Xuebing Du
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Andulka
izzy's playlists!
Love Begins
PUT YOUR BEARD IN MY MOUTH
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Aqua Utopia｜海の底で記憶を紡ぐ
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@onproducts-blog
At least someone is keeping the government shut down light.
It's important to remember not to take life too seriously. Even when things feel very, very serious, it's the job of a designer to help shape the mood and experience.
Help make that shape hopeful and positive.
I just about blew a gasket because I couldn't figure out why something wasn't validating. JSON Lint to the rescue, it found the problem row in a jiffy. It's already in my bookmark bar, and should be in yours as well.
A pile of social application assets to add to your toolbox. Enjoy :-) h/t to [Patrick H at Bunch](http://www.joinbunch.com/group/36/mobile-web-design/# "Bunch Mobile and Web Design community").
Incredible Guardian interactive infographic on gun laws
It's pretty, and definitely interactive (please jump over to the site to play with it and other visualizations on gun laws). The trend identification potential of a radial grid, essentially, is also pretty cool.
But, I have to humbly disagree with the assessment "incredible."
tl,dr: It looks good and makes an interesting statement about the geography of gun laws. Many deficiencies make it a mediocre visualization.
Positive: The graphic demonstrates that the states in their Northeast category do have many more gun laws than the rest of the country, which is an interesting trend to identify, and argues that the gun control debate may be a "Northeast and California" thing.
The click-through image from his post, though, misses an important part of the visualization though.
The selector allows you to adjust the grid so that the wedge size is based on population rather than evenly distributed.
Side question: Why is Illinois adjacent to the Northeast if Ohio, Indiana and Michigan are all geographically in between? Sorting within the bins isn't by any immediately discernable order.
Criticism: What does blue mean in the center ring? Per the legend, it should be the shaded red color as with the rest of the scenegraph. We have to go to the graphic and hover over one of those blue boxes to discover that, on the "Open" ring, for example, the blue coloration means that the state bans open carry of a firearm.
Criticism: The color palate is divisive. Colors associated with GOP/conservative and DNC/liberal identities in the United States are well known. The choice of red to encode states that allow open and concealed carry reinforces an identity for pro-gun conservatives and dissociates pro-gun liberals. The choice of blue for various regulations reinforces an identity for pro-regulation liberals and dissociates pro-regulation conservatives. Non-associative colors should have been chosen to improve graphical integrity and honesty.
Criticism: The hashed red shading for "no law or law is unclear" in the regulation areas can be (and I'd be surprised if it hasn't yet) interpreted as being related to conservatives. The presence or absence of a law or regulation isn't party or ideologically polar, and non-associative shading should have been chosen to identify these points.
Criticism: The radial graph is only helpful in identifying the coarse grouping of Northeast states. Comparing specific information between individual states is cognitively difficult because of the separation between wedges we might compare, and because specific information is hidden in tooltips that only appear when a space is hovered. It's hard for people to store that specific information in their brains and make comparisons while looking at other tooltip information.
A moment for self-improvement
Take a time out for yourself and learn something new today.
Head on over to Learn Layout and brush up on your CSS skills (or learn for the first time).
Great examples of data visualization techniques.
Efficiency still matters
Scott Gilbertson offers helpful instructions in a recent article for Webmonkey, on new services browsers to configure browsing through mobile-optimizing proxies. A gem:
Google and Opera are doing what web developers ought to be doing but aren’t. Just like developers should have been making reader-friendly pages, but weren’t, so “reader” modes were born.
It's a problem that we tend to bloat our software along with the advancing capabilities of the hardware on which it's used. It's an interesting aspect of our physiology and psychology.
We "see" through a composite picture built of series of quick eye movements, because most of our color vision capability is located in a small, central part of the retina. Further biology of the eye makes us really good at seeing changes in contrast, much more than differences in color. This leads our model for perception to be based around identifying and noticing changes in shapes within our mental map of the world.
I'll take the leap, then, and suggest that the process of constantly adjusting our perception of edges and contrast in that mental image, translates to a broader approach to higher-order mental constructs. We normalize our expectations of an object so that we might notice small changes with more acuity.
4-wheel drive was a major safety feature when drivers treat 4WD cars like 2WD cars. When they normalize their perception, however, and drive 4WD cars to the limit of their capabilities (as happens often in 2WD), the driver negates the safety afforded to them. There are many further examples; take it as homework to find one or two in your daily life.
Anyways... if I continue down this obviously infallible road, by treating the world with such a constant re-normalizing process, we end up building toward a moving target. It allows us to make significant strides, definitely. But it also leads to bloat, in our languages, designs and expectations of the abilities of the end host. Especially with the trend toward running websites like applications in the browser, sending 10's of megabytes to sit on local storage and eat up memory.
If I may suggest, let's please take a step back now and again, and determine if we really need to send the kitchen sink to the client, too.
I'll leave you with something to chew on:
In other words, if your site isn’t svelte and fast, it’s not well designed no matter how pretty it might look.
Fruits of some Python-y efforts
So, here’s a cursory look at what a little Python and some elbow grease turn up.
Have a look: Public transport during rush hour in LA
This is every bus in LA County, from just before 07:00 to about 09:30, collected every 7 minutes using the Metro Transit Authority’s awesome developer tools. It’s an initial effort to look at the way that populations have changed and what trends the transportation has followed. I’m using Tableau Desktop here to explore the data.
This first capture is a simple view with default glyph sizing.
Next we drop the glyph size so that the individual points come out. It’s fascinating to see the routes all light up.
And here is a first attempt at conflating bus routes against Census data.
In this case, population change from 2009 to 2013.
I’ll talk a bit about the data and what I did next week, but I wanted to show these (especially the little video, go back and have a look) off now.
Happy Friday everyone!
Hip Shots: Heritage Foundation on the sequester
Heritage Foundation published a visualization of where the cuts in the Budget Control Act will come from, and in what percentage from which parts of the federal budget.
It get's a mixed grade.
Information is grouped with like information, allowing visual comparison of the sizes of budgets. Color stands out, attracting the audience's attention and specifically walking us through the point they mean to make—that the defense budget will be much more aggressively cut than other parts of the budget.
They had a neat idea to put the size of a cut inside the size of a budgets sector, but it creates some visual dishonest; comparing like objects that are adjacent, the audience will overestimate the size of a cut in a larger box vs. and overestimate the size of a cut in a smaller box. As an experiment, objectively, which cut looks larger: Net Interest or Entitlement Spending? Now cover the two middle categories and look again. Without the numbers, we'd likely conclude from a brief glance that more money was being cut from Net Interest, even though the two small boxes are for all purposes the same size, because the Net Interest cut in-context looks larger.
Encoding quantitative data in surface areas is non-optimal for data comparison.
Also, the visualization and the caption it accompanies on the link-through site don't explain what is considered "Entitlement Spending" vs "Non-Defense Discretionary Spending", which may mean that some information was added to the Entitlement section that inflates its size and obscures the actual cut percentage. Transparency there would be worthwhile.
Bottom line: It does tell a story, and it tells that story well. It is questionable for the visual distortion in its visualization methodology and potentially for its data categorization.
Hip shots: Nextgov
A brief criticism of Nextgov, using this article.
The page:
Let's play "Where's the content?"
This screen shot shows the actual article. It's easier to identify when the Flash advertisements aren't dancing on the page.
Highlighted here are the parts of this page which actually make up the news of the article (I gave the author a call out because the author of an article, and when it's published, are important).
The volume of noise in this page is astounding. The advertisements are unabashedly the focus of this design, and are arresting in their colorful and animated presentaiton. Small, cramped text areas and thrown-away bylines are the second biggest failure; the reader wants news, but Nextgov would rather they click some ads instead.
It's an unfortunate failure of the product team to maintain the value of their product in the face of sales and operations.
This section is particularly cogent. In a very short time I've already been guilty of most of these.
Python Style
I'm learning Python, and, like lots of people it seems, the thing that bugs me the most about reading other people's code is neglected conventions. Especially having started my post-college life as a technical writer, I'm sure I can be frustratingly obtuse when it comes to the subject.
So it makes me happy to find well-written, casual guides like this one, written by Guido van Rossum and Barry Warsaw. It's a quick read, dense, easily accessible to a non-convert and, overall, just plain useful.
If you use Python and haven't refreshed in a while (or want to know how to make it look right), give the guide a gander.
PEP 8 - A Style Guide for Python Code
Paying back technical debt
James LaPlaine, a VP of Technical Operations at AOL, wrote [a post on technical debt](http://mentaleffort.wordpress.com/2012/03/04/technical-debt-part-1-stop-accumulating-debt/) many months ago. It's a topic I often try to come back to, at work or at home. > Many of the technology choices of a software product may seem fully rational at the inception of a project, but over time may turn into technical debt. [...] It is pretty clear to me that technology choices turns into debt over time if they are not periodically refreshed and upgraded. Managing technical systems is a continual process of reevaluation and reinvestment. Tangential pressures from well-meaning and active stakeholders often serves to only complicate the matter. > All to often we’re presented with a technology that has been chosen because it’s new, is all the rage, or suggested in some off-hand comment by an executive. How do the shortcuts we take today mess up our productivity tomorrow? What strategies can we follow to stop ourselves from creating these problems in the first place?
