I like this approach to offering a design system. It seems less prescriptive than many:
Designed not as a rule set, but rather a toolbox, the Data Design Language includes a chart library, design guidelines, colour and typographic style specifications with usability guidance for internationalization (i18n) and accessibility (a11y), all reflecting our data design principles.
Here’s a really excellent, clearly-written case study that unfortunately includes this accurate observation:
In recent years the practice of information architecture has fallen out of fashion, which is a shame as you can’t design something successfully without it. If a user can’t find a feature, it’s game over - the feature may as well not exist as far as they’re concerned.
I also like this insight:
Burger menus are effective… at hiding things.
My talk, Building, was about the metaphors we use to talk about the work we do on the web. So I’m interested in this analysis of the metaphors used to talk about markup:
- Data is documents, processing data is clerking
- Data is trees, processing data is forestry
- Data is buildings, processing data is construction
- Data is a place, processing data is a journey
- Data is a fluid, processing data is plumbing
- Data is a textile, processing data is weaving
- Data is music, processing data is performing
The design process in action in Victorian England:
Recognizing that few people actually read statistical tables, Nightingale and her team designed graphics to attract attention and engage readers in ways that other media could not. Their diagram designs evolved over two batches of publications, giving them opportunities to react to the efforts of other parties also jockeying for influence. These competitors buried stuffy graphic analysis inside thick books. In contrast, Nightingale packaged her charts in attractive slim folios, integrating diagrams with witty prose. Her charts were accessible and punchy. Instead of building complex arguments that required heavy work from the audience, she focused her narrative lens on specific claims. It was more than data visualization—it was data storytelling.
This is a story about pizza and geometry.
The interactive widget here really demonstrates the difference between showing and telling.
City of Women encourages Londoners to take a second glance at places we might once have taken for granted by reimagining the iconic Underground map.
I love everything about this …except that there’s no Rosalind Franklin station.
Following on from my recently-lost long bet, this is a timely bit of data spelunking from Brian analysing the linkrot of 1400 links over 18 years of time.
Goodreads lost my entire account last week. Nine years as a user, some 600 books and 250 carefully written reviews all deleted and unrecoverable. Their support has not been helpful. In 35 years of being online I’ve never encountered a company with such callous disregard for their users’ data.
Ouch! Lesson learned:
My plan now is to host my own blog-like collection of all my reading notes like Tom does.
A fascinating four-part series by Lisa Charlotte Muth on colour in data visualisations:
This is a great combination of rigorous research and great data visualisation.
We’ve got click rates, impressions, conversion rates, open rates, ROAS, pageviews, bounces rates, ROI, CPM, CPC, impression share, average position, sessions, channels, landing pages, KPI after never ending KPI.
That’d be fine if all this shit meant something and we knew how to interpret it. But it doesn’t and we don’t.
The reality is much simpler, and therefore much more complex. Most of us don’t understand how data is collected, how these mechanisms work and most importantly where and how they don’t work.
Even if you can somehow justify using tracking technologies (which don’t work reliably) to make general, statistical decisions (“fewer people open our emails when the subject contains the word ‘overdraft’!”), you can’t make individual decisions based on them. That’s just wrong.
Prompted by my post on tracking, Chris does some soul searching about his own use of tracking.
I’m interested not just in the ethical concerns and my long-time complacency with industry norms, but also as someone who very literally sells advertising.
He brings up the point that advertisers expect to know how many people opened a particular email and how many people clicked on a particular link. I’m sure that’s right, but it’s also beside the point: what matters is how the receiver of the email feels about having that information tracked. If they haven’t given you permission to do it, you can’t just assume they’re okay with it.
Download this PDF to see 100 beautiful literary visualisations.
The next best thing to having Kurt Vonnegut at the blackboard.
Simon describes the pattern he uses for content sites to get all of the resilience of static site generators while keeping dynamic functionality.
Caleb Scharf:
Wait a minute. There is no real difference between the dataome—our externalized world of books and computers and machines and robots and cloud servers—and us. That means the dataome is a genuine alternative living system here on the planet. It’s dependent on us, but we’re dependent on it too. And for me that was nerve-wracking. You get to the point of looking at it and going, Wow, the alien world is here, and it’s right under our nose, and we’re interacting with it constantly.
I like this Long Now view of our dataome:
We are constantly exchanging information that enables us to build a library for survival on this planet. It’s proven an incredibly successful approach to survival. If I can remember what happened 1,000 years ago, that may inform me for success today.
The discussions around data policy still feel like they are framing data as oil - as a vast, passive resource that either needs to be exploited or protected. But this data isn’t dead fish from millions of years ago - it’s the thoughts, emotions and behaviours of over a third of the world’s population, the largest record of human thought and activity ever collected. It’s not oil, it’s history. It’s people. It’s us.
This is a great HTML boilerplate, with an explanation of every line.
Visualising the growth of the internet.