Article

Improving accessibility to statistical graphs: the iGraph-Lite system

Authors:

Petro Verkhogliad,

Gitte Lindgaard,

Antoine Chretien,

Martin LachanceAuthors Info & Claims

Assets '07: Proceedings of the 9th international ACM SIGACCESS conference on Computers and accessibility

Pages 67 - 74

https://doi.org/10.1145/1296843.1296857

Published: 15 October 2007 Publication History

Abstract

Information is often presented in graphical form. Unfortunately, current assistive technologies such as screen readers are not well-equipped to handle these representations. To provide accessibility to graphs published in ``The Daily" (Statistics Canada's main dissemination venue), we have developed iGraph-Lite, a system that provides short verbal descriptions of the information depicted in graphs and a way to also interact with this information.

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Cited By

Martiniello NWittich W(2024)A Duoethnography on Disability and Allyship Within a Vision Science Doctoral Program: Perspectives on Inclusion, Diversity, Equity, and AccessibilityInternational Journal of Qualitative Methods10.1177/1609406924125153823Online publication date: 1-May-2024
https://doi.org/10.1177/16094069241251538
Wang YZhao YKim Y(2024)How Do Low-Vision Individuals Experience Information Visualization?Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642188(1-15)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642188
Engel CSchmalfuß-Schwarz J(2024)ExcelViZ: Automated Generation of High-Level, Adaptable Scatterplot Descriptions Based on a User StudyUniversal Access in Human-Computer Interaction10.1007/978-3-031-60884-1_27(393-412)Online publication date: 1-Jun-2024
https://doi.org/10.1007/978-3-031-60884-1_27
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Index Terms

Improving accessibility to statistical graphs: the iGraph-Lite system
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Natural language interfaces

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cover image ACM Conferences

Assets '07: Proceedings of the 9th international ACM SIGACCESS conference on Computers and accessibility

October 2007

282 pages

ISBN:9781595935731

DOI:10.1145/1296843

General Chair:
Enrico Pontelli
New Mexico State University, USA
,
Program Chair:
Shari Trewin
IBM T.J. Watson Research Center, USA

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 15 October 2007

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ASSETS07: The 9th International ACM SIGACCESS Conference on Computers and Accessibility

October 15 - 17, 2007

Arizona, Tempe, USA

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Overall Acceptance Rate 436 of 1,556 submissions, 28%

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Cited By

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https://doi.org/10.1177/16094069241251538
Wang YZhao YKim Y(2024)How Do Low-Vision Individuals Experience Information Visualization?Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642188(1-15)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642188
Engel CSchmalfuß-Schwarz J(2024)ExcelViZ: Automated Generation of High-Level, Adaptable Scatterplot Descriptions Based on a User StudyUniversal Access in Human-Computer Interaction10.1007/978-3-031-60884-1_27(393-412)Online publication date: 1-Jun-2024
https://doi.org/10.1007/978-3-031-60884-1_27
Momotaz FEhtesham-Ul-Haque MBillah S(2023)Understanding the Usages, Lifecycle, and Opportunities of Screen Readers’ PluginsACM Transactions on Accessible Computing10.1145/358269716:2(1-35)Online publication date: 13-Jul-2023
https://dl.acm.org/doi/10.1145/3582697
Wang YKim Y(2023)Making Data-Driven Articles more Accessible: An Active Preference Learning Approach to Data Fact PersonalizationProceedings of the 2023 ACM Designing Interactive Systems Conference10.1145/3563657.3595986(1353-1366)Online publication date: 10-Jul-2023
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Kim JSrinivasan AKim NKim Y(2023)Exploring Chart Question Answering for Blind and Low Vision UsersProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581532(1-15)Online publication date: 19-Apr-2023
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Kim NAtaguba GJoyner SZhao CIm H(2023)Beyond Alternative Text and tables: Comparative Analysis of Visualization Tools and Accessibility MethodsComputer Graphics Forum10.1111/cgf.1483342:3(323-335)Online publication date: 27-Jun-2023
https://doi.org/10.1111/cgf.14833
Bajić FJob J(2023)Review of chart image detection and classificationInternational Journal on Document Analysis and Recognition (IJDAR)10.1007/s10032-022-00424-526:4(453-474)Online publication date: 12-Jan-2023
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Williams Cde Greef LHarris EFindlater LPavel ABennett CAhmetovic DYaneva V(2022)Toward supporting quality alt text in computing publicationsProceedings of the 19th International Web for All Conference10.1145/3493612.3520449(1-12)Online publication date: 25-Apr-2022
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Holloway LGoncu CIlsar AButler MMarriott K(2022)Infosonics: Accessible Infographics for People who are Blind using Sonification and VoiceProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3517465(1-13)Online publication date: 29-Apr-2022
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