The Data Provenance Initiative audited 14,000 web domains to see how sites currently restrict scraping for the purpose of adding to AI datasets like C4, RefinedWeb, and Dolma. Sites are putting up more barriers:

Our longitudinal analyses show that in a single year (2023-2024) there has been a rapid crescendo of data restrictions from web sources, rendering ~5%+ of all tokens in C4, or 28%+ of the most actively maintained, critical sources in C4, fully restricted from use. For Terms of Service crawling restrictions, a full 45% of C4 is now restricted. If respected or enforced, these restrictions are rapidly biasing the diversity, freshness, and scaling laws for general-purpose AI systems. We hope to illustrate the emerging crisis in data consent, foreclosing much of the open web, not only for commercial AI, but non-commercial AI and academic purposes.

Bots used to be a welcome thing to see in your web analytics, because it meant that your site was indexed by a search engine. Real people could find your site. However, bots for the purpose of generative AI take everything and those who run sites don’t get much, if anything, in return. The decline in data availability seems warranted.

Aaron Koelker printed a six-foot long map on receipt printer earlier this year. He put it in a route sheet holder for more practical usage. Seems like a good end-of-world product, if you’re into that sort of thing.

Victoria Rose Richards uses embroidery to depict aerial views and landscapes. The above was inspired by a local creek:

I was once again directly inspired by my local landscape, copying the shape of the nearby estuary for this creek. Rather than an estuary though, I wanted to depict a receded river bed with dry mud and creeping plants starting to form across the base. Completed with grass, fresh crops and sprinkles of birds.

It’s one of two pieces still available in Richards’ shop.

Reuters, with illustrations by Catherine Tai, has visual guides to all of the Olympic sports. (Trampoline is tucked into the Gymnastics category in case you’re looking.) For each sport, there’s a schedule, a leading illustration, and a set of visuals that show you important moves or terminology.

It’s very good, especially for the sports you might not be familiar with.

Speaking of the Olympics, Alberto Cairo and Simon Rogers talked about the warm-blooded aspects of covering sports that make data more meaningful.

When approaching data visualisation for the Olympics, focus on the humanity of the games by integrating socio-economic, political, and historical stories alongside sports performance. Engage readers by placing them at the centre of visualisations, allowing interactive and fun experiences that reflect the current times and issues. Use handcrafted visuals for warmth and personality, and don’t hesitate to create your own datasets or collaborate with others to overcome data access challenges.

Everyone knows these athletes are the best in the world, but it’s the more human aspects of their stories that make the performances all the more unbelievable.

A part of outdoor sports is that you must deal with the weather, which is a challenge when it’s really hot and you have to run as fast as you can for a couple of hours. Bloomberg illustrates the challenges and how athletes might cope:

The harder the human body works, the hotter it gets. Roughly 80% of the energy generated by performing muscular exercises is released as heat, according to Mike Sawka, an environmental physiologist and professor at Georgia Tech. When external temperatures are cool, it’s easy for the body to dissipate that heat through thermal radiation and sweat. But when temperatures soar, and especially when it’s humid, the body struggles to keep up.

There’s a section that shows triathlete Kristian Blummenfelt’s core temperature against his skin temperature with two line charts during a race. Coupled with the annotation, the charts work well to show the attempts at keeping his body cool and the eventual heat stroke as his body hits its limit.

Here’s the good stuff for July.

We usually hear about fracking in a negative context, but for the Washington Post, Harry Stevens illustrates how a company aims to convert geothermal heat to usable electricity with zero emissions.

The New York Times collected drone footage and built a 3-D model to reconstruct the scene of the rally. They show four lines of sight: from the location of the gunman and three countersniper teams. You get a sense of distance and obstructions, which partially explain how the gunman could’ve been missed in surveillance.

Those who run cryptocurrency companies have much to gain from policies that favor them. Follow the Crypto by Molly White tracks the spending:

Cryptocurrency companies have raised hundreds of millions of dollars to put towards buying crypto-friendly politicians and ousting those who have spoken up for stricter regulations to protect consumers in an industry that is fraught with hacks, scams, and fraud. Although parts of the industry have tried to portray this as a grassroots effort, the reality is that a very small number of crypto companies, and the billionaire executives and venture capitalists behind them, are spending millions with a singular goal: to obtain favorable crypto policy, no matter the cost.

Like political contribution dashboards before it, the site uses data from the Federal Election Commission.

Nate Silver, who left Disney and the FiveThirtyEight brand last year but took his forecast models with him, is not a fan of the new models on 538, developed by G. Elliott Morris:

I thought the 538 model seemed basically reasonable when it was first published in June, showing the race as a toss-up. But its behavior since the debate — Biden has actually gained ground in their forecast over the past few weeks even though their polling average has moved toward Trump by 2 points! — raises a lot of questions. This may be by design — Morris seems to believe it’s too early to really look at the polls at all. But If my model was behaving like this, I’d be concerned.

Moreover, some of the internal workings of the model are strange, or at least appear that way based on the information Morris has made publicly available.

Silver has his own forecast. It currently places more weight on polls, which makes possible outcomes a lot less favorable for Joe Biden.

There’s much uncertainty around the election right now, so I wouldn’t lean on any forecast numbers at this point. But I like learning the thought process behind the models.

Like many, you’ve probably wondered what HTTP response headers are also area codes in the real world, or vice versa. Doug Sillars has you covered with HTTP Area Codes. This is very important.

The slider, a common UI element with a range and a handle that you can drag, has been around for a long time. It’s proven to be useful for visualization.

A lot of immigration talk in the U.S. focuses on Mexico, but immigrants come from other places, of course. Using immigration records from the past decade, the Washington Post provides a breakdown with a streamgraph and a series of maps.

The records come from the Department of Justice, which are released monthly via a FOIA request. (Sidenote: the download speed for this data seems super slow.)

It continues to grow more difficult for federal statistical agencies to accurately measure how the United States is doing. The American Statistical Association, in collaboration with George Mason University, released a report that highlights the challenges and possible solutions:

Our bottom-line assessment is that federal statistics are at risk. Federal statistical agencies have many strengths—economic indicators, such as the inflation rate, gasoline prices, and retail sales, roll out weekly, monthly, or quarterly on time and without fail; several agencies and OMB moved rapidly to produce timely, frequent data during Covid-19 on such topics as remote work and Covid-19 effects on health; and the 2020 Census was completed during the height of the pandemic. But the agencies face increasing challenges to their ability to innovate to the extent necessary to meet the nation’s detailed information and evidence requirements in the 21st century (e.g., for data on the economic effects of investments in infrastructure or of AI on work, education, and other sectors of society). The chief statistician’s office in OMB is under- resourced for its necessary functions to coordinate and lead a decentralized statistical system.

Using science fiction films as a proxy for what we see in our future, Alvin Chang, for the Pudding, examines the shift in settings, themes, and endings over the past eight decades. Pixel art adds depth to the data, which was partially derived via ChatGPT to categorize films over the years.

I always appreciate Chang’s connections between life and data. An analysis of sci-fi movies could easily get stuck at counts and percentages, but this gives a bit more.