Visualization Guardrails: Designing Interventions Against Cherry-Picking in Interactive Data Explorers
Maxim Lisnic, Zach Tyler Cutler, Marina Kogan, Alexander Lex · 2025
The growing popularity of interactive time series exploration platforms has made data visualizationmore accessible to the public. However, the ease of creating polished charts with preloaded dataalso enables selective information presentation, often resulting in biased or misleading visualizations.Research shows that these tools have been used to spread misinformation, particularly in areas likepublic health and economic policies during the COVID-19 pandemic. Post-hoc fact-checking may beineffective because it typically addresses only a portion of misleading posts and comes too late tocurb the spread. In this work, we explore using visualization design to counteract cherry-picking, acommon tactic in deceptive visualizations. We propose a design space of guardrails—interventionsto expose cherry-picking in time-series explorers. Through three crowd-sourced experiments, wedemonstrate that guardrails, particularly those superimposing data, can encourage skepticism, thoughwith some limitations. We provide recommendations for developing more effective visualizationguardrails.