#413: quantum of sollazzo – 16 March 2021
The data newsletter by @puntofisso.
Last week we celebrated Open Data Day 2021. In the last few years, the day has reflected upon the Open Data movement and its achievements, noting that the strong impetus for transparency and machine readable data that characterised the late noughties and early 2010s has been replaced by a somewhat negative vibe.
We have open data portals with thousands of unusable datasets, the data versioning isn’t appropriately managed in 99% of those, and what’s worse is that there are few success stories built around open data. And yet, 2021 is the year in which everyone seems to understand how good, timely, structured, high quality data that is linked to real-life processes can be a matter of life and death. COVID-19 has produced an understanding that data matters more than ever, not through empty words about digital twins, but by offering a real chance of monitoring and informing what’s happening out there in the real world.
Alex Blandford offers a short but spot-on reading on Open Data Day. He writes: “User needs are a slightly/massively reductive way of viewing the world, but in terms of open data, the “so that” is always missing. Armchair auditors never appeared in the wake of open data release and civil society’s oft repeated call of “holding government to account” rings hollow as there basically isn’t any mechanism to do this. Making yet another website that shows the government is performing like shit is having no impact. So, as a community, we need to articulate what we need data for and how we can use it for purposes that are emancipatory and impactful, rather than just another map.”
And so I find myself flirting the idea of an upside down government data portal. Let’s start with ordinary problems, and then identify the data that we need, the structure that it needs to have, the frequency of updates, and the governance around it. Doing this by marking the data flows and whether the data exists or not in some form, will enable campaigners to focus on creating solid processes (including by enshrining them in specific legislation, if and when required). Missing Numbers by Anna Powell-Smith has done quite a bit to highlight the data that should be there in order to look at a problem. Do you think there is a fundamental flawed approach in a problem-first view of data publication? I’m curious to hear your views.
Till next week,
Bats and the origins of outbreaks
“As the World Health Organization reaches its findings on the zoonotic origins of the novel coronavirus, we explain why bats make such ideal hosts for disease-causing viruses.”
A brilliantly visualized (I could say “illuminated”) article by Reuters Graphics.
The Data Visualizations Behind COVID-19 Skepticism
Data is great, data is useful. However, it is also, sadly, prone to be misused, as shown by this MIT study.
*”We studied half a million tweets, over 41,000 visualizations, and spent six months lurking in anti-mask Facebook groups.”
Tools, Tutorials, and Datasets
“A collection of queries to help you use the OpenStreetMap Overpass API”.
Launched by Leigh Dodds in this blog post, OSM Queries is a collection of ready-to-use queries and tutorials to extract data from OpenStreetMap.
The Human Screenome Project
Stanford University has launched this interesting project that aims to understand what people really see on their screens: “no one really knows what people actually see and do on their screens in an increasingly complex digital world”.
It allows users to record screens at regular intervals, with their activity being consequently tagged and classified.
(via the Dataninja newsletter)
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A semi-comedic take at the Pentagon’s recent release of UFO sighting reports.
“So, in need of a little comic relief from the monotony of lockdown life, we decided to comb through the new material and see what the data might reveal! Some entries were incredibly detailed, including close descriptions of each UFO’s design, brightness, and speed. Some seemed more offhand, or vague. All of them were weird.“
Radical Dots Simulator
“Visualizing extreme belief formation, echo chambers, polarization, and attitude latitudes”.
Does speaking to people with different beliefs allow them to reconsider, or does it radicalise them? This blog post by Eli Holder on the Nightingale journal and interactive tool look at the issue.
A useful collection of tools, put together by the Society of Professional Journalists.
It has been around since 2008 and gets frequently updated with thousands of mostly free resources.
Encode Mighty Things
I was really expecting this.
Making an animated data visualisation/sonification with After Effects
Last week’s Quantum of Sollazzo covered this brilliant data sonivisualisation by Jamie Whyte. He’s now written a useful how-to.
Dataviz, & Geo/Maps
Bats in Amsterdam
Ok, this is the second article about bats in this newsletter, which isn’t overly politically correct in the time of pandemic.... but apparently the City of Amsterdam has an open dataset of bats and I think this is marvellous.
(via Jeremy Singer-Vine’s utterly fantastic newsletter, which you will like if you like mine)
The Shortest Route Between All the Pubs in the UK
Plotting out the world’s longest pub crawl had a serious, mathematical point.
This quest started a long time ago, and this is a 4 year old article, but it’s pretty good.
(via Richard Potts)
Experience the power of a nuclear blast in your area
I’ve seen similar maps before, but this one is pretty refined from a visual point of view. Cheerful in a pandemic year.
Two parts of a pandemic: How the coronavirus spread in Canada
“A new surge in coronavirus cases has seen year-end gatherings prohibited for the majority of Canadians. See how this surge in cases compares to the spread earlier this year. Scroll to the end to get numbers for your area and compare where you live to the rest of the country.“
Really good visual and interactive scrollytelling article by Naël Shiab and colleagues of Radio Canada. The “spike maps” return.
(via Elena Ferranti)
“This section attempts to provide an unbiased and objective ground for helping visitors to independently assess the magnitude of Bitcoin’s electricity consumption and compare it to other uses of electricity.“
The University of Cambridge’s Centre for Alternativce Finance has developed a Bitcoin Electricity Consumption Index; here, it uses it to compare countries of the world to what Bitcoin is like in terms of production/consumption of energy.
At the time of writing, “The amount of electricity used annually by the Bitcoin network could satisfy the energy needs of the University of Cambridge for 727 years”.
Pay up or put it off: how Europe treats depression and anxiety
“In many European countries, the availability of psychological treatment in the public healthcare system is inadequate or even non-existent. Barriers such as long waiting lists, co-payments and inadequate resources push people with anxiety or depression – those who can afford it – to the private system.”
An excellent if sad analysis and visualization from the European Data Journalism Network.
We Failed to Set Up a Data Catalog 3x. Here’s Why.
We thought it would be easy enough to figure this out, but we couldn’t have been more wrong.
This article by Prukalpa Sankar resonates a lot with a few discussions I’ve had over the years.
The SIC note. Why the UK needs to overhaul its industrial classification system
“It is a well known, but little talked about, problem that the way that businesses in the UK are classified is fundamentally broken. “
The smart folks at The Data City suggest a Real Time solution.
Traffic congestion dropped by 73 percent in 2020 due to the pandemic
The most interesting aspect of this data analysis from Ars Technica, as Charles Arthure notes in his newsletter, is that if you compare the US and the UK, both countries had obvious drops in traffic; what’s less obvious and worth analysing in more depth is that this resulted in more accidents in the US, while accidents in the UK decreased.
Draw streets, visually.
A real heatmap
Hendrik at Datawrapper writes about thermal images: “Thermal imaging is basically a special case of heatmap visualization.“
How the New York Times A/B tests their headlines
“Part 1 of a series on the New York Times, in which I take a close look at how (and when) the New York Times tests multiple headlines for a single article.”
Keep an eye on the series.
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