Content Types
Data is the supportive brick for any presentation or report out there. It offers bits of reality that together form an accurate image.
Without data, marketers would create their campaigns on assumptions and suppositions, instead of knowing exactly what their clients want. Not to mention engineers would construct only hazardous buildings from the beginning. Even consumers need data to know how to use their new products accordingly.
Despite its ubiquitous nature, technical data is still seen as cold and flat. Here are a few tips on how to communicate technical information simply and beautifully through content and design.
RELATED: Expert Tips on How to Grab Attention With Your Data Visualizations
There are four types of learning styles, which are visual, auditory, read-write, and kinesthetic. This means that we all understand information in different ways. People usually have one predominant style, but they need the other three too to assimilate a complex image of the new content.
Visual data can combine almost all learning styles to obtain a comprehensive scheme. A 1998 study discovered that people have the capacity to remember images better than words. That is because people should read one line at a time. On the other hand, images can be comprehended with just a glance. Writers need entire pages to describe a scene. However, one image can contain all details at the same time.
Visual data is not all about images. It is about finding a way to connect two elements that in a text would appear unrelated. Once the information is clearly categorized, the visual elements can come in to represent pieces of content. Once each of them receives a form of its own, it is easy to work with them.
Data interpreters can create scenarios true to life and use geographical orientation to find a connection between two seemingly foreign elements. Geographical orientation will enable you to find a link between two points exactly like people do in geometry. Texts cannot give you a spatial interpretation, and data can remain hidden behind context.
For example, architects use data visualization to assign each real element with a visual interpretation. Instead of the word “wall,” they draw a line. Instead of using the word “window,” they draw a second line against a wall. Each element receives its own interpretation in the world of design and becomes a symbol.
By reducing complex images to simple lines and dots, architects can easily discover certain connections. So, the job of an architect does not only require design skills, but also extensive problem solving capabilities, and we all know how much architects make.
People learn through assimilation. We take a completely unknown notion and place it in its rightful location in this world. We need to understand its meaning and its relationship with the things and notions we already know. For example, when we learn a new language, we assimilate each word with an object or phenomenon from reality.
The more concise and clear our lessons are, the more quickly we learn them. Our human nature demands us to find a logic or reason behind the unknown. Therefore, the prehistoric era found the cause of strange natural phenomena like thunder or rain as the power of gods. We all know that behind these effects is science and we learned its connection to weather.
So, to create an easily digestible technical data representation, we need structure. The new information must follow a logical course. Without this organization, there are going to be just some random numbers and phrases.
To create simplicity, your technical data needs organization. People need a logical beginning, middle, and end to understand and grasp new notions. Thus, any clear visual data should respect one of the five logical structures:
Without these structures, there would be a compact mass of infinite data. The world functions on complex rules and equations, and one lifetime is not enough to master them all.
But people don’t need to know everything. By structuring a precise topic in a logical structure, you deliver meaning to their subjects of interest.
Simplicity and structure are not enough to support effective visual data by themselves. They need the help of a common goal. What’s the purpose of the report? To what problem does the data provide a solution? Thus, any technical content should work towards one or several of the following functions:
Now that we've covered the importance of simplicity in communicating technical information, it is time to integrate data visualization into beautifully designed graphics. There are many ways to bestow data with visual elements and meaning. The following is a complex list of visualization types that can structure data in logical and accurate graphics.
This single dimensional structure can be defined by what we know of lists of items. While this is the most used type of visual, it certainly lacks depth. The viewers are unable to perform logical correlations, and the connections between its items remain hidden behind the absence of multidimensional agents.
This is a comprehensive type of graphics that relies on geographical interpretations. Its main aim is to synthesize the data that describe a real area such as a country, city, or neighborhood. There are several ways to unlock the potential of planar visualization that can even lead to interactive maps.
This type of visualization offers extensive methods to represent the data recorded in three dimensions, which are length, width, and height.
This is the perfect visualization style that enables viewers to understand connections in space. It is easy to find unique angles and combinations of data elements that would have remained otherwise unseen in 2D or 1D representations.
The most complex data visualization offers the most comprehensive solutions. It is difficult to remain relevant in the realm of multi-dimensions. However, the end result will turn complicated structures into simple graphics.
From here on, it is quite simple to relate the elements between them and understand how they work together as a whole.
All in all, the effectiveness of technical data depends on simplicity and visual representation. Simplicity means structuring data in a certain manner so that it serves one single goal.
Beauty and visual representations are vital to encourage viewers to understand the system described by numbers and other records. Once the users are educated on a certain topic, the data would have served its purpose entirely.
If you're wondering whether it takes advanced expertise--and even a data science degree--to create these kinds of data visualizations, there are also plenty of easy-to-use information design tools for beginners that can help you create interactive charts, graphs and infographics within minutes.
One option you can try is Visme, an all-in-one visual content creation tool. Click here to try it for free.
And if you have any information design tips and advice of your own on how to communicate technical information to non-technical audiences, don't hesitate to drop us a line in the comments section below.
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About the Author
Amanda Wilks is a Boston University graduate and a Digital Marketing Strategist. She has a great interest in everything related to content marketing, online marketing and corporate and personal branding.