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.
Of broad interest, but not fitting the categories below – “In November and December 2021, the European Journalism Centre surveyed over 1500 people involved in data journalism worldwide in what they believe is the biggest effort to measure the state of data journalism to date. The results provide an excellent overview of the various aspects of the field: the community’s demographics, the skills and tools, and the impact of the pandemic”. You can find The State of Data Journalism 2021 here.
Series 2 of my “Six Questions” finished last week. I’ve now published interviews with 34 data folks who have been inspiring others with their work. With that, the newsletter takes a few week’s break while I reassemble the interviews for Series 3 and take a short holiday.
See you on March 22nd.
‘till next week,
Giuseppe @puntofisso
This week’s edition is sponsored by OpenCage
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Lisa Charlotte Muth at Datawrapper has published a very useful Twitter thread of all maps about the war published by the media.
I’d have assumed the Swiss would be better than this.
An interesting animated dataviz which is a good opportunity to remind you of the existence of the brilliant electricitymap.org/, which is the source for the chart.
(via Guy Lipman)
To be taken with a pinch of salt, as the misconfigured Google Map is not a great sign, but this map by the Georgian Foundation for Strategic and International Studies could be useful to understand the current war. Conversely, it might be a good starting point for a discussion about trust and information.
I don’t have access to the article that shows this animated speedskating animation, but luckily Der Spiegel has released its source code.
A web application (limited access) and its source code to detect hate speech against women in several languages, made by the LSE’s Polis/JournalismAI project.
“Whether to break an axis—the practice of starting a numerical chart scale at a number other than zero—is one of the most contentious topics in data visualisation”, and The Economist explains when and how they’d do it in their latest Off The Charts newsletter.
World Atlas is a website “incorporating over 2,500 datasets for you to explore. With over 12 million data points spanning 100 categories, find a dataset that interests you and analyse it using a suite of interactive charts. All data is fully sourced and available for download. It’s designed to be easy to use and fun to learn. Let me show you what I mean”, the developer who set it up explains in this blog post.
“Here’s how you can order up a high-resolution image of any place on Earth”, and much more.
Another good piece of dataviz thinking by Lisa Charlotte Muth, with a good set of tips and practical examples.
“We believe that there is great potential in using AI tools to create more compassionate, inclusive - and yes, loving - journalism, and we hope that this resource will contribute to such a future. […] Through the LSE JournalismAI Collab, we - representatives from eight major news organisations across the world - have together explored a big challenge: How might we leverage the power of AI to understand, identify and mitigate newsroom biases?“
“Here we share what we can learn from long-run patterns on Lyft’s operations in major US cities”, says Lyft’s data scientist Mark Huberty.
This data analysis asks an intriguing lateral question: how can we estimate the number of lost books? And it answers it by using the techniques used by paleozoologists to calculate the number of lost species.
“A visual essay about the (mis)representation of women in the news”, by Leonardo Nicoletti and Sahiti Sarva for The Pudding.
[]”Not only is it one of the first isochronic maps (marking distances that could be traveled in the same time) but it drew on steamship tables, post office records, and private voyage records.”](https://twitter.com/emollick/status/1479679442662346753) The Twitter thread also links to documents explaining how the map was made.
(via Davide Tassinari)
Interesting animation and linked academic paper.
(via Christ Weston)
“An examination of translating text to make it as accessible as possible.“
Interestingly for The Pudding, not quite a dataviz.
Some innovations described here, suggest that AI could alert drivers of an imminent collision. The question, for me, is: what do you do with that information that does not result in an increased accident rate caused by sudden braking?
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