Data visualization is an important part of content because it allows an audience to easily consume and interpret information. With that in mind, data visualization must be accurate and stylish. What good is any design if it does not thoroughly represent its subject or appeal to the intended audience?
Accurate visual representation is important because it can be done in various forms from animations, still images, and interactive media. The goal is to make complex data much simpler to understand. Data visualization must include some key and some standard of measurement. If a bar chart was to display the number of people who attended an event on different days. The x-axis and y-axis must display the appropriate values. However, these values need to be displayed accurately. Each measurement must remain consistent. This is nothing complex to grasp; all designers need to do is ensure that the visual representation is aesthetically pleasing and accurate.
When it comes to content, the priority of accurate data representation can slip under the radar, usually putting aesthetics over everything else. But this is actually a harmful way of presenting data. Even if values are clearly visible, the design can mislead individuals with the data presented. It’s as if you are nodding your head “yes”, but you are saying “no”.
Simply put, it is confusing and misrepresents what is intended. Whether or not this is an intentional distortion, this is an unethical practice. Content that is intended to provide data representation is doing so with the intention of representing facts. By not representing it factually, it is akin to writing misleading sentences.
It’s easy to think that having the values visible and a rough estimation of a chart should be enough to get the point across, but accurate visual cues help people to process information faster. The numbers they see are logically processed but the visual cue gives them a comparison that reinforces the values. It makes a point more effective, but in cases where information is roughly scanned (which happens more often than we like it to), it makes data processing much easier and quicker.
When divulging technical information, it is a content creator’s job to ensure that it is easily understandable and cannot be misleading. No one enjoys a book that is written to be confusing.
