Data Visualization Design Concepts

Data visualization designs need to consider some basic concepts. Honesty in presenting data comes first. If you are presenting relationships or correlations, your data must show evidence to support what you are presenting; otherwise, you'd be misleading your audience. Do not convey a message of something that isn't true or focus on facts that do not influence the results. Everyone, specifically a scientist, needs to take trust seriously. People looking at your results are trusting you, they want to take actions based on your findings. Do not lose that trust, combat human psychological bias. Your sole reason to share your research findings should be for others to use and benefit from them. Accessibility is about audiences and their ability to use the visualization. As a scientist, you need to consider who will use the visualizations you produce and how they will be used. Purpose, timing, insights, levels of drill down, speed, simplicity, are examples of other concepts to be considered to make your visualization accessible. Accessibility is, therefore, not sharing; it indeed it is about readability and comprehension. No one wants to see something ugly. I think clarity and beauty have been main goals in every visualization and presentation I have designed. Do not think that spending more time on making your visualization elegant is waste of time. This is not only about data presentation but also your mindset. However, be careful! Elegance shouldn't get in the way of properly interpreting and presenting the data. In short, as my fellow professors at UCSD Dr. Altintas and Dr. Porter say, data visualization needs to be trustworthy, accessible, and elegant.