1. Be Comfortable, Creature by the Explosions in the Sky from Take Care, Take Care, Take Care
2. Avant Garde Music by Ballboy from A Guide for the Daylight Hours
3. My Heart Rate Rapid by Metronomy from Nights Out
4. Die by Girls from Father, Son, Holy Ghost
5. Wired by I Break Horses from Hearts

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Put more specifically, font classifications pigeon-hole fonts by historical or visual attributes, but not by role, sentiment, emotional impact, mental association, idiosyncrasies, technical features, stylistic variety, societal characteristics, internationalisation, technical concerns, or many other ways that a visual designer may be approaching font selection. I want to change that, but it won’t be easy, and I’ll need some help (more on that later).

The thing is, there is no one font classification system to rule them all. In fact there is a huge number of classification systems. A British Standard for (BS 2961) does – or did – exist, but that seems to have been abandoned fifty years ago. It was based on the Vox-ATypI system which was adopted by ATypI (the Association International Typographique) in 1962. The Vox-ATypI system was compiled by Maximilien Vox in 1952 and reflected the availability of fonts at the time, the vast majority of which were historical serif body text fonts. Sans-serif and slab-serif fonts are not well served by the classification, and fonts for use at heading and display sizes are almost completely ignored.

In addition to its Victorian bias, the Vox-ATypI category names are also arcane and cryptic. Consider the serif categories ‘Garald’ and ‘Didone’. These words are constructs of 16th and 19th Century type designers Garamond & Aldus Manutius, and Didot & Bodoni. These labels will clearly mean little to most designers without a formal typographic education. Admittedly Fontdeck uses both these terms in its font browsing system, although it incorporate other classifications and tagging to provide further routes for finding and filtering.

Earlier this month, the type designer Ray Larabie began a thread on Typophile by saying “conventional font categories are practically useless to me.” With this, Larabie posted a very different list of categories which he uses to classify his fonts, almost all of which “fall under decorative or sans-serif”. The ensuring conversation with other type designers is well worth a read.

Font description schemes

Font classifications provide single words with which to categorise fonts, but font description schemes, such as Panose, go a step further and provide systematic facets by which to describe fonts. In 2002 Catherine Dixon presented a font description scheme which nicely combined the historical background of the font (‘sources’) with an eight-facet visual analysis of the typeface (‘formal attributes’). The really clever bit was the layering on ‘patterns’. The afore-mentioned Didone classification is a ‘pattern’ that can be described by a combination of source and formal attributes, thus affording the system a kind of shorthand and backwards compatibility into font classifications. But more importantly, the system enables fonts now, and in the future, to be precisely described and grouped, and whats more its inherently designed to be extensible with the possible addition of new sources, formal attributes and patterns.

But that said, Dixon’s system is still data-centric rather than user-centric, and still only describes what the font looks like. So if you know what visual characteristics you want in a font, and you know what terms like ‘ball terminal’ means then it could be of use; otherwise perhaps not.

I don’t want to design a new font classification system

Categories, taxonomies, classifications are dependant on time, context and target group: what is good for a typographer isn’t the same that’s good for a discerning customer. – Riccardo Sartori

Neither do I want to design a new type description scheme. Want I do want to design is a new way for visual designers to find fonts which specifically suit their needs and the needs of their clients. This means approaching things by way of a user-centred design process.

This is where you come in

As a starting point, I have extracted around forty tags from the hundreds used by foundries to describe their fonts on Fontdeck. The tags I’ve selected deliberately vary from reasonably understandable words like ‘news’, ‘wide’ and ‘romantic’ to more esoteric terminology such as ‘fat face’, ‘monoline’ and ‘spurless’.

Using the splendid tool OptimalSort, I’ve created an online open card sort for these tags. If you’re a web designer or anyone who has a professional interest in fonts, what I’d really like you to do is run the card sort by organising the tags into groups and giving those groups labels. A few keen people have done the exercise already, and on average a full sort is taking 8 minutes. If you are short of time, you don’t need to finish organising all the tags, but please do label all the groups you create. If there are some tags that you simply don’t understand (quite likely) then feel free to leave them unsorted – that’s useful data in itself.

Once I’ve got enough responses to reveal significant patterns, I will stop the exercise and publish the results here, including dendrograms and other UX goodness.

Card sorting is a classic go-to tool for the user experience designer and I’m hoping this research will give clarity to some ideas I’m forming about how to provide better ways for designers to find fonts that meet their specific requirements. Obviously some of that thinking may well end up on Fontdeck, but I’ll continue to publish ideas here beforehand for everyone to consider. I really welcome your thoughts too, especially if you are a designer who finds that current systems don’t help much in the finding of suitable fonts.

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We use jQuery in all of our interactive wireframes to help us quickly try out concepts and define interactions. As Jeffrey Zeldman once wrote, “Wireframing ajax is a bitch”, and here jQuery is very much your friend.

If you know some HTML and CSS, jQuery is pretty quick to get to grips with, but like most technologies, there is still a learning curve and the initial incline, as always, is the hardest to get over. This is where a little guidance from someone who’s been there before comes in really handy. Hence when Jared Spool and the good folk at UIE invited me to give a virtual seminar I jumped at the chance to present the course I wish had been available to me a few years ago: jQuery for UX Designers.

But do we really need another ‘like’ button? My initial thinking was no, and that opinion hasn’t changed yet. Google might have some interesting plans for the data they receive – it may well feed into GoogleRank for a start. Essentially though, this just seems like another attempt by Google to move into the ‘social web’ space and grab some of Facebook’s territory. They’ve failed miserably so far, and I can’t see this helping.

Josh noted that it’s understandable for Google to gather yet more data – it’s their business model and it’s worked well for them so far: knowledge is power. But do we want to give Google more data? There’s an understandable fear around a company having so much influence, but what evil can they inflict once they know what we ‘like’? Perhaps it’s an irrational fear, but it’s good to be cautious when it comes to monopolies.

Harry pointed our that what matters is not the recommendation data itself but who gets to see it. With Facebook, when you ‘like’ something, your recommendation can be seen by your Facebook friends. Let’s think about that for a minute – your Facebook social graph is something you have lovingly curated over many years. Facebook have tried they damnedest to make sure you’ve put in a ridiculous number of hours growing, preening and pruning your friend list. This is why Facebook relatively ‘likes’ are high value.

With Google, your social graph is not something you have personally curated. In typical Google style, they’ve tried to automate the process of social graph creation by mining publicly available friend data on the web – like your Twitter follows and followers – together with the various bits of contact information you have stored within your Google account. If you’re a big Twitter user, a blogger and you use your Google account a lot, then Google’s automated approach will probably work quite well for you right out the gate. But will it work well for normal humans? If Average Joe sees a load of +1s from people he doesn’t care about, it’s just noise. And if he doesn’t see enough +1s, it’s just not useful. And at least with Facebook, he can instantly remedy either issue. With Google, what can he do – sit and wait?

Which is pretty much what we’ll have to do now – sit and wait to see how much traction this gets, and what Google decides to do with the data. As Josh said above (and many people before him) knowledge is power. And so is data, if you’re Google.

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