uk-51768274
Coronavirus and male risk (Philip Ball): https://www.theguardian.com/commentisfree/2020/apr/07/coronavirus-hits-men-harder-evidence-risk
Communication themes and COVID-19 (Andy Kirk): https://www.visualisingdata.com/2020/03/communication-themes-from-coronavirus-outbreak/
Gender data gaps (WHO): https://www.who.int/activities/closing-data-gaps-in-gender
Why Population Size Matters
Calling out COVID-19 misinformation: https://www.wired.com/story/professors-call-bullshit-covid-19-misinformation/
Data Feminism book (D’Ignazio): https://www.amazon.com/Feminism-Strong-Ideas-Catherine-DIgnazio/dp/0262044005
CDC US cases update: https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/cases-in-us.html
Using Data Visualisation to Dramatise the Pandemic
Deconstructing COVID-19 data viz (Andy Cotgreave): https://gravyanecdote.com/visual-analytics/coronavirus-be-wary-how-we-visualise-data/
Responsible data vis (Kenneth Field): https://www.esri.com/arcgis-blog/products/product/mapping/mapping-coronavirus-responsibly/
Projections Are Not an Exact Science
Projections and COVID-19 spread (Angus Loten): https://www.wsj.com/articles/scientists-crunch-data-to-predict-how-many-people-will-get-coronavirus-11584479851
Models and projections (Zeynep Tufekci): https://www.theatlantic.com/technology/archive/2020/04/coronavirus-models-arent-supposed-be-right/609271/
Simulation Shock graph source: https://www.nature.com/articles/d41586-020-01003-6