We often say that data speaks for itself. This session challenges that assumption. By removing titles, annotations, labels, and context from carefully selected visualizations, participants experience what happens when a chart is left to speak on its own.
The session opens with a fast-paced visual challenge: participants are shown several well-known visualizations with key contextual elements removed (e.g, climate strips) and asked to infer what they represent, setting the stage for a deeper exploration of how we interpret visual information. Sounds easy enough!
Next comes the main challenge. Participants are divided into small teams of 3–4 and introduced to the rules of the game. Each team receives a visualization where the visual marks, colors, chart structure, and creator credits remain intact, but all contextual clues including the title, subtitle, annotations, legend labels, and source narrative have been removed. Working together as data detectives, teams must determine what the chart represents, what the colors or categories signify, the key insight being communicated, and how confident they are in their interpretation on a scale of 1 to 5. (1 = least confident, 5 = most confident). Armed only with visual clues, they observe patterns, develop theories, debate interpretations, and defend their reasoning before the original chart and story are revealed.
With each reveal, the room explores how context changes understanding. Which assumptions were correct? Which were completely off? What role did titles, annotations, and storytelling play in guiding interpretation? The focus is not on getting the right answer, but on uncovering how people make sense of visual information.
By the end of the session, participants will have sharpened their visual literacy, challenged their assumptions, and gained a deeper appreciation for the design choices that transform data into understanding. The result is a lively, discussion-driven experience that turns attendees from chart readers into data detectives.