Charagraph: Interactive Generation of Charts for Realtime Annotation of Data-Rich Paragraphs - Archive ouverte HAL Access content directly
Conference Papers Year : 2023

Charagraph: Interactive Generation of Charts for Realtime Annotation of Data-Rich Paragraphs

Damien Masson
  • Function : Author
  • PersonId : 1064277
Sylvain Malacria
Géry Casiez
Daniel Vogel
  • Function : Author
  • PersonId : 913043

Abstract

Documents often have paragraphs packed with numbers that are difficult to extract, compare, and interpret. To help readers make sense of data in text, we introduce the concept of Charagraphs: dynamically generated interactive charts and annotations for in-situ visualization, comparison, and manipulation of numeric data included within text. Three Charagraph characteristics are defined: leveraging related textual information about data; integrating textual and graphical representations; and interacting at different contexts. We contribute a document viewer to select in-text data; generate and customize Charagraphs; merge and refine a Charagraph using other in-text data; and identify, filter, compare, and sort data synchronized between text and visualization. Results of a study show participants can easily create Charagraphs for diverse examples of data-rich text, and when answering questions about data in text, participants were more correct compared to only reading text.
Fichier principal
Vignette du fichier
Charagraph__CHI2023.pdf (3.46 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-04017629 , version 1 (07-03-2023)

Identifiers

Cite

Damien Masson, Sylvain Malacria, Géry Casiez, Daniel Vogel. Charagraph: Interactive Generation of Charts for Realtime Annotation of Data-Rich Paragraphs. CHI 2023 - ACM Conference on Human Factors in Computing Systems (CHI 2023), ACM, Apr 2023, Hamburg, Germany. ⟨10.1145/3544548.3581091⟩. ⟨hal-04017629⟩
159 View
239 Download

Altmetric

Share

Gmail Facebook X LinkedIn More