In a world where data is king, data visualization has become increasingly important. Data visualization is a way of making something complex simple, telling a story and removing noise while highlighting useful information and facilitating the creation of new knowledge.
According to Scott Berinato, there are four types of visualizations that “really work”. In order to determine what you are producing; you have to ask yourself whether the information you are presenting is conceptual or data driven and whether you are declaring or exploring an idea. The answer to these questions will generate a visualization that is either idea illustration, idea generation, visual discovery or everyday dataviz.
Coming from a background in psychology, I have always been passionate about connecting to my community and giving back. A way to do this could be by studying current trends and presenting useful information to clients through data visualization. In order to achieve this, I must first understand the type of data that I am trying to convey.
According to Berinato, idea illustration has a clear and simple design and is usually used in presentations to facilitate and simplify learning. I could utilize idea illustration to present therapy concepts to my clients on my social media account. An example of this includes a visualization regarding Sternberg’s Theory of Love in which an “ideal” romantic relationship involves commitment, intimacy and passion. There are multiple variants of these three components as shown in the visualization to the left. It is simple and clearly communicates the concepts postulated by Sternberg.
Idea generation is usually done in informal settings and uses conceptual metaphors. This type of data visualization can be in the form of sketches done in work sessions and benefits greatly from collaboration. I could use an idea generation visualization to brainstorm therapy goals for my clients as well as a way to brainstorm and innovate new marketing ideas to position my private practice on social media.
This type of visualization is the most complex as it deals with big data that is dynamic. It involves trend spotting and deep analysis and may implicate either visual exploration or visual confirmation. In visual exploration, I may not know what I am looking for but be open to new findings while in visual confirmation I may be trying to prove a hypothesis.
I could use visual discovery to assess if my clients are more likely to have a relapse in a certain time of day or period in the year. I work closely with clients struggling with addiction so, in order to do this, I would have to study a great amount of data of relapsing addicts to assess if any trends or interactions are present between different measurable aspects of the addicts life. I could play around with the data and determine whether any trend exists and use these findings to help clients in my practice.
Lastly, everyday dataviz involves analyzing low volume data to generate simple visualizations. Everyday dataviz may assist storytelling in presentations. I could use this, for example. to highlight the increase of substance abuse during the COVID-19 pandemic or exhibit demographic data of visits to my website or social media accounts.
The power of data visualization is undeniable, however, uses vary greatly depending on context and the type of information being presented. If you understand your communication goal and client, it is much more likely you’ll be able to produce an effective visualization, regardless of the market you are in.