Four Great Articles on Dataviz I’ve Read Recently
Data visualization, in all its forms, is a complex craft. When creating a dataviz, one can be so absorbed by cleaning the dataset and working out the technical challenges, that it is easy to lose grasp of the big picture. Sometimes it is good to take a step back, and read about general principles in data visualization, different points of view and ongoing discussions in the field. This kind of readings helps data visualization designers to feed their work with new ideas and a fresh critical look.
The good news is, this type of content is more and more accessible online: video recordings of past conferences are made available on Youtube, several podcasts are now specialized on the topic, and great articles are regularly published on blogs like the one on Datawrapper’s website, on Nightingale (the journal of the Data Visualization Society), on Tableau Research website, and on other publications on Medium (UX Collective and Towards Data Science are among my favourites).
Here are four great pieces on data visualization I’ve read recently.
“Towards a Theory of Bullshit Visualization”
by Michael Correll
It is not common to find articles that are at the same time as rich and well-documented, and as hilarious as this paper by Michael Correll, Senior Staff at Tableau Research.
What Michael calls “bullshit visualizations” are not simple illegible or deceptive charts, they go far beyond that: they are “charts that do not have even the common decency to intentionally lie but are totally unconcerned about the state of the world or any practical utility”.
Seasoned jedi or young padawan, when it comes to bullshit charts, we all have our fair share of guilt to confess. Making the reader aware of this fact is probably the most important takeaway of this fantastic paper.
Also, thanks to this article, I discovered the existence of a Tableau Research portal, full of very interesting readings. A pity, though, that the papers are not available in a more shareable format than pdf (Tableau people, if any of you are reading this…)
“In defense of simple charts”
by Lisa Charlotte Muth
In this article, the talented blog writer at Datawrapper Lisa Charlotte Muth argues against the popular idea that “simple charts are boring”.
“That’s not the shortcoming of the chart type, but the shortcoming of the designer”, she replies. Her recipe to make the most out of simple charts: combining interesting data and good design.
“Data Visualization Has a Taxonomy Problem”
by Elijah Meeks
In this article beautifully illustrated by Hajra Meeks, Elijah Meeks takes the conversation about chart types a step further and challenges the idea itself of a chart taxonomy.
“Charts are a bad unit of measurement of data visualization” the author argues. Thinking in terms of chart taxonomies creates unnecessary constraints for designers and users. Instead, data visualization should be thought of as a mix of smaller components, including annotations and style elements.
I couldn’t agree more with the ideas stated in this article. In my opinion, this is a particularly useful read for those who’ve already taken their first steps in the field and now want to enrich their perspective, unleash their creativity and go beyond a beginner’s approach.
“Unmaking the Nonprofit Data Mess”
by Genevieve Smith
In this piece, Geneviève Smith shares her “Data Ecosystem Diagnostic” framework to better understand and improve data use in NGOs and nonprofits in general.
In a nonprofit organization, data collection and analysis should support the mission. But data do not live alone, they are part of an ecosystem, together with the internal culture, processes, tools and people, at many levels: organizational, governmental, social, etc.
A very good read I would advise to all those working in nonprofits.
