Showing the right story: how to design scientific visualizations for effective research communication

Meta-research aims to distill large bodies of scientific evidence into clear, actionable insights that can guide future studies, policy decisions, and research priorities. In an era where the volume of published work is rapidly expanding and researchers face increasing time constraints, effective visualization becomes essential, not just to summarize findings, but to make them usable. Without careful design, important aspects such as variability across studies, uncertainty, or potential bias can be lost, leading to oversimplified or even misleading interpretations.

This talk focuses on how to translate complex evidence syntheses into visuals that support accurate understanding and informed decision-making. Widely used approaches for presenting meta-analytic results will be examined, alongside more advanced techniques that help reveal patterns across large and diverse datasets. Attention will be given to how visual choices influence interpretation, especially when dealing with heterogeneity, study quality, and the structure of the available evidence.

By combining practical examples with design considerations, the session highlights strategies for balancing completeness with clarity. The goal is to demonstrate how well-crafted visuals can turn dense collections of studies into coherent narratives that are both scientifically rigorous and accessible. Attendees will gain concrete ideas for improving how they present synthesized evidence, making their findings easier to interpret, compare, and apply in real-world contexts.