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we can avoid. It's the nature of language and categorization. But such ambiguity begs for aware-
ness.
On one level, when we use words to make places, the map is the territory, the word is the thing,
and language is the environment where experience and exploration occur. But on another level,
that's simply not true. Since understanding arises through the unity of mind, body, and environ-
ment, language can't contain meaning, or to put it poetically, in the words of Hui-neng, the pat-
riarch of Chinese Buddhism:
Truth has nothing to do with words. Truth can be likened to the bright moon in the sky. Words, in this
case, can be likened to a finger. The finger can point to the moon's location. However, the finger is not the
moon. To look at the moon, it is necessary to gaze beyond the finger.
In the systems we design, our words do lots of pointing. They serve as symbols for categories,
concepts, tasks, and content. Words are necessary. They help users find what they need and un-
derstand what they find. But words are never sufficient. Meaning is irretrievably lost in transla-
tion.
Figure 2-12. Words are only fingers pointing to the moon.
As information architects, the first step is awareness of the weakness of words. Once we accept
the limits of language, we go beyond them. The same is true of taxonomy. Every single one is
flawed. Once we admit the problems of ontology, we solve them. Classifications, like colors, ex-
ist on a spectrum. The objective ones - alphabet, numbers, geography - are easy to use but not
always useful. The subjective ones - topic, task, audience - are useful but not so easy. In the
white pages, we can quickly find a friend, but it's impractical to discover a plumber. In the yel-
low pages, we can easily locate a theater, provided it's not called a cinema or drive-in.
The first step in taxonomy construction is defining its purpose. What's the goal? Who are the
users? How will we measure success? But this isn't a linear process. A taxonomy merits Agile,
not Waterfall. To put objectives before ontology is good, but we must also pair classification
with context. Where will the taxonomy exist? What parts will users encounter and when? Will
they touch it on mobile? Will they see it on TV? A taxonomy is part of a cross-channel informa-
tion architecture. To make the whole work, we need a build-measure-learn loop that gets how
the parts fit together.
Simple metrics are seductive. We move t-shirts up a level and look for a sales boost. We test and
refine within-category similarity and cross-category difference, and hope for customer satisfac-
tion. But each taxonomy has many touchpoints. Categories appear in search results, filters, fa-
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