In data visualization, much like in any form of communication, it’s vital to keep the main point front and center. That’s precisely why I’m a proponent of a clean, minimalistic approach to crafting data visuals, coupled with the inclusion of descriptive titles for each graph. These titles aren’t just fluff; they serve as a psychological lever, aiding in persuading your audience of your argument. Moreover, the act of titling forces a second look at the graph to ensure it accurately represents your intended message.
During a recent practical data visualization workshop I led, we tackled creating a graph that illustrated the income inequality in Israel in comparison to OECD countries. In the “before” version of the graph, displayed below on the left, there’s a noticeable redundancy between the title and the Y-axis label. Both essentially echoed each other, added no real value, and worst of all, were obscure to anyone not versed in the jargon of the “Gini Index”.
Our strategy for improvement was straightforward but effective: we swapped the title for the overarching conclusion. This modification was the kickoff for a cascade of enhancements. Yet, we hit a snag with the Gini Index itself—our focal point. Our solution? We underscored the fact that this index is a measure of inequality, clarified its scale (“Higher – more unequal”), and kept the term for those already in the know.
Wrapping up, the derision towards explaining the seemingly obvious, sparked by the “mansplaining” trend, has bled into all areas of communication. However, in the realm of data visualization, clarity and comprehensibility must reign supreme. By making our visual presentations both accessible and elucidatory, we widen the doorway for a more extensive audience to connect with and grasp complex information.
Boris Gorelik 