Case ID: M22-067P^

Published: 2023-01-04 09:42:26

Last Updated: 1677136438


Arlen Fan
Yuxin Ma
Ross Maciejewski

Technology categories

Computing & Information TechnologyPhysical Science

Technology keywords

PS-Computing and Information Technology

Licensing Contacts

Physical Sciences Team

Annotating Line Charts in the Wild

­Charts and data graphics have been widely used for communicating dense amounts of numerical information and are a preferred way to view data in many types of documents.  Charts can be found in all mass news sources, from television channels to periodicals and are used to assist in storytelling.  Such visualizations have become increasingly popular due to the development of easy-to-access tools for creating them.  However, the increased ease of visualization construction brings new challenges.  Ideally, designers who craft visualizations are considered to be objective, unbiased, and immune to deliberate manipulations.  However, there have been many cases where chart designers violate key design principles and alter the reader’s understanding of the graph, whether knowingly or unknowingly.  Typical examples include truncated y-axes where the vertical graph baseline does not start at zero, unnecessary 3-D representations to distort the sizes or angles of the visual elements, and arbitrary visual encodings that do not reflect data values.

Besides visual components in charts, misaligned titles and verbal comments also create barriers for chart comprehension.  Intentionally selected, miscued, or contradictory descriptions in the charts have been shown to harm the credibility of the data sources.  Such problems could result in degraded readability and misinterpretation of the data being represented in a chart.  As such, there is a need for effective tools to alert consumers to potentially erroneous design practices.  

Researchers at Arizona State University (ASU) have developed a framework for annotating line charts.  The ASU framework has the ability to extract the specifications and data of a chart and return annotations (e.g., visual and/or textual) that effectively point out exactly where there are potentially deceptive elements.  The framework can also output a reconstruction of the graph with any potentially deceptive practices removed. 

Potential Applications:

  • The ASU framework could be offered as a:
    • Browser extension
    • Mobile App
    • Computer App
    • Add-in or Add-on for current chart building/viewing utilities

Benefits and Advantages:

  • Highly automated
  • Any deceptions can be pointed out visually and/or textually to user
  • Enhances visual literacy of line charts
  • Could be implemented in a variety of ways (e.g., browser extension, mobile app, computer app, add-in, add-on, etc.)