It might seem odd that one of the forefathers of information architecture would proclaim that everything is intertwingled and thus hard to force down into specific categories, but that’s what Peter Morville is saying. You can’t separate the parts from the whole. Intertwingled: Information Changes Everything is the start of a journey in realizing that, no matter how hard you try to cut apart, partition, chunk, and dissect, most things can’t be broken down without losing something. That won’t stop us from doing it, because we need to do it to simplify our world. However, it may change the way that we approach the process.
The vehicle in our journey is the ability to see everything as a system. There’s an old Tootsie Roll commercial where a jingle is played that ends with “Tootsie Rolls are all I see.” It’s a catchy tune that was designed to get people thinking about Tootsie Rolls, so they couldn’t forget about them. However, there’s some truth in life to this commercial. Once you see something, you can’t un-see it. It’s impossible to not know what a hippopotamus looks like after you’ve seen one. If you’ve learned to see things in systems, it’s hard to un-see them.
For Morville – and for me – everything is a system. It’s a system that can be manipulated, changed, and adapted often with unintended and inexplicable outcomes. Whether you realize that steel axe heads degenerated some aboriginal societies (as in Diffusion of Innovations), you got caught up in Peter Singe’s wildly popular The Fifth Discipline, or you stumbled across the posthumously published book Thinking in Systems by Donella Meadows, once you’ve been infected with the awareness that everything is a system of stocks and flows (inbound and outbound), it’s hard to not see it any longer.
However, just because you can see things in systems doesn’t mean you can predict outcomes. Gary Klein recognized that fire commanders build mental models of the fire where they could predict what is happening. Their Sources of Power may not have been consciously known to them, but they did know when one of their expectations generated by the model was violated, and it was time to go back to the drawing board and try to learn how the system was really functioning.
Wireframes are a stock tool of a user experience designer and of the information architect. These wireframes form the boxes. They’re the pictures of what’s being built. However, what Morville and others have discovered is that it’s what happens between the boxes that is truly interesting. In Understanding Comics, Scott McCloud explains that the story in a comic book happens in the gutter between the frames. In effect, it’s the arrows between the boxes that gives the story its power. It’s what the user fills in themselves that helps the most.
Story is about connecting one frame with the next. That’s why storyboards are an even more powerful tool for designers than the venerable wire frame. Storyboards, which are often used in designing feature films (see Creativity, Inc.), connect the dots and reveal what’s hidden in plain sight in the way of the wireframes.
In fact, agile aligns perfectly with systems thinking, where you do something, observe the results, and then do something else. Sometimes you reverse (or try to reverse) the latest change. Sometimes you head off in a different direction. Ultimately, you’re always making small changes to see how things react, then adapting.
Information architecture – like software development – can take on characteristics of agile or traditional waterfall development. It all depends upon whose hands the tools are wielding the tools. There are some activities that require the development of non-intervention understanding. However, this is not always the case. Good information architecture recognizes that you won’t get it right the first time – or at one time. The needs of users to access content shift as attitudes and options change.
Our memories are fickle things. Our memories aren’t like video recorders accurately storing what happened. Instead, the memories become encoded and reduced into fragments and concepts that we can rearrange when we try to retrieve them. (See Science in Pseudo Science in Clinical Psychology for more on the fallacy of our memories.) Our memories don’t encode words. Instead, we encode concepts and ideas. When we retrieve the memory, we reconstruct the concepts using the words that we have in our current vocabulary.
If you don’t believe me, try to recall a conversation that you had when you were 8-10 years old. Recite the dialogue as you remember it into a recorder. Then go back and review the recording. You’re likely to find that your words weren’t words that you had in your vocabulary back then. Your memories were reconstructed with the help of your current vocabulary.
Words are the way that we create the mental framing that we use for a problem. That’s why the words we use in our taxonomies are so important. They can conjure up the right ideas or ones that don’t connect with our audiences.
They’re called the badlands. Technically, this is a geological term referring to the erosion of clay-rich soil and softer sedentary rocks. However, the connotations of the term “bad” subtly influence millions of people to avoid these beautiful geological features. In this way, labeling an area as “badlands” on a map influences the visitors at Badlands National Park. The hidden connotations of the words we use shape how people see what we’re talking about, for better or for worse.
If I define a category for furniture, I’ll shape the way that people think about the category. They’ll picture in their mind what furniture means. They’ll see a chair, a couch, or a table. (At least 90% of the groups I do this exercise with say these three items.) If I’m looking for a rug, I won’t automatically look in furniture. Similarly, I’ll have a problem looking for a lamp. Is it in electrical or furniture? It has both properties.
So in one sense, a map isn’t a territory – but in another sense, it is, because it shapes that way that we think about the territory.
There is an information architecture problem caused when the categorization labels make it difficult for consumers to decide which path they should follow. One approach to solving this is to use polyhierarchy – having one category included in multiple places in the hierarchy – said differently, having two parent categories for the same category.
While this is a necessary strategy for providing solutions to platypus-type problems (which don’t fit neatly in any one category), it can be an unnecessary crutch used because of poor category selection. Like other tools in the information architecture toolbox, it’s important to know when to use it – and when not to.
The best strategy for managing the problem of things that fall within multiple categories of an existing taxonomy is to use multiple taxonomies. That is, instead of creating one and only one hierarchy of terms, multiple taxonomies are used, each with its own set of terms that can be selected when appropriate – and omitted when not necessary.
With all we know about how the mind works and how we categorize, we still don’t know enough, and we still can’t see enough. Breaking things down into their components so that we can learn about them is a good strategy. (See Efficiency in Learning and The Art of Explanation for more on learning approaches.) However, it’s not a good strategy if we fail to learn how those pieces fit together, how they work together, and how they break the rules when they’re connected to one another. That’s what makes things Intertwingled. They become that way because, when you put the pieces back together, you don’t always get exactly what you would expect. If you’re ready to start your own journey, perhaps it’s time to learn to see the world Intertwingled.
When I explain my passion for information architecture to folks, they often wonder what I’m talking about. They understand intuitively that I’m not talking about designing buildings, but how can you design information? A better way of explaining information architecture is to say it is How to Make Sense of Any Mess. Abby Covert nailed the colloquial definition. In her book, she takes a practical tone to an often academic topic and explains how to make sense of our messes.
I’ve addressed the fuzziness with which our words convey our meaning. Though we have powerful mind-reading skills that allow us to work together, these skills are not perfect (see Mindreading). A single word can have opposite meanings. Words with multiple, different meanings are called homographs. They’re particularly insidious to communication when they have opposite meanings. Consider dust – which can either refer to the act of removing dust or the dust itself. Consider “weather,” which can either mean to withstand a storm or to be worn away.
I know, too, that the way we arrange options can make us what Nudge calls “choice architects.” We can shape the choices that people take by their arrangement. However, the rules for this rely upon the murky depths of subtle cues that we use to make or decisions without knowing we’re making decisions.
The ultimate question for any information architecture effort is “To what end?” That is, who is going to use the information you’re organizing? What are their goals? What is it that you would like them to learn – without knowing it? By answering these questions, you can use the tools you have to create organizations that make it easier for users to find the information they’re looking for.
However, the current users aren’t the only people to be considered when designing the information architecture. Future potential users count, too – particularly when the existing user base is small and you’re trying to make it larger. So, too, do those people who are involved in the outcome of the structure that you’re using – like investors or managers of the departments.
Organizing information isn’t an easy proposition. It’s a process designed to reduce the cognitive load necessary to learn. (See Efficiency in Learning for more on cognitive load.) One might argue that, if we’re speaking about organizing and making sense of messes, what does learning have to do with this seemingly unrelated topic? The answer is that we’re learning to navigate the information jungle to find what we’re looking for. We’re learning how to organize our thinking into more effective patterns. Thus, we’re always learning. Marcia Bates estimates that we absorb 80% of what we know not through formal learning. We just “get” it by experiencing life.
Abby Covert walks us through several diagram types including block diagrams, flow diagrams, Gantt charts, quadrant diagrams, Venn diagrams, swim lanes, hierarchies, mind maps, schematics, and journey maps. Each of these visualizations has different benefits. In software requirements gathering, I use these types of diagrams as well as entity relationship diagrams, activity diagrams, state diagrams, data flow diagrams, and ecosystem maps. The idea is that each type of visualization can quickly relate an aspect of the relationship between entities in ways that the others – and certainly words – cannot.
In designing a taxonomy, there are sometimes some hard choices to be made. In some cases, the users routinely categorize something “incorrectly.” While there’s no right or wrong way to organize things, once you’ve accepted a taxonomy, every item should have its place. A classic example is the tomato. Technically, it’s a fruit, but it’s important to know not to put it in a fruit salad. Most folks recognize that it has vegetable-type qualities when used in cooking. When classifying products in a grocery store, where would you put the tomato? In the technically correct location – where few people would find it initially – or in the incorrect location where it’s findable?
The answer depends on your goals. In the case of a grocery store, the answer may be that you file it with vegetables, because cashiers and shoppers who use self-serve lines expect to find it there. If you’re a college library on botany ,where would you place it, then? Because there’s a different objective, teaching the “correct” locations, you might be inclined to place it in the category of fruit. Of course, people still won’t be able to find it, but then they can be admonished by a professor for not realizing that the tomato is a fruit and not a vegetable.
On the surface, exactitude would be our goal in organizing any mess. After all, if everything has a place, and everything is in its place, then all is right with the universe. However, exactitude costs us flexibility. We can’t put cooking scissors in a drawer labeled spices and expect anyone will find them. Spices is a specific and –relatively speaking – exact label. It means that we don’t have the flexibility to add scissors into the same container. Of course, the ambiguity of “kitchen stuff” is probably broad.
“Kitchen stuff” could be almost anything even – quite literally – the kitchen sink. Cooking stuff may be an alternate category label that restricts the contents some, but not by much. The flexibility offered by ambiguity increases the level of abstraction and reduces navigability.
There’s no answer to how to create the right balance of being ambiguous enough to be accommodating to unexpected events and at the same time exact enough to be clear and valuable. When you err in one direction, you move away from the other.
In the context of How to Make Sense of Any Mess, everything is a mess. At some level, something designed by someone else won’t make perfect sense for us. Things designed by others will at least seem messy to us. Even things that seem like they’re organized today won’t feel organized tomorrow. We don’t have to feel overwhelmed by the mess. Bit by bit, we can make sense of our messes – and try to move things forward. Even if we don’t expect to ever learn how to make sense of our messes, it’s worth learning How to Make Sense of Any Mess.
There are dozens of things that I do each day that I didn’t set out to do. I do accounting and billing work without a desire or intent to do it. I do sales and marketing – and neither are at the top of my list of things to do. I accidentally picked these things up when I decided to be an entrepreneur and run my own company well over a decade ago. Working with taxonomies – and becoming a taxonomist – can happen by accident too. That’s why The Accidental Taxonomist is appropriate for someone looking to learn how to create taxonomies. I’ve never heard a child say, “I want to grow up to be a taxonomist.” Despite this, there are those who have taxonomy as a part of their job – whether they intended it to be or not.
Before I get to the heart of the matter, it’s appropriate to tell you that I didn’t read the book in one sitting. I didn’t read it in a week, a month, or even a year. I started the process of reading The Accidental Taxonomist about half a dozen years ago. It was as I was putting the final touches on my Pluralsight course The Art and Practice of Information Architecture. I got the course done and never finished the book.
In just getting back to it, I felt a bit like some of my clients that struggle to get their taxonomy projects off the ground. Or, rather, my clients that needed to get something accomplished and realized they needed a taxonomy to accomplish their goals. The taxonomy was started, the goals were achieved, and the taxonomy sat aside for a while – sometimes a long while. Before we get too far, we should explain what a taxonomy is.
What is a Taxonomy, Anyway?
Barry Swartz in The Paradox of Choice explains that filtering is one of the basic functions of consciousness. What he doesn’t cover is that so is organization. We’re hardwired to make sense out of our world, and, as Gary Klein explains in Sources of Power, that comes through simplification until we have a model that we can run in our heads. Taxonomies allow us to organize our thoughts and information.
We’re all familiar – willingly or not – with the hierarchical biological taxonomy of zoology. That is to say that we learned Carl Linnaeus’ organization of all animals. We learned Kingdom, Phylum, Class, Order, Family, Genus, and Species as a way for differentiating one animal from another and identifying their nearest cousins.
We also learned, but most of us promptly forgot, how Melvin Dewey organized his library. The system of organization held a brilliant discovery for extension. He figured out that he could make his system flexible and allow for increasing levels of detail through the use of a numbering system.
We probably never learned about S.R. Ranganathan’s different approach to classification. He was frustrated that things could only be placed in one spot. There was in effect one “right” way to find things. His insight was to introduce facets. Instead of trying to capture the uniqueness of any given item in a single hierarchical dimension, he proposed that items be classified in several different categories, or facets, and the combination of these facets would be how the item was classified. This approach was called colon classification, because he chose the colon to separate the various facets.
I include Ranganathan’s system to point out that taxonomies are about organization. They’re not about hierarchy, though that is often the way they’re executed. They’re not about books or animals. Taxonomies are, at their core, about how we make sense of this world that is far too complex for our minds to process.
I remember first “discovering” the thesaurus in grade school. You could make your writing sound more impressive by looking up words that no one knew. I could take a simple, common, everyday word and replace it with something more profound and meaningful. (Perhaps I even looked up the word profound.) To me at the time, thesaurus only meant synonyms. I could find words with similar definitions. Eventually, I found the antonyms. However, for the better part of 30 years, that’s all they were.
When I started diving into information architecture and how we organize information in ways designed to make them easier to access, I realized that my old friend the thesaurus was more powerful than I had given her credit for. More than just synonyms and antonyms, the thesaurus contained the relationships between words. Where a dictionary can tell you what meanings are associated with a word, it’s the thesaurus that can put the word on the map in relationship to other words.
Understanding which words had broader and narrower meanings allows you to respond with precision words that encapsulate the exact scope that you wish to cover. There can be alternative spellings to help you understand how there might be multiple different ways to spell a word – such as color and colour. The thesaurus had more to offer than I had anticipated.
The role of a thesaurus in an organization is even more powerful. Inside the context of an organization, a thesaurus can identify preferred terms over terms that are less preferred. They can share common misspellings. They can define terms across languages. They can translate the scientific to the everyday – and vice versa.
An organization’s taxonomy provides a map of the terms that are used in the organization and notes about how those terms are used – or are intended to be used. They provide the basic relationships between the terms. When the relationships get more complex, then we’ve moved from the world of thesaurus into the world of ontology.
In a thesaurus, the focus is on words. They make up the tent poles on which the relationships are hung. However, ontologies focus much more on the relationships between words and the nuances of these relationships than the words themselves. Instead of being focused on the tent, ontologies are focused on the net that keeps circus workers safe. It’s not the individual ropes – or words – that keep performers safe. It’s the relationship and connection between the words that keep performers from falling.
Ontologies are a way of understanding a field of study or knowledge. Ontologies provide a rich map of how things in the field are connected to one another. The relationships are richer than simply one term being broader or narrower than another.
If an organization organizes their content through a taxonomy in the form of a thesaurus and a set of ontologies, why do we call the role a taxonomist? At the root, it’s the development of an organizational structure – irrespective of which tools are used – that defines the core behaviors of a taxonomist. Their role is to organize and make easier to access information. The tools they use are just the tools of the trade.
The funny thing is that many taxonomists – but not all – aren’t in full-time roles. Few taxonomists have it in their title, though some have it in their job description. It’s more common to have taxonomy development as a prerequisite for something the role requires, so often the taxonomist isn’t a person who spends all day organizing structures. Most of the time, the taxonomist is someone who has a job to do that is made better by taxonomic development.
If categorization and organization is a part of the basic functioning of consciousness, then shouldn’t everyone be considered a taxonomist? At some level, yes. However, what differentiates every man from the taxonomist is in the tools that they’ve developed for clarifying, codifying, and communicating what the structure of organization is. By learning what humanity knows about psychology, neurology, and the organization of large information, taxonomists can distinguish their capabilities.
While these aren’t likely enough for a taxonomist to feel truly confident in every situation, this knowledge and these skills are useful.
A taxonomy’s purpose is to help organize content, that’s easy. However, taxonomies provide structure and framing that shapes the way that people think. As a result, taxonomies are more than just a way to browse to the information you want. Taxonomies can be helpful in shifting the way the organization works.
Sometimes this is through the inclusion of detailed terms in a hierarchy to encourage users to be more specific about what they mean. Other times, it might be through the use of preferred terms. Preferred terms in the taxonomy can shift the thinking from package delivery to package assurance. It’s a subtle shift that focuses the corporate consciousness on assuring shippers and recipients that their package will make it to their destination.
Atoms have a challenge that they can only exist in one place at a time. However, in our electronic taxonomies, we can put things into more than one place in the taxonomic tree. Consider a color taxonomy that starts with a level of red, blue, and green. Where does the second-level color blue-green belong? Blue sure, but green as well. This is a polyhierarchy, where an item has multiple parents. While logically this seems like the exception, polyhierarchies are more common than most would like to admit.
The truth is that taxonomy projects are messy. It’s only a matter of time before you’re going to run across the digital equivalent of a platypus. The platypus has a mixture of reptilian, avian, and mammalian genes. It’s a classic challenge for the zoological taxonomy that splits reptiles, birds, and mammals all the way at the top. With a polyhierarchy, the platypus can find its place in all three taxonomies.
Being a taxonomist solves only one part of the puzzle. Taxonomists create the structures, but it’s often up to others to tag the content to fit into the taxonomy. This split means that, in many cases, the taxonomist must make a point to sit with those who are actually doing the categorization to understand what is and isn’t working. Similarly, they should sit with users who are actually trying to find the information.
The key challenge in taxonomic development isn’t in designing the taxonomy. The key challenge is getting the users – who are often not dedicated indexers – to enter the metadata necessary to make the taxonomy work. Too many taxonomy projects are abandoned before the work really gets started, because the people indexing the content refuse to do it.
There are tricks that can be used to improve results. Search can aggregate terms by leveraging synonyms even if the users aren’t always using the preferred term. Facets can go a long way to simplifying the search process, and full-text indexing makes some level of taxonomic identification unnecessary. Automatic classifiers – whether rules or machine learning-based – can help the content get the correct metadata with minimal help from the indexers.
With all this mess, it’s hard to keep track of when the metadata is known and to judge its reliability. Whether it’s entered at or near the time of creation in the form of pre-coordination or it’s managed through the searching process, getting it right is hard. Maybe you find that you’re not getting the findability that you want, so to fix the problem, you’re going to become The Accidental Taxonomist. Perhaps a quick read can give you tips that will make the process easier and less painful.