labelhighlighting

Label highlighting is a user interface technique used in data visualization and labeling tools to make the relationship between visual elements and their textual descriptions more apparent. The technique activates or emphasizes labels in response to user actions such as hovering, selecting, filtering, or focusing on a data point, dataset category, or legend item. The goal is to improve discoverability and reduce misinterpretation.

Common approaches include linking color and typography: the color of a label matches the corresponding data mark, the label is bolded or enlarged on interaction, and legends are synchronized to highlight the active category. Some systems apply subtle glow, outline, or background shading to make the label stand out while keeping other labels subdued. Keyboard and screen-reader accessible mechanisms are often supported by adding focus indicators or textual cues.

Applications span interactive charts, dashboards, and data labeling workflows for machine learning. In labeling tools, label highlighting helps annotators verify which label is being applied and can guide the labeling speed and accuracy. In dashboards, highlighting clarifies the connection between data series and their descriptions during exploration.

Design considerations include accessibility, avoiding color overuse, and maintaining performance with large datasets. It is important to ensure multiple cues (not just color) convey the relationship, and to provide consistent behavior across components. Overuse can cause visual noise or distraction, and color-vision deficiencies should be accounted for with contrast and alternative cues.