447: quantum of sollazzo
#447: quantum of sollazzo – 22 November 2021
The data newsletter by @puntofisso.
Hello, regular readers and welcome new ones :) This is Quantum of Sollazzo, the newsletter about all things data. I am Giuseppe Sollazzo, or @puntofisso. I’ve been sending this newsletter since 2012 to be a summary of all the articles with or about data that captured my attention over the previous week. The newsletter is and will always (well, for as long as I can keep going!) be free, but you’re welcome to become a friend via the links below.
Every week I include a six-question interview with an inspiring data person. This week, I speak with Florent Daudens of Le Devoir, a French-language Canadian newspaper which is widely respected for its brilliant approach to interactive data-driven journalism.
The Prepared is a newsletter about physical engineering. This week we interviewed robot ethicist Dr. Kate Darling, author of The New Breed, a book that pushes back against fears that robots will automate human jobs and replace friendships. Subscribe for free here!
There’s a pretty good job opening going at The Guardian, where Ashley Kirk is looking for a Graphics Editor to lead their daily news production team. You can read the job description and apply here
A final shout out to DataJournalism.com’s State of Data Journalism 2021 survey, which many of you might be interested in contributing to: What is the most difficult part of being a data journalist? What tools are currently being used, and how are they perceived by data journalists who use them? How much does the role vary across the globe? Let us know in the survey! The survey offers some very special rewards, including the chance to win a trip to the International Journalism Festival 2022 in Perugia, as well as Amazon Coupons and Digital Goodies.
‘till next week,
Giuseppe @puntofisso
Six questions to...
Florent Daudens
Florent is News Director at Le Devoir.
What is your daily data work like and what tools do you use?
Datavisualization is one of the pillars of our editorial strategy, and we define it in two main tracks:
- On a daily basis, to find visual leads in data or to put a story in context.
- With bigger scale projects based on exclusive data or in-depth explainers.
I think it is also important to democratize data in the newsroom, and we are lucky to count on several journalists interested by datavisualization capacities and curious to use the tools we provide them!
For our daily production, we juggled with different tools, even homemade chart tools, but finally decided to adopt DataWrapper, since they were able to configure the layouts with our graphical guidelines (even for print) and its easy-of-use interface. With Google Sheets, it is our go-to toolset.
For bigger projects, we look to various tools such as Pandas, Plotly and D3.js, but also Mapbox for cartographic projects. And we always try to build scalable projects, in order to avoid to start from scratch each time.
Tell me about a data project that you're proud of...
Allow me to cheat a little bit, but it’s election time in Canada (aka Christmas for data journalists!), and even if it was called early, we were able to release a series of captivating data projects:
- Live 2021 election results and maps
- Compare parties promises
- Where will the election be winned?
- Draw yourself the Trudeau government’s record
- Revisit the House of Commons after its dissolution
...and a data project that someone else did and you're jealous of.
Difficult to choose, but I especially liked this project from the Washington Post: Where America’s developed areas are growing: ‘Way off into the horizon’ . Sometimes, the map is the territory. This story takes interesting data released by the USGS and does a great job at explaining the causes of this development (housing costs, fracking boom, etc), and the environmental impacts of it.
Also, a great example of data without complicated visualizations is this investigation of the NYT showing different prices charged by hospitals to patients and insurers for the same basic services.
If I say "dataset", you think of...
A potential gold mine / headache.
Give someone new to data a tip or lesson you wish you'd learned earlier.
It is not because you have big datasets that you have to expose them all to your readers and that it is interesting (I plead guilty on these two charges!). Sometimes, a 1-million-rows file will only give you one bar chart, and it can be ok. You really have to think about the informative value of your data, and how to explain your story in the most comprehensive way to your readers.
Data is or data are...
In French, we say « les données », therefore I will go with data are ;)
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Topical
John Burn-Murdoch’s COVID charts series
This chart on the ratio of acute metrics to COVID cases is one of the best I’ve seen in months, but the whole thread contains some very useful graphics to digest.
According to Twitter, Twitter’s algorithm favours conservatives
The Economist captures visually what Twitter seems to be admitting about its algorithms.
Queer stories of violence in Berlin
“In the map below, you can see 373 stories of violence towards the queer community in Berlin, collected over the last seven years. The data comes from the Berlin Register, a website that tracks discriminatory incidents and right-wing extremists.“
This is by Rebecca Mary Peake, a junior software developer at Datawrapper.
A Race to Adapt: The Climate Crisis in the Sahel
The United Nations’ OCHA Centre for Humanitarian Data has published this incredibly visual story about “a Chadian girl’s daily journey to collect water [which] illustrates how the climate crisis is affecting her community”, with links to the data.
Tools & Tutorials
Parsehub
Parsehub is a web scraper SaaS with a relatively generous free tier.
Introducing a Novel Very High-Resolution Dataset of Landfills and Waste Dumps
“A novel dataset consisting of very high resolution multi-spectral satellite images of landfills from Germany, Hungary, Serbia, India and Brazil”, with this blog post describing which steps and datasets the author used to create it.
Data thinking
How we plotted a journey through space
The Economist’s data team explains in their Off The Charts newsletter the approach they took to visualising the 12-year journey of Lucy, a space probe that visited eight different asteroids.
Dataviz & Interactive
How has Cop26 shifted the dial on the climate crisis? A visual guide
Useful visual summary by The Guardian, using data from Climate Action Tracker and the World Bank.
AI
Explaining Machine Learning Models: A Non-Technical Guide to Interpreting SHAP Analyses
“With interpretability becoming an increasingly important requirement for machine learning projects, there’s a growing need for the complex outputs of techniques such as SHAP to be communicated to non-technical stakeholders.“
Data scientist Aidan Cooper explains SHAP in practical terms and discusses what it can be used for.
How Much Women and Men Work
“Over the years, more women have entered the workforce while the percentage of men has gone down slightly. The chart below shows the shifts since 1960.“
As per usual approach, Nathan at FlowingData also shares links to the data and methodology.
Random
The food timeline
The food timeline is a website that was started in 1999. Its last update dates back to 2021, but I suppose that its UI never changed since the beginning… Jokes aside, its contents are way more interesting.
quantum of sollazzo is also supported by ProofRed’s excellent proofreading service. If you need high-quality copy editing or proofreading, head to http://proofred.co.uk. Oh, they also make really good explainer videos.
