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Yu Jun Yam

dblp:371/8968 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0008-9061-0828ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Accessibility and assistive technology · 100%
Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Accessibility and assistive technology › image accessibility
accessible data visualization
0.812024
MAIDR: Making Statistical Visualizations Accessible with Multimodal Data Representation · CHI 2024
Accessibility and assistive technology
multimodal representations
0.812024
MAIDR: Making Statistical Visualizations Accessible with Multimodal Data Representation · CHI 2024
Visualization and visual analytics › information visualization › quantitative data visualization
statistical visualization
0.212024
MAIDR: Making Statistical Visualizations Accessible with Multimodal Data Representation · CHI 2024

Methods — techniques the papers use, named apart from their topics

tactile representation · 1.5sonification · 1.5braille display · 1.5
YearPublicationVenuePosition
2024 MAIDR: Making Statistical Visualizations Accessible with Multimodal Data Representation
abstract
This paper investigates new data exploration experiences that enable blind users to interact with statistical data visualizations—bar plots, heat maps, box plots, and scatter plots—leveraging multimodal data representations. In addition to sonification and textual descriptions that are commonly employed by existing accessible visualizations, our MAIDR (multimodal access and interactive data representation) system incorporates two additional modalities (braille and review) that offer complementary benefits. It also provides blind users with the autonomy and control to interactively access and understand data visualizations. In a user study involving 11 blind participants, we found the MAIDR system facilitated the accurate interpretation of statistical visualizations. Participants exhibited a range of strategies in combining multiple modalities, influenced by their past interactions and experiences with data visualizations. This work accentuates the overlooked potential of combining refreshable tactile representation with other modalities and elevates the discussion on the importance of user autonomy when designing accessible data visualizations.
Jooyoung Seo, Yilin Xia, Bongshin Lee, Sean McCurry, Yu Jun Yam
CHI5