Information Architecture: A Primer For UX Designers
By: Agile Infoways
Tags: UX Research, Information Architecture, Website Design, Mobile App Design, UX Design

Information Architecture UX design

A well-structured application which makes its operation easier and helps the user to solve their problems is one of the first steps to good UX

Introduction

The purpose of writing this article for UX designers is to enable them to understand (and possibly create) the structure of an application for which they will create wireframes, documentation and so on. Without this understanding, any UX designer is going into a project blind.

Having said this, there is a lot of reading material already available on information and its architecture. This article is meant to make the concept accessible and digestible to most of us. A lot of highly technical concepts have either been simplified or simply excluded in the spirit of keeping this article practical rather than a heavy theoretical discourse.

What is information?

Data is everywhere. Information on the other hand needs to be created, seen and perceived. You can then take information and convert it into knowledge — which means you can do something with this information. As a simple example, data is like taxis roaming around in a city. But which taxi is where? Where is it going? Which area does it operate in? and so on — that is information. You can then take this information and book a taxi to go to a movie — that’s knowledge.

What is information architecture?

Data is scattered. Information is connected. As soon as you start connecting data points, you need to know how to do so — you need a structure, a logic. In the same way, if you want to understand how an existing collection of data is connected, you need structure and logic. This underlying structure is what is information architecture.

Why do you need information architects?

In today’s age of internet and IoT, blockchain development, mobile and web technologies — simply put, in today’s explosion of hardware and software, data gets generated at unbelievable speeds. It is estimated that by 2020, 1.7mb of data will be created per second for every person on earth. If we count 7.5 billion people on earth, we get about 12,159 terabytes of data per second. This brings at least four questions to mind:

How do we sort and contextualize this data?

How do we structure and prioritize this data?

How do we optimize and manage this data?

How do we represent this data in a structure?

An information architect comes in to answer all these (and more) questions.

Let us see how this works. Suppose if we have some data relating to temperature, humidity, altitude and number of people. As we can see, they are already grouped and sorted according to their types. But what is the context in which this data exists? Is this data from a weather satellite, or an IoT sensor set? Unless we mention the context, this data has limited meaning and is practically unusable.

This is data, but is this information?

If we are looking at software for scientists studying the weather, then the temperature and humidity do have an important and usable relation to the altitude, but there is no relation to the number of people at that altitude (unless the number of people is so large that the temperature and humidity get affected…but that is another story).

On the other hand, if we are building an app for an air-conditioning company, then the number of people (in a room) becomes very important. It has a definite and usable relation to temperature, humidity (and perhaps even altitude). So in a specific context, the same data can have different relations and importance.

Let’s go further. We can ask more questions to this data. Is there a range of temperatures — maximum to minimum? Is this today’s data and if so, does it change every day? Does all data change every day?

For the scientists studying the weather, the data may be so dynamic that temperature and humidity may change every few minutes. Low temperatures and high humidity may indicate a possible storm. So they need to decide ‘normal’ and ‘outside normal’ ranges to figure out if everything is ok, or the area needs evacuation.

For the air-conditioning company, the number of people in a room may change every few minutes. So they need to decide ‘normal’ and ‘outside normal’ ranges for the number of people. In both cases, if data falls under ‘normal’, there is nothing much to do. If it is ‘outside normal’, then it is time to act. So even if there are millions of data points, all they need to decide is where each data point falls — normal or outside. This is one way to optimize data and make it manageable.

A further point — if an information architect is planning to use this data to build software, then which data should be shown first, which second and which further? What’s the sequence? If important data is hidden and useless data is shown upfront, the software will be useless. So creating a step-by-step structure in which this data can sit comfortably becomes very important.

As we can see, information architects have a very important job at hand. Let’s look at some practical steps to become an information architect. A word of caution though — the steps below will not make you an expert, but they will definitely give you the basics of how to start.

1. Conducting research for information architecture

Creating an information architecture is a process which requires patience. Never come to hasty conclusions. The architecture itself is an outcome of the process being followed. A meticulous process creates a robust and time-tested architecture. A rushed process will create a feeble architecture.

The first and most important step in the research is to understand:

a. The context

As we saw above, the context defines the core meaning of the data. Without context, any data is potentially meaningless and unusable. The context defines the basis of the information architecture.

b. The users

Each context will have users who have different competencies, skill-sets, tech-savviness and so on. Complex information for a lay-person and over-simplified information for an expert will both end in disaster. Understanding the users defines the simplicity and control value of the information architecture.

c. The intention behind creating the information architecture

The same data can be used for different functions. Data on vehicle locations can be used for tracking their position or for traffic control. Defining the intention guides the way the information architecture will be constructed.

d. The nature of the data at hand

Data can be anything…words, numbers, colors, sounds, pictures and so on. First find out what is the data, how many types, ranges and so on. Identifying these helps categorize the data into different buckets, and decide how the structure will be split.

2. Converting the data into information

Once the core research is done, creating a cohesive and consistent relationship between disparate data points requires great skill. Once this is achieved, the data starts becoming increasingly useful to manipulate through filtering, sorting, searching and so on. It becomes accessible and manageable. You can ask questions to it and get answers. It becomes information. It starts telling you many stories.

3. Organizing information into modules

When the relationships between different points of data start becoming clear, we can also see how closely related data can be clubbed together into chunks. Each chunk becomes capable of telling a useful part of the whole story. Each chunk becomes a module, which can then have sub-modules and so on.

4. Prioritizing the architecture into modules, sub-modules and further

Based on the context and different types of users, the same information architecture can have different priorities. A business owner would need an overview of the business performance, along with overriding access and control on the whole system. His accountant will have specific modules with limited control. A general rule of thumb can be:

System > module > sub-module > single item detail > controls

While a very complex system can have sub-sub-modules and even further, the skill of an information architect lies is keeping this at a minimum, or at least making the system look simple enough to navigate.

5. Testing the architecture for:

a. Simplicity

Simplicity is a very big term and highly contextual. If the amount of information being presented to the user overloads them and they cannot function properly, the architecture needs to be simpler. Conversely, if the amount of information is so less that it starts testing a user’s patience, the architecture is too simple.

Measuring, what is technically called the ‘cognitive load’ on a user helps determine simplicity. For example, ATMs are often rejected in rural areas for being perceived to be too complicated. They prompt the user to do too many actions, overloading them.

b. Accessibility

If the user has to take too many steps for going from the first level of the architecture to the last, then the architecture is not accessible. For example, in a house, if there is a living room leading to a bedroom which has a private area inside which there is a hidden room behind a door, then that room can be a safe room, not a washroom. As another rule of thumb, 3 to 4 steps between the first and last steps of the architecture is good enough.

c. Scalability

As information grows, so do its types and functions. The information architect needs to keep this in mind, explore this possibility in the research phase and then create the architecture. It is impossible for any information architect to fully predict the scale of a system in the future, but adequate research at specific points of the project helps avoid a lot of pain later.

In Conclusion

The crux of the matter is this — the best UI design will eventually fail when the application has a structure which is tedious for a user to navigate. The reason for this is simple — all applications exist because we don’t know techniques to harness our brain potential. They are support mechanisms. They exist to decrease our workload, not increase it.

Today a lot of web and mobile UI and UX design projects skip the crucial step of creating a good information architecture. They look for quick launches in the market. They also fizzle out as quickly as they launch. Thus it is important to remember this saying — it does not matter how you start up; it matters where you end up.