ExcelViZ: Automated Generation of High-Level, Adaptable Scatterplot Descriptions Based on a User Study

Research output: Contribution to conferencesPaperContributedpeer-review

Contributors

Abstract

Digital charts enable quick and effective analysis of complex data, while they pose a barrier for people with visual impairments. Image descriptions are intended to provide equivalent access to the chart’s content, which is challenging and requires interpretations of the data, especially for complex data sets. Therefore, this paper investigates which key messages and categories sighted students perceive in scatterplots based on two user studies. First, we discussed five exemplary scatterplots with a group of sixteen students, who are familiar with digital accessibility and scatterplots in the academic context. We further analyzed this sample of scatterplots through an online survey with 222 participants, primarily students. We also compared the statistical correlations with the correlations reported by the participants, finding a high degree of agreement on outliers and trends. The results highlight the potential of image descriptions for accessible data analysis and form the basis for their automated generation.

Details

Original languageEnglish
Pages393–412
Publication statusPublished - 1 Jun 2024
Peer-reviewedYes

Conference

TitleInternational Conference on Human-Computer Interaction
Abbreviated titleHCII
Conference number26
Duration29 June - 4 July 2024
Website
Degree of recognitionInternational event
LocationWashington Hilton Hotel
CityWashington DC
CountryUnited States of America

External IDs

Scopus 85195884897