Yau, CalvinKarimzadeh, MortezaSurakitbanharn, ChittayongElmqvist, NiklasEbert, DavidGleicher, Michael and Viola, Ivan and Leitte, Heike2019-06-022019-06-0220191467-8659https://doi.org/10.1111/cgf.13696https://diglib.eg.org:443/handle/10.1111/cgf13696Communication-minded visualizations are designed to provide their audience-managers, decision-makers, and the public-with new knowledge. Authoring such visualizations effectively is challenging because the audience often lacks the expertise, context, and time that professional analysts have at their disposal to explore and understand datasets. We present a novel summarized line graph visualization technique designed specifically for data analysts to communicate data to decision-makers more effectively and efficiently. Our summarized line graph reduces a large and detailed dataset of multiple quantitative time-series into (1) representative data that provides a quick takeaway of the full dataset; (2) analytical highlights that distinguish specific insights of interest; and (3) a data envelope that summarizes the remaining aggregated data. Our summarized line graph achieved the best overall results when evaluated against line graphs, band graphs, stream graphs, and horizon graphs on four representative tasks.Humancentered computingVisualization techniquesInformation visualization10.1111/cgf.13696375-386