How to develop a taxonomy for your information architecture
When I first heard the word ‘taxonomy’, I had no idea what it meant. I remember enthusiastically nodding my head at my boss about how awesome it is while frantically Googling it under the table. We’ve all been there early on in our careers. Although, what I found left me feeling even more confused — something about classifying animals? Whether you’re as confused as I was all those years ago or just in need of a refresher, this quick guide to all things taxonomy will sort you out.
What is a taxonomy in information architecture?
In information architecture, taxonomy refers to how information is grouped, classified and labeled within a shared information environment. The overarching structure of that shared information environment is the information architecture (IA) and we find our way around it using the navigation. Think of an IA as a house. The taxonomy determines which pieces of furniture belong in each room and we navigate around the house via doorways and hallways. It all fits together to create one shared environment.
For a website architecture example, think of an online shoe store. The shoes might be organized and labelled by color, size, style, season or collection — that’s the taxonomy. The overall picture of where those groups of shoes live is the IA and in our pursuit of new shoes, we might navigate that structure via a navigation bar at the top of the page. In the amazing Grand Taxonomy of Rap Names visualization below, we can see how the information is categorized, connected and labeled through the lines and the colors. There’s no structure or hierarchy to it yet; that would be the next step in the process to build the IA.
There are so many different ways to carve information up into a taxonomy and the key drivers for determining that are your content and, of course, your users. Your taxonomy needs to make sense to your users.You may be starting from scratch with a new website or you may have inherited a taxonomy that for whatever reason just isn’t fit for purpose. The first step when creating an initial taxonomy is to do a comprehensive audit of your content. Ask yourself, is your content relevant? Is it up-to-date? Is it all necessary? Are there opportunities to delete or condense content? Once you have your content sorted, you’re ready to move on to the next step of running a card sort with users.Running a card sort early in your taxonomy creation process will allow you to build it up from an evidence based foundation. There’s no point guessing then testing and potentially going back to square one, when you can co-create with your users and then test that informed approach to validate and further evolve your thinking.When you’re designing your card sort, you’ll need to decide if you’re going to do an open, closed or hybrid sort. Here’s a very high level look at what each type involves:
Open: participants sort cards into groups and name their own categories
Closed: participants sort cards into categories determined by you
Hybrid: participants sort cards into categories determined by you AND they can also make up their own.
This early in the taxonomy creation process, it’s best to start out with an open card sort. Not only will this tell you how your users expect your content to be grouped, but will also provide insight into the language and labels that they would expect that content to be associated with. You never know, an open card sort may even surface something you hadn’t considered. At this stage of the process, it’s important to be open to ideas and new possibilities and an open card sort will do just that.Once you’ve settled on the type of card sort you’ll be running, you’ll need to test which can be done through a tool such as Optimal Workshop’s OptimalSort. OptimalSort enables you to run unmoderated card sorts remotely (or print out cards for a moderated/in-person card sort!). After your participants have completed your card sort, you can access the benefits of OptimalSort’s powerful result analysis functions.
After you’ve run your initial open card sort with users, you should have everything you need to create the first iteration of your taxonomy. Consider everything you learned during the card sort and cross reference that with your business goals and any tech constraints you might be facing. Don’t stress too much about nailing it this time around — remember this is the first iteration and as you test more and learn more, you can make changes. Build out your taxonomy in Post-it notes with a team and then whack it into a spreadsheet to make future testing and iteration activities easier.
How to test a taxonomy
Now that you have the first iteration of your taxonomy, it’s time to have a go at structuring those groups into an IA and running a tree test. A tree test works like a card sort but in reverse — it allows you to test your thinking by working backwards. Optimal Workshop’s Treejack is an online tree testing tool that helps you assess the findability of your content without any visual design elements. All you need are clear objectives for what you’d like to learn more about and a spreadsheet version of your draft IA (told you it would come in handy! ).
Another way to test your taxonomy thinking is to run another card sort. However this time, a hybrid or a closed card sort might be more suitable. A closed card sort would be useful if you’ve got evidence to suggest that your group labels are making sense to users but you’re not 100% sure what belongs in each group. A hybrid sort will let you go one step further and tell you if your content does in fact fit within those labels and if not you’ll also pick up some new ideas to iterate your taxonomy further.
Developing a taxonomy is like any other design process. Bring users into your process as early as you can and never stop iterating, improving and learning.Oh, and about those animals — I wasn’t entirely wrong. The way we classify animals (e.g., vertebrates and invertebrates) is a taxonomy. There are taxonomies everywhere and they’re not all digital. From libraries to supermarkets, we are immersed in taxonomies. It's the role of information architects to determine how these taxonomies are presented to us and how we navigate through them — the possibilities are truly endless!
Further reading
"What is information architecture" — a guide we created to help people learn more about information architecture, including stuff for beginners and those who are more advanced.
"An introduction to taxonomies" — an article from UXBooth's Sarah Khan that details what taxonomies are, taxonomy displays and more.
According to Abby Covert, author, teacher and community leader in the field of information architecture (IA) : ‘IA is the way we arrange pieces of content to make sense when experienced as a whole. By this definition: there is information architecture in everything. Mindblown?’
😮 (That’s a resounding yes from an IA rookie like me.)
In this issue of CRUX we go in search of information architecture and have some surprising encounters in the worlds of emoji, elevators, walking tracks, games and more. We meet UX designers, developers, researchers and even a Senior Park Ranger. It seems you can have your ‘IA hat’ on without even realising it. That’s the power of information architecture.
Some highlights from this issue:
UX research and strategy specialist, Q Walker explores the world of emoji from an information architecture perspective and sparks curiosity along the way. Have you ever wondered why clock emojis are organized under travel and places? 🤔
We talk to Senior Park Ranger David Rogers about the thinking behind creating and building New Zealand’s national walking track network and reveal how information architecture can also live ‘in the wild’.
UX developer Ben Chapman delves into the classification systems of libraries over time and ponders the pros and cons for users of moving information online.
We talk to Sam Cope, Lead UX Designer at Wētā Workshop’s Interactive division about what it takes to drive design decisions with the end user in mind - something crucial for any video game’s success, whether it’s a blockbuster or something more niche.
And much more about information architecture in unexpected places….
The stories and people in this issue of CRUX certainly captured our imagination and attention - we hope they inspire and even surprise you too.
Do you have a burning idea to share or a conversation you’re dying to kickstart that’s of interest to the world of UX? Now’s your chance. We’re already on the lookout for contributors for our next edition of CRUX for 2022. To find out more please drop us a line.
When I first heard the word ‘taxonomy’, I had no idea what it meant. I remember enthusiastically nodding my head at my boss about how awesome it is while frantically Googling it under the table. We’ve all been there early on in our careers. Although, what I found left me feeling even more confused — something about classifying animals? Whether you’re as confused as I was all those years ago or just in need of a refresher, this quick guide to all things taxonomy will sort you out.
What is a taxonomy in information architecture?
In information architecture, taxonomy refers to how information is grouped, classified and labeled within a shared information environment. The overarching structure of that shared information environment is the information architecture (IA) and we find our way around it using the navigation. Think of an IA as a house. The taxonomy determines which pieces of furniture belong in each room and we navigate around the house via doorways and hallways. It all fits together to create one shared environment.
For a website architecture example, think of an online shoe store. The shoes might be organized and labelled by color, size, style, season or collection — that’s the taxonomy. The overall picture of where those groups of shoes live is the IA and in our pursuit of new shoes, we might navigate that structure via a navigation bar at the top of the page. In the amazing Grand Taxonomy of Rap Names visualization below, we can see how the information is categorized, connected and labeled through the lines and the colors. There’s no structure or hierarchy to it yet; that would be the next step in the process to build the IA.
There are so many different ways to carve information up into a taxonomy and the key drivers for determining that are your content and, of course, your users. Your taxonomy needs to make sense to your users.You may be starting from scratch with a new website or you may have inherited a taxonomy that for whatever reason just isn’t fit for purpose. The first step when creating an initial taxonomy is to do a comprehensive audit of your content. Ask yourself, is your content relevant? Is it up-to-date? Is it all necessary? Are there opportunities to delete or condense content? Once you have your content sorted, you’re ready to move on to the next step of running a card sort with users.Running a card sort early in your taxonomy creation process will allow you to build it up from an evidence based foundation. There’s no point guessing then testing and potentially going back to square one, when you can co-create with your users and then test that informed approach to validate and further evolve your thinking.When you’re designing your card sort, you’ll need to decide if you’re going to do an open, closed or hybrid sort. Here’s a very high level look at what each type involves:
Open: participants sort cards into groups and name their own categories
Closed: participants sort cards into categories determined by you
Hybrid: participants sort cards into categories determined by you AND they can also make up their own.
This early in the taxonomy creation process, it’s best to start out with an open card sort. Not only will this tell you how your users expect your content to be grouped, but will also provide insight into the language and labels that they would expect that content to be associated with. You never know, an open card sort may even surface something you hadn’t considered. At this stage of the process, it’s important to be open to ideas and new possibilities and an open card sort will do just that.Once you’ve settled on the type of card sort you’ll be running, you’ll need to test which can be done through a tool such as Optimal Workshop’s OptimalSort. OptimalSort enables you to run unmoderated card sorts remotely (or print out cards for a moderated/in-person card sort!). After your participants have completed your card sort, you can access the benefits of OptimalSort’s powerful result analysis functions.
After you’ve run your initial open card sort with users, you should have everything you need to create the first iteration of your taxonomy. Consider everything you learned during the card sort and cross reference that with your business goals and any tech constraints you might be facing. Don’t stress too much about nailing it this time around — remember this is the first iteration and as you test more and learn more, you can make changes. Build out your taxonomy in Post-it notes with a team and then whack it into a spreadsheet to make future testing and iteration activities easier.
How to test a taxonomy
Now that you have the first iteration of your taxonomy, it’s time to have a go at structuring those groups into an IA and running a tree test. A tree test works like a card sort but in reverse — it allows you to test your thinking by working backwards. Optimal Workshop’s Treejack is an online tree testing tool that helps you assess the findability of your content without any visual design elements. All you need are clear objectives for what you’d like to learn more about and a spreadsheet version of your draft IA (told you it would come in handy! ).
Another way to test your taxonomy thinking is to run another card sort. However this time, a hybrid or a closed card sort might be more suitable. A closed card sort would be useful if you’ve got evidence to suggest that your group labels are making sense to users but you’re not 100% sure what belongs in each group. A hybrid sort will let you go one step further and tell you if your content does in fact fit within those labels and if not you’ll also pick up some new ideas to iterate your taxonomy further.
Developing a taxonomy is like any other design process. Bring users into your process as early as you can and never stop iterating, improving and learning.Oh, and about those animals — I wasn’t entirely wrong. The way we classify animals (e.g., vertebrates and invertebrates) is a taxonomy. There are taxonomies everywhere and they’re not all digital. From libraries to supermarkets, we are immersed in taxonomies. It's the role of information architects to determine how these taxonomies are presented to us and how we navigate through them — the possibilities are truly endless!
Further reading
"What is information architecture" — a guide we created to help people learn more about information architecture, including stuff for beginners and those who are more advanced.
"An introduction to taxonomies" — an article from UXBooth's Sarah Khan that details what taxonomies are, taxonomy displays and more.
As information professionals, we work with the “stuff” of information in our everyday work. We search for information, we spend time analyzing and synthesizing it, and we carefully create and structure it. Whether you elicit information from users and stakeholders, explore large data sets, design ‘journeys’ or interfaces, or create information architectures, understanding the information you are using and creating as information can help you do your work better.
Kat King, Business Intelligence Analyst at the University of Michigan Library, recently spoke at UX New Zealand, the leading UX and IA conference in New Zealand hosted by Optimal Workshop, about understanding exactly what information is, and where it is, in our work.
In her talk, Kat uses simple examples to teach you to “see” the information around you and understand what makes something “information” in the context of working as a human to accomplish something.
Kat King bio 🎤
Kat King is an Information Architect interested in language, meaning, and the things we make. She currently works as a Business Intelligence Analyst for the University of Michigan Library.
Information theory can be dense and jargon-filled, and discussions in academic texts can feel divorced from the practice of actually working with information. We’re all told that information architecture is much more than website navigation. So, what is it? IA has a reputation for being difficult to understand, and in her talk, Kat attempts to help us understand what it is, where the information is, and what is it that we’re doing when we use IA methods.
Kat defines IA as “the practice of ensuring ontological alignment”. ‘Ontological’ relates to concepts, categories, properties, and relationships. ‘Alignment’ means arrangements into appropriate relative positions. Therefore, information architecture is “the practice of ensuring concepts, categories and their properties and relationships are arranged into appropriate relative positions.”
To align information then, you need to begin by sorting it into concepts and categories, which is difficult because information can sometimes be “slippery and abstract”. Kat argues this is the real reason that IA is sometimes hard to wrap our heads around. So, getting to the heart of the question, what is information?
Kat defines information as “a patterned relationship between differences that reduces uncertainty”. The key word here is ‘differences’. The trick to understanding and taming information is to identify what is different about sets of information. The next trick is to identify consistencies between these differences.
This can be a little confusing, so Kat uses the example of picking fruit. We tend to use color (the difference) to identify when fruit is ripe and sweet. We know for a fact that, at some point, the fruit will be at its sweetest and, while there is a scientific way of identifying this point, we have to use the information we have at our disposal instead i.e. the colour of the fruit. The skin of the fruit in this example is like an interface - allowing a flow of information from the fruit’s ripening process to our eyes.
Information categories 🧺🧺🧺
The relationship between the information described in the fruit example can be split into two categories. “Information 1” is a factual, objective description of when the fruit is ripe (i.e. the science of why the fruit is the color that it is right now), whereas our subjective observation, based on color, is “Information 2”.
Information 1: Matter and energy, and their properties and interactions i.e. the laws of physics and universal truth or rules
Information 1 poses challenges for us because we have a narrow range of perception, attention, and aggregation, which means we, as humans, can’t possibly understand the laws of nature just by observing. We have evolved to be simple, efficient observers of what is important to us. In other words, we don’t need to understand everything in order to get things right. We see patterns and generalize. Going back to the fruit example – we only need to know the color of ripe fruit, not the exact chemistry of why it is ripe.
Information 2: This is Information 1 that is given meaning by humans. This is done via processing semantic information, or “differences and structures that create meaning for people”.
We use semantic information by processing concepts, patterns, categories, mental models, and even language as inputs to form our understanding. As social animals, we tend to reinforce general ‘truths’ about things because we’re constantly cooperating using shared information. General ‘truths’ are good enough.
Kat uses the following interaction to demonstrate the interplay of different information.
Person 1: If the raspberries look good, can you get some for me?
Person 2: How can tell is they’re good?
Person 1: Get the ones that are the most red.
In this interaction, the different pieces of information can be broken down by category:
Semantic information = Words and concepts
Information 1 = Meaningful signs
Information 2 = Perceptible differences
Real life information = Raspberries
Using our ability to communicate and understand concepts (words “red”, “good”, and “raspberries”) helps us to understand Information 2 (processing the words and concepts to understand that a red berry is good”), which aligns with Information 1 (the evolutionary science and ongoing consistency of red/ripe berries being sweet) that helps us decide when processing all of this information.
So, now that we understand a little more about information, how does this influence our roles as designers?
Why it matters 👀
Thanks to our individual lived experiences, people have many different inputs/concepts about things. However, Kat points out that we’re pretty good at navigating these different concepts/inputs.
Take conversations, for example. Conversations are our way of getting a “live” alignment of information. If we’re not on the same page we can ask each other questions to ensure we’re communicating semantic information accurately.
When we start to think about technology and digital products, the interfaces that we design and code become the information that is being transmitted, rather than words in a conversation. The design and presentation become semantic information structures, helping someone to understand the information we’re putting forward. This highlights the importance of aligning the interface (structure and semantic information) and the users' ontology (concepts and categories). For the interface to work, IA practitioners and designers need to know what most people understand to be true when they interact with information, concepts, and categories.
We need to find some sort of stability that means that most users can understand what they need to do to achieve a goal or make a decision. To do this, we need to find common ground between the semantic information (that might vary between users) so that users can have successful Information 2 style interactions (i.e. absorbing and understanding the concepts presented by the interface).
To wrap up, let’s remind ourselves that information architecture is “the practice of ensuring concepts, categories and their properties and relations are arranged into appropriate and relevant positions”. As IA practitioners and designers, it’s our job to ensure that concepts and categories are arranged in structures that can be understood by the nuance of shared human understanding and semantic information – not just in some physical diagram.
We need to present stable, local structures that help to reduce uncertainty at the moment of interaction. If we don’t, the information flow breaks and we aren’t reducing uncertainty; instead, we create confusion and disappointing user interactions with our digital products. Making sure we present information correctly is important (and difficult!) for the success of our products – and for better or worse, it’s the work of information architecture!
