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.
A City Is Not a Tree
- Strands of life
- Impending destruction
- The right overlap
- The difficulty of designing complexity
- Political chains of influence
Strands of life
For the human mind, the tree is the easiest vehicle for complex thoughts. But the city is not, cannot, and must not be a tree. The city is a receptacle for life. If the receptacle severs the overlap of the strands of life within it, because it is a tree, it will be like a bowl full of razor blades on edge, ready to cut up whatever is entrusted to it. In such a receptacle life will be cut to pieces. If we make cities which are trees, they will cut our life within to pieces.
Impending destruction
In any organized object, extreme compartmentalization and the dissociation of internal elements are the first signs of coming destruction.
The right overlap
Overlap alone does not give structure. It can also give chaos. A garbage can is full of overlap. To have structure, you must have the right overlap.
The difficulty of designing complexity
Designers, limited as they must be by the capacity of the mind to form intuitively accessible structures, cannot achieve the complexity of the semilattice in a single mental act. The mind has an overwhelming predisposition to see trees wherever it looks and cannot escape the tree conception.
Experiments suggest strongly that people have an underlying tendency, when faced by a complex organization, to reorganize it mentally in terms of non-overlapping units. The complexity of the semilattice is replaced by the simpler and more easily grasped tree form.
Political chains of influence
In Chicago, formal chains of influence and authority are entirely overshadowed by the ad hoc lines of control which arise naturally as each new city problem presents itself. These ad hoc lines depend on who is interested in the matter, who has what at stake, who has what favors to trade to whom.
This structure, which is informal, working within the framework of the first, is what really controls public action. It varies from week to week, even from hour to hour, as one problem replaces another. Nobody’s sphere of influence is entirely under the control of any one superior; each person is under different influences as the problems change. Although the organization chart in the Mayor’s office is a tree, the actual control and exercise of authority is semilattice-like.
Same name in the same basket
Does a concert hall ask to be next to an opera house? Can the two feed on one another? Will anybody ever visit them both, gluttonously, in a single evening, or even buy tickets from one after going to a performance in the other?
In Vienna, London, Paris, each of the performing arts has found its own place, because all are not mixed randomly. The only reason that these functions have all been brought together in Lincoln Center is that the concept of performing art links them to one another. The organization is born of the mania every simple-minded person has for putting things with the same name into the same basket.
Separation of concerns
Another favorite concept of the CIAM theorists and others is the separation of recreation from everything else. This has crystallized in our real cities in the form of playgrounds. The playground, asphalted and fenced in, is nothing but a pictorial acknowledgment of the fact that ‘play’ exists as an isolated concept in our minds. It has nothing to do with the life of play itself. Few self-respecting children will even play in a playground.
Play itself, the play that children practice, goes on somewhere different every day. In a natural city this is what happens.
Structural complexity
The idea of overlap, ambiguity, multiplicity of aspect, and the semilattice are not less orderly than the right tree, but more so. They represent a thicker, tougher, more subtle and more complex view of structure.
Neighborhoods
We cannot get an adequate picture of what Middlesborough is, or of what it ought to be, in terms of neighborhoods. When we describe the city in terms of neighborhoods, we implicitly assume that the smaller elements within any one of these neighborhoods belong together so tightly that they only interact with elements in other neighborhoods through the medium of the neighborhoods to which they themselves belong. Ruth Glass herself shows clearly that this is not the case.
Cities which are trees
Columbia, Maryland
Greenbelt, Maryland
Greater London Plan
Mesa City, Paolo Soleri
Tokyo Plan, Kenzo Tange
Chandigarh (Le Corbusier)
Brasilia, Lucia Costa
Communitas (Percival and Paul Goodman)
Roman town evolved from military campsIn the worst cases, the units of which these cities are composed fail to correspond to any living reality; and the real systems, whose existence actually makes the city live, have been provided with no physical receptacle.
In a tree structure, it means that within this structure no piece of any unit is ever connected to other units, except through the medium of that unit as a whole.
Sets and systems
When the elements of a set belong together because they cooperate or work together somehow, we call the set of elements a system.
From a designer’s point of view, the physically unchanging part of this system is of special interest. I define this fixed part as a unit of the city.
Whatever picture of the city someone has is defined precisely by the subsets he sees as units.
Natural and artificial cities
I want to call those cities which have arisen more or less spontaneously over many, many years natural cities. And I shall call those cities and parts of cities which have been spontaneously created by designers and planners artificial cities. Siena, Liverpool, Kyoto, and Manhattan are examples of natural cities. Levittown, Chandigarh, and the British New Towns are examples of artificial cities.
It is more and more widely recognized today that there is some essential ingredient missing from artificial cities.
Trees and semilattices
The tree of my title is not a green tree with leaves. It is the name of an abstract structure. I shall contrast it with another, more complex abstract structure called a semilattice.
Both the tree and semilattice are ways of thinking about how a large collection of many small systems goes to make up a large and complex system.
A collection of sets forms a semilattice if, and only if, when two overlapping sets belong to the collection, the set of elements common to both also belongs to the collection. That is, if [234] and [345] belong to the collection, then [34] belongs to the collection.
A collection of sets forms a tree if, and only if, for any two sets that belong to the collection either one is wholly contained in the other, or they are wholly disjoint. Every tree is trivially a simple semilattice.
We are concerned with the difference between structures in which no overlap occurs, and those structures in which overlap does occur.
The semilattice is potentially a much more complex and subtle structure than a tree. It is this lack of structural complexity, characteristic of trees, which is crippling our conceptions of the city.