Dave stops feeding his site’s visitors data to Google. I wish more people (and companies) would join him.
There’s also an empowering #indieweb feeling about owning your analytics too. I pay for the server my analytics collector runs on. It’s on my own subdomain. It’s mine.
Oodles and oodles of data on cities, including gorgeous animations of urban growth over time.
Some lovely data visualisation by Brendan:
The work features three main components — the threats, represented by black obelisk style objects, the system which detects and deals with these threats, represented by an organic mesh like structure, and finally the creativity that is allowed to flow because the threats have been neutralised.
This is a nifty visualisation by Hui Jing. It’s really handy to have elements categorised like this:
Chris has made sonic sparklines on his site too, but they’re far more musical than mine. Here’s his explanation of how he did it.
Rob has turned his exhaustive spreadsheet of all the concerts he has attended into a beautiful website. Browse around—it’s really quite lovely!
Rob’s also writing about the making of the site over on his blog.
Hui Jing runs through a whole bunch of options for displaying responsive tables, some of them using just CSS, some of them using a smidgen of JavaScript. There are some really clever techniques in here.
Raw data is both an oxymoron and a bad idea; to the contrary, data should be cooked with care.
Never mind their recent data breach—the reason to avoid Quora is that it’s a data roach motel.
All of Quora’s efforts to lock up its community’s contributions make it incredibly difficult to preserve when that they go away, which they someday will. If you choose to contribute to Quora, they’re actively fighting to limit future access to your own work.
Minimalist cartography.
I quite like Phil’s idea of having charts like this. It might be a fun project for Homebrew Website Club to do something like this for my site.
While a geographical map is helpful if you want to find your way around the world, a population cartogram is the representation that we need if we want to know where our fellow humans are at home.
JavaScript is the web’s CO2. We need some of it, but too much puts the entire ecosystem at risk. Those who emit the most are furthest from suffering the consequences — until the ecosystem collapses. The web will not succeed in the markets and form-factors where computing is headed unless we get JS emissions under control.
Damn, that’s a fine opening! And the rest of this post by Alex is pretty darn great too. He’s absolutely right in calling out the fetishisation of developer experience at the expense of user needs:
The swap is executed by implying that by making things better for developers, users will eventually benefit equivalently. The unstated agreement is that developers share all of the same goals with the same intensity as end users and even managers. This is not true.
I have a feeling that this will be a very bitter pill for many developers to swallow:
If one views the web as a way to address a fixed market of existing, wealthy web users, then it’s reasonable to bias towards richness and lower production costs. If, on the other hand, our primary challenge is in growing the web along with the growth of computing overall, the ability to reasonably access content bumps up in priority. If you believe the web’s future to be at risk due to the unusability of most web experiences for most users, then discussion of developer comfort that isn’t tied to demonstrable gains for marginalized users is at best misguided.
Oh,captain, my captain!
Tools that cost the poorest users to pay wealthy developers are bunk.
It turns out that a whole lot of The So-Called Cloud is relying on magnetic tape for its backups.
A lovely bit of data visualisation from Nadieh showing the differences and commonalities in constellations across cultures. As always, she’s written up the process too.
Typography meets astronomy in 16th century books like the Astronomicum Caesareum.
It is arguably the most typographically impressive scientific manual of the sixteenth century. Owen Gingerich claimed it, “the most spectacular contribution of the book-maker’s art to sixteenth-century science.”
From smart dust and spimes, through to online journaling and social media, to machine learning, big data and digital preservation…
Is the archive where information goes to live forever, or where data goes to die?
This strikes me as a sensible way of thinking about machine learning: it’s like when we got relational databases—suddenly we could do more, quicker, and easier …but it doesn’t require us to treat the technology like it’s magic.
An important parallel here is that though relational databases had economy of scale effects, there were limited network or ‘winner takes all’ effects. The database being used by company A doesn’t get better if company B buys the same database software from the same vendor: Safeway’s database doesn’t get better if Caterpillar buys the same one. Much the same actually applies to machine learning: machine learning is all about data, but data is highly specific to particular applications. More handwriting data will make a handwriting recognizer better, and more gas turbine data will make a system that predicts failures in gas turbines better, but the one doesn’t help with the other. Data isn’t fungible.
Tutorials for recreating classics of generative art with JavaScript and canvas.