data
INSUFFICIENT DATA FOR MEANINGFUL ANSWER.
The Eyes Have It
A Research Paper by Ben ShneidermanThe trend is your friend 'til the bend at the end
A Fragment by Noah SmithIn the past, GDP and resources use have always been tightly correlated. But this is just drawing a line through some data — it’s not based on any deep theory. And in fact, these correlations can change very quickly. Just as one example, here’s energy use versus GDP since 1949.
If you were sitting in 1970, you could look at this curve and claim, very confidently, that economic growth requires concomitant increases in energy use. And you’d be wrong. Because the trend is your friend til the bend at the end.
Embracing Asymmetrical Design
An Article by Ben NadelHumans love symmetry. We find symmetry to be very attractive. Our brains may even be hard-wired through evolution to process symmetrical data more efficiently. So, it's no surprise that, as designers, we try to build symmetry into our product interfaces and layouts. It makes them feel very pleasant to look at.
Unfortunately, data is not symmetrical…Once you release a product into "the real world", and users start to enter "real world data" into it, you immediately see that asymmetrical data, shoe-horned into a symmetrical design, can start to look terrible.
To fix this, we need to lean into an asymmetric reality. We need to embrace the fact that data is asymmetric and we need to design user interfaces that can expand and contract to work with the asymmetry, not against it. To borrow from Bruce Lee, we need to build user interfaces that act more like water:
“You must be shapeless, formless, like water. When you pour water in a cup, it becomes the cup. When you pour water in a bottle, it becomes the bottle. When you pour water in a teapot, it becomes the teapot. Water can drip and it can crash. Become like water my friend.” — Bruce Lee
Goodbye, Google
An Article by Douglas BowmanWithout a person at (or near) the helm who thoroughly understands the principles and elements of Design, a company eventually runs out of reasons for design decisions. With every new design decision, critics cry foul. Without conviction, doubt creeps in. Instincts fail. “Is this the right move?” When a company is filled with engineers, it turns to engineering to solve problems. Reduce each decision to a simple logic problem. Remove all subjectivity and just look at the data. Data in your favor? Ok, launch it. Data shows negative effects? Back to the drawing board. And that data eventually becomes a crutch for every decision, paralyzing the company and preventing it from making any daring design decisions.
Yes, it’s true that a team at Google couldn’t decide between two blues, so they’re testing 41 shades between each blue to see which one performs better. I had a recent debate over whether a border should be 3, 4 or 5 pixels wide, and was asked to prove my case. I can’t operate in an environment like that. I’ve grown tired of debating such minuscule design decisions. There are more exciting design problems in this world to tackle.
The Subtleties of Color
A Series by Robert SimmonThe use of color to display data is a solved problem, right? Just pick a palette from a drop-down menu (probably either a grayscale ramp or a rainbow), set start and end points, press “apply,” and you’re done. Although we all know it’s not that simple, that’s often how colors are chosen in the real world. As a result, many visualizations fail to represent the underlying data as well as they could.
Data Farming
A Research PaperMiners seek valuable nuggets of ore buried in the earth, but have no control over what is out there or how hard it is to extract the nuggets from their surroundings. ... Similarly, data miners seek to uncover valuable nuggets of information buried within massive amounts of data.
Farmers cultivate the land to maximize their yield. They manipulate the environment to their advantage using irrigation, pest control, crop rotation, fertilizer, and more. Small-scale designed experiments let them determine whether these treatments are effective. Similarly, data farmers manipulate simulation models to their advantage, using large-scale designed experimentation to grow data from their models in a manner that easily lets them extract useful information.
What Good Means
The center of the way
The advice I’ve received from those who are close to the center of this timeless way of building is to start small. Like with a piece of tile, or a tea tray. And to then imagine along with Christopher Alexander:
What it would be like
to live in a mental world
where one’s reasons
for making something
functionally
and one’s reasons
for making something
a certain shape,
or in a certain
ornamental way
are coming
from precisely
the same place
in you
.Seduction
“The classic pervasive seduction to designers is finding a solution instead of the truth.” — Richard Saul Wurman
What the material wants to be
Part of how Lou Kahn made things be good was to ask the material what it wanted to do and be. He asked brick what it liked, and would get a different answer depending on the context for the building. In Dacca, the capital of Bangladesh, brick said it liked an arch. For the Korman House in Philadelphia, brick said it liked two giant fireplaces with a lintel between them for a doorway beneath and a balcony above.
Asking yourself some questions
All of the moves that we make in space will tend toward being in accord with this phenomenon of wholeness / beauty / life if we’re willing to bring the requisite level of care to the doing of our work.
Alexander says that each of us possess the means for accessing this order within ourselves and — here’s where he loses most other architects and many in the so-called sciences in academia — he contends that what we’re connecting with inside of ourselves is an objective criterion for what good means.
Applying the criterion is easy: you ask yourself some questions:
With any action you might take with regard to placement, and with regard to the situatedness of things in space you ask yourself: does this move increase wholeness / beauty / life?
Does the intervention you’re taking intensify the feelings of wholeness in you as the maker when you are performing the work?
How does your work on this one part enhance what’s going on among wholes at the system level?
Losing meaning
The people who’ve proven that they can make very good individual products with the radical focus of a spotlight seem to be pushed ever further from making good ecosystems.
Products are being made “consistent” with the application of so-called “design patterns,” and rather than bringing coherence to these various touch-points, the painting-on of interface standards and interaction patterns did something far less valuable.
Rote consistency, in the way many seem to be going about it (Material Design being just one example), is at odds with making things be good. It simplifies what needs to remain complex.
Always, when simplification is underway, meaning is being lost.
Two coffee trays
We speculate that the shop owners designed and built an initial quantity of these remarkable coffee trays, replete with what Alexander considers to be the fifteen geometric properties that correlate with wholeness / beauty / life.
Then they got busy. And then they got successful. They needed more coffee trays, and our hypothesis is that somebody decided to simplify the trays to ensure they could be produced in the quantities and at the price that worked for their budget, within an urgent food-service timeline.
The simplified tray fulfills every function the more complex tray does, with less fuss in manufacturing on account of having standardized its geometry. The simplified tray works, but isn’t alive. It lacks the gradients, local symmetries, levels of scale, contrast, and boundaries that are all present and accounted for in the tray that’s got wholeness / beauty / life. The tray with wholeness isn’t necessarily better than the simpler one. But it is good.