Fortunately some typefaces are emerging that make constructing these elements directly within layout applications such as Adobe InDesign much easier. These “Smart Fonts” use Opentype features to allow seamless layering of graphic elements and on-the-fly glyph replacement, the results of which were previously only possible using Adobe Illustrator.

Below are examples of three of these typefaces.

FF Dingbats 2.0

FF Dingbats 2.0 is an evolution of FontFont’s early 1990s pictographic type family. Version 2.0 brings alternate glyphs sets for each pictogram (outlines, fills, and additional details), allowing multi-layering and full color customization. By choosing a specific Opentype feature, the spacing of each glyph is adjusted so they stack perfectly on top of one another. You can read more about FF Dingbats 2.0 here.

Chartwell

Designed by Travis Kochel, Chartwell is a type family designed specifically for producing data visualizations. It works by detecting numeric character combinations and substituting them with custom-designed ligatures. Each substituted ligature is influenced by previously entered values, allowing for seamless pie charts, line charts, and bar graphs. You can find out more about how Chartwell works here.

Wayfinding Sans Symbols

As an addition to his signage design typeface, Wayfinding Sans, type designer Ralf Herrmann has developed a pictographic counterpart. Although it may seem like an ordinary pictographic typeface at first glance, the demonstration video below reveals some ingenious Opentype features. Need a shopping basket icon? No problem. Thanks to Opentype, simply type #shoppingbasket and there it is.

Wayfinding Sans Symbols (Preview) from Ralf Herrmann on Vimeo.

The best part? Although currently in beta testing, the typeface will be released as a free download at fonts.info. You can find out more about Wayfinding Sans Symbols here.

I’m really excited to see what else Opentype can do for type design. I expect to see lots more “Smart Fonts” appearing in the future.

I’ll admit it – I’m a recovering design process deliverables junkie. Historically, the generation of process maps, usability audits, wireframes, site diagrams, application flows, mental models, task-level scenarios, user stories, standards documentation, conceptual frameworks, content audits, navigation maps, and countless other examples of design ephemera, were so central to the work that we created for clients that we began to view them as the work we were creating for our clients. In reality, as important as many of those deliverables may be, they are just means to an end. The end – is a finished product that customers want to purchase and use and a solution that meets or exceeds the clients expectations.

So before I start a holy war about the importance of research, process, and planning in User Experience Design (UX), let me be clear – all of the steps and deliverables mentioned above are, in many scenarios, important and useful elements of the design process. But as time has gone by, and we’ve continued to refine our own approach to design, we’ve begun to realize that by over-emphasizing their importance we’re doing a disservice to our clients and ourselves. Sometimes, some (and very rarely all) of, these deliverables are critical to delivering a winning design solution. But trotting them out in front of clients in an often vain attempt to either impress them, overwhelm them, or justify your fees often has the inverse effect.

In a brilliant post, titled “An Open Letter To The Design Community“, Marty Cagan at the Silicon Valley Product Group details some common traps that designers often fall prey to. In particular he extolls the virtues of getting to the real product, via Hi-Fidelity prototypes, as quickly as possible.

“Please people, if you want to succeed at your company, just remember this rule: the only thing that works to explain your design to execs and stakeholders are prototypes, the higher the fidelity the better.  Do yourself a favor and keep the sausage making within the design team.  Some execs will want to know how you got from here to there, and that’s okay, so long as you start with them understanding where “there” is.”

Do yourself a favor and keep the sausage making within the design team.

We’ve discovered a much more liberating way to engage our clients, do away with a ton of busy work, and deliver better design solutions in the bargin. In short, it’s about getting to the point. You can’t cut corners or entirely abandon the development of design support materials, but you can get much smarter about determining what design deliverables are essential to the projects success and which ones are only part of your process because you feel they have to be. I can promise you, at least in our experience, that most clients don’t care and aren’t nearly as impressed by many of the process-oriented deliverables that we, as designers, have come to hold sacred.

We’ve discovered a much more liberating way to engage our clients, do away with a ton of busy work, and deliver better design solutions in the bargin.

I’m not suggesting that you can go from a back of the napkin sketch to a fully functional product design without going through the painstaking process of researching user needs, mapping complex interactions, and creating comprehensive design specifications. What I am saying is that, that’s the stuff in the kitchen that you darn well better know how to execute on and that getting to something worthy of presentation in the dining room is where your focus should be. The faster you can get to a “real world” manifestation of the final product the happier your client will be and the sooner you’ll be able to begin the process of refining the design solution.

We’ve started by pulling together a list of all the tech-oriented startup in Indy. Currently it’s an incomplete list. If you are a founder of an Indianapolis-based startup or you are aware of one that is not our list, please go here and submit it. There are lots of really great young companies here in Indy, but for the time being we are predominantly focusing on technology and technology-enabled businesses in the web space (software, web-apps, etc.). For the time being, we’re not focusing on advanced manufacturing, life sciences, or service-based businesses – but that will come.

Once we’ve got a good handle on startup landscape in Indianapolis, we’ll begin to flesh out the other side(s) of the coin… infrastructure, support services, funding, etc. We’ve begun to detail some of that already, but its a work in progress. We’re using a really cool application called Mindmeister to create a mind map of the ecosystem. You can check out a truncated view below, or click through to see the whole thing. One the infrastructure and services tip we are really looking for businesses that specialize in working with and for startups. We’re really looking for businesses and organizations that are focused on the Indy startup space. Indianapolis is achieving critical mass in the startup infrastructure space and that is what we want to highlight.

If you have a startup or a technology/web-based startup to recommend or would like to ask a question, hit me up on Twitter @kristianindy and let me know about it. But take a look at the mind map we’ve set-up first so that you can get an idea of what we’re looking for.

Note: Regarding “stages” (e.g. seed, growth, established, etc.) These are pretty fluid terms, but you can use the following brief descriptions for context.

Early/Seed Stage – Building the product and proving the concept

Growth Stage – Growing the business and becoming self-sustaining

Established – Profitable, stable, managed growth

Once the mapping process is completed, we’ll publish the entire Indy Startup Genome Project online for public consumption.

Warning: This is a work in progress. There will be errors and omissions. If you find an error or omission, let us know in the comments.

Our most recent app engagement began in the usual way, collaborating with the client on multiple rounds of wireframes and process maps, dialing in the inner workings and structure of the app itself. When we started to move forward into the initial visual prototypes the ideas for the navigation and overall aesthetic came fast, but we quickly realized something just didn’t ‘feel’ right. It didn’t take long before we realized why and just how easy it is to fall into the same trap that so many others do when designing for the iPhone. In an attempt to create something fresh and slick we were losing the very thing that makes the best iPhone apps ‘feel’ right – familiarity.

“… it is clear that a user interface feature is ‘intuitive’ insofar as it resembles or is identical to something the user has already learned. In short, “intuitive” in this context
is an almost exact synonym of ‘familiar.’”
—Jef Raskin

Spend time with the native iPhone apps such as Mail, Calendar and Clock, and you can see familiarity at play. While each one fulfills a different purpose, they seem like they were ‘cut from the same cloth’, related, familiar. They share common design elements such as standard header and footer bars with clear navigation controls. They share consistent colors, gradients, shadows and highlights. There is a minimal amount of information presented on-screen at any one time and there are no distracting superfluous visuals to get in the way. main navigation and other interactive elements are appropriately sized and spaced so they are easy to ‘tap.’

Some of the other native iPhone apps such as Weather, Stocks and Maps need to present more visual-based information, calling for more elaborate interfaces. However, Apple have managed to retain the same familiarity throughout by using the same basic principles. Many of the third party apps available in the App Store are also successful for these reasons. Below are some of the apps I use on a daily basis:

The last several weeks here at Kristian Andersen + Associates have been a very busy time indeed. Last week, as we wrapped up our work for ExactTarget’s Connections User Conference, we decided to treat ourselves to a new office toy – a Nintendo Wii and a copy of Rock Band 2. Perfect for unwinding after a hard day’s work, or simply to make complete fools of ourselves when the mood takes us.

I’d already been playing Rock Band for a couple of months, the guitar being my instrument of choice. I’ve managed to work my way up to playing on Hard level, and even on Expert on a few of the more simple songs. Late Saturday night I had the opportunity to play Guitar Hero, Activision’s alternative and rival to Harmonix’ Rock Band series. Without thinking I jumped straight into a song on Hard level, only to be booed off about a minute in. I initially put this down to not having played the song before (some songs are title exclusives and aren’t available on the competitor’s product). I then restarted on Medium level, this time only just making it through to the end of the song. This time I blamed bad guitar calibration. However, as time passed I realized that the owner of the game and guitar seemed to be doing just fine on Hard and even Expert level. That left only one cause for my lack of performance – the several bottles of Heineken and pints of Dogfish Head 60 Minute IPA. I decided to pass on Guitar Hero for the rest of the night and went home to sleep off my shame.

On Sunday I picked up my Rock Band guitar and played a few songs, again on Hard and Expert level, getting through with high 90s percentage scores. Then it hit me. The reason why I was no good at Guitar Hero had nothing to do with not knowing the song, nothing to do with bad calibration, and maybe only a little to do with the alcohol content of my blood that night. It had almost everything to do with data visualization.

Playing guitar in Rock Band and Guitar Hero works pretty much the same way. On screen there is a fretboard, like that on a real guitar, with five tracks (or strings) on which song notes travel towards you. When these notes reach the hit bar at the bottom of the screen, you hit the strum bar. Simple. These song notes are essentially data that is presented to you over time as the song progresses. The big difference between the two is in the way this data is visually presented.

Back in August, Nathan and I attended a seminar by Edward Tufte (a recap of which can be read here). He opened his talk with a video of Stephen Malinowski’s Music Animation Machine, an example of which you can see below. It is a beautifully simple representation of musical data, and strikingly familiar to fans of Rock Band.

The quote below from Nathan’s post has perfectly summarized my opinion on the main reason Rock Band triumphs over Guitar Hero.

If you’re having to dress up your content or data with superfluous visuals, not only are you making the content harder to decipher, you’re manipulating your audience in a negative way.

Rock Band’s notes are represented by simple colored bars, as opposed to Guitar Hero’s bulbous, spinning UFOs that are so bulky they almost obscure the notes that follow behind. Guitar Hero’s fretboard is also harder to follow: it is set at a shallower angle, the strings are difficult to make out and the timing bars aren’t as obvious. Earlier versions overlaid visual effects on the fretboard, further distracting you from the data, but thankfully everything is much cleaner with the latest release. Admittedly Guitar Hero uses three-finger chords more liberally, and some song sections are a little more difficult, but the playing a song ends up as an exercise in staying calm under pressure (fending off the alien attack), rather than being able to enjoy the music. Transfer the raw data from one to the other and I know which one I’d have an easier time following.

The lesson here is simple: don’t dress up data or use superfluous visuals that will detract from the information you are trying to present. If the content is strong enough it shouldn’t need the visuals to scream at you unnecessarily. That diagram doesn’t need swooping, overlapping rainbow gradient arrows and three-dimensional boxes; that ‘Sign Up’ button doesn’t need to flash lime green and bright red; and those song notes certainly don’t need dressing up as spinning UFOs.

For the time being we’ll stick with Rock Band. Give us a few months and we’ll be able to handle anything… except maybe if it’s this hard:

The visual display of data and information is about to explode — or maybe it already has. It’s been an area of design expertise for many years, but we’re now faced with more mountains of data than ever before, and they’re staggeringly high.

The image above, a visualization of 50 years of space exploration, is one example how data visualizations have risen in popularity. They’ve gained an aura of coolness, kind of like rock posters (in some circles anyway). Firms such as Visual Complexity focus exclusively on this design niche. And we’ve seen more and more data visualization websites like We Feel Fine and DAYTUM pop up over the last couple of years and offer experimental solutions for managing and understanding some of the reams of data our everyday activities now create.

Looking cool is a great benefit, but usefulness is where the real value lies. At KA+A many of our clients provide a web-based product or service, many of them with a focus on online marketing. We’ve seen a shift in focus over the last couple of years from merely capturing data, to figuring out how to make it visible, understandable, and actionable. Data for the sake of data isn’t worth much. It’s what it enables you to do that matters.

We see ourselves as having an integral role to play as organizations begin to more aggressively explore the ways in which data can be understood and used. By looking to today’s experts, like Edward Tufte, we begin with a solid foundation, one built upon the core principles of the display of visual information. However, technology has created opportunities to interface with data in brand new ways, so designers will also have to explore and develop new best practices and principles that will apply to interactive data visualization — visualizations that are dynamic and can be adjusted in real time to show relationships, comparisons, contrasts, predictions, and more.

The ability to identify and clarify relationships between disparate pieces of information is a skill that designers tend to employ naturally, and this is an area where its application is particularly relevant. We’re looking forward to watching this field grow, as well as participating in its evolution.

If you have any favorite examples, post them in the comments.

There were more quotables in that eight hour course then you could shake a stick at. Here are a handful the choicest thoughts I took away:

• Don’t waste time visualizing information than doesn’t need it. People aren’t stupid.
• Never dumb things down.
• Overproducing information is dishonest and manipulative, and reveals a lack of performance.
• Don’t get original, get it right.
• Don’t hurt your credibility with metaphors.
• Legends and codes are the enemies of charts.
• Look to science for innovative visualizations (the world of business has largely failed at presentation because of a focus on “the pitch”).
• Document everything.
• Content counts most of all. Analytical presentations ultimately stand or fall depending on the quality, relevance, and integrity of their content.
• Get better data and content.

What impacted me the most from Tufte’s course, was the idea that if you’re having to dress up your content or data with superfluous visuals, not only are you making the content harder to decipher, you’re manipulating your audience in a negative way. This isn’t to say that your presentation shouldn’t look great (and possibly even glossy), just that it shouldn’t look great in an attempt to cover up irrelevance or unimportance.

It occurs to me that this is a great way test an idea or concept. If it’s not compelling in an unadorned state, and you spent more time trying to “trick out” the way it looks than you did on the idea itself, maybe it’s not a very good idea in the first place.