English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Although visualization tools are widely available and accessible, noteveryone knows the best practices and guidelines for creating accurate andhonest visual representations of data. Numerous books and articles have beenwritten to expose the misleading potential of poorly constructed charts andteach people how to avoid being deceived by them or making their own mistakes.These readings use various rhetorical devices to explain the concepts to theirreaders. In our analysis of a collection of books, online materials, and adesign workshop, we identified six common explanation methods. To assess theeffectiveness of these methods, we conducted two crowdsourced studies (eachwith N = 125) to evaluate their ability to teach and persuade people to makedesign changes. In addition to these existing methods, we brought in the ideaof Explorable Explanations, which allows readers to experiment with differentchart settings and observe how the changes are reflected in the visualization.While we did not find significant differences across explanation methods, theresults of our experiments indicate that, following the exposure to theexplanations, the participants showed improved proficiency in identifyingdeceptive charts and were more receptive to proposed alterations of thevisualization design. We discovered that participants were willing to acceptmore than 60% of the proposed adjustments in the persuasiveness assessment.Nevertheless, we found no significant differences among different explanationmethods in convincing participants to accept the modifications.

Why Change My Design: Explaining Poorly Constructed Visualization Designs with Explorable Explanations