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Hello everyone, I’m Tingying He. 
Today, I'll present our work,  

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Using Tactile Charts to Support Comprehension  

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and Learning of Complex Visualizations 
for Blind and Low-Vision Individuals.

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Visualization is a powerful tool for 
communicating complex information. However,  

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a large population of people who are blind or 
have low vision often face barriers to directly  

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accessing visualizations, because interpreting 
visualization relies heavily on the visual system.

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Despite these challenges, BLV 
individuals need access to the  

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rich information visualizations convey. 
Most often, they access this information  

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through alternative text, which provides 
textual descriptions of chart content.

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Accessibility guidelines commonly recommend 
including the chart type in the alt text.  

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Visualizations often convey more than just 
raw data. For example, a histogram shows the  

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distribution of a dataset—something that’s 
hard to grasp from the raw numbers alone.

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Research on visualization accessibility also 
highlights the importance of chart type for  

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BLV individuals’ understanding 
of visualization descriptions.

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While BLV individuals are generally 
familiar with basic chart types such as pie,  

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bar, and line charts, they often 
struggle with more advanced types.

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Yet, complex visualizations are now common in  

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professional contexts such 
as scientific reporting.

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Therefore, it is valuable for BLV professionals 
to learn complex chart types, both to better  

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interpret alt text and to collaborate 
effectively with sighted colleagues.

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Tactile charts are another modality that can make 
visualizations accessible to BLV individuals.  

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Previous work has examined tactile charts as 
data representations and found that they can  

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help users understand spatial relationships and 
data patterns. However, tactile charts are slower  

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and more costly to produce. Static tactile 
charts cannot be easily updated once created,  

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and while dynamic tactile devices do exist, they 
are still expensive and have limited resolution.

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Tactile charts have also been used 
as teaching tools, where they do not  

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often need to be updated. In practice, tactile 
graphics are commonly used in BLV education,  

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but typically only include simple charts. A 
few research exploring their use as educational  

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tools for visualizations, but mostly 
focuses on basic chart types. Teaching  

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complex chart types through tactile 
charts remains largely underexplored.

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In this work, we aim to support BLV individuals 
in building mental models of complex chart types  

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through tactile charts. We hypothesize that 
developing such mental models can help them  

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better interpret digital representations, 
such as alt text, that use these chart types.

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To test this hypothesis, we selected four advanced 
chart types commonly used in scientific contexts:  

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UpSet plots, clustered heatmaps, faceted 
area plots, and violin plots. Since our goal  

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was to use tactile charts as learning 
tools, we designed them using simple,  

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familiar datasets so participants could focus 
on the chart types rather than the data content.

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The design of tactile charts greatly 
influences their readability.

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However, there are not many design guidelines 
specific to the chart types we selected.

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To address this gap, we followed a collaborative 
and iterative design process. We followed existing  

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guidelines and best practices, applied 
our expertise in visualization design,  

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and collaborated closely with two BLV researchers.

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To create a tactile chart, we first 
designed a 2D version, then built 3D  

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models and produced them with 3D printing, 
and finally added labels to the backside.

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To explore different design options, we created 
two initial variations of each chart and prepared  

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exploration instructions. We then asked our BLV 
collaborators for feedback on both the design  

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and the instructions. Based on their input, we 
refined each chart into a third, final design.

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We also finalized the exploration 
instructions alongside them.

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We recommend checking our paper for details on 
our design considerations and recommendations.

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All final models and exploration instructions 
are available on our project website.

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Using these finalized tactile charts, we 
conducted an interview study with 12 BLV  

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participants to evaluate their effectiveness. 
We required participants to be students or  

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in employment status, because the focus of our 
study is a professional data analysis context.

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Our goal was not only to introduce participants 
to complex chart types but also to test whether  

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learning through tactile charts improved 
their comprehension when reading alt text  

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for new datasets of the same chart type. For each 
chart, participants first learned it either with  

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a tactile model and textual instructions or with 
textual instructions only, then demonstrated their  

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understanding using an alt text describing 
a more complex dataset of that chart type.

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Given the expected interview length and 
recruitment challenges, it was infeasible  

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to test all four chart types. To narrow them 
down, we consulted our BLV collaborators and  

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ranked the charts by difficulty. From most 
to least difficult: UpSet plot, clustered  

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heatmap, violin plot, and faceted line chart.
To balance the need for evaluating complex charts  

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without overwhelming participants, we selected 
the clustered heatmap and violin plot for testing.

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Participants learned one chart type with 
tactile charts and the other without. We  

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compared participants’ learning experiences, 
outcomes, and preferences between the two  

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modalities and gathered feedback 
on the tactile charts themselves.

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We conducted a thematic analysis and 
identified five main themes. Here,  

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I’ll focus on three of them, but 
you can find all five in our paper.

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First, I’ll discuss how tactile charts 
support building mental models of chart types.

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As one participant P9 said:
“The tactile model helps put it  

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into a picture that you can use, you can create 
a mental model, to picture things in your head.” 

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Tactile charts, in particular, 
supported learning about chart  

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layout and element shapes, which are important 
for understanding how the chart type works.

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Participants also prefer the hands-on 
learning approach, for example,P3 said:  

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“I want to touch everything.” P4 also mentioned: 
“I’m blind, but I do consider myself a visual  

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or a tactile learner in the sense that 
I’m able to feel what I’m being told.”

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Second, participants found that the mental models 
they built were reusable and transferable across  

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different datasets. These models helped 
them interpret new data and alt texts.

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As P12 said:
“It helps me  

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understand the chart itself, then it allows me to 
recreate it mentally with a different data set.” 

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Participants emphasized that tactile charts 
help them develop a structural understanding  

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of how each chart type functions and provide a 
reference point when interpreting new datasets.

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The third theme relates to 
BLV visualization education. 

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Participants discussed the challenges BLV 
individuals face when learning subjects  

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involving data visualizations.
As P2 shared: 

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“They didn’t know how to help me. So we just 
skipped that part of the curriculum for me.” 

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They expressed strong interest in learning new 
visualizations and emphasized the importance of  

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equal access to information.
As P1 said: 

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“Information, like how to read a map or access 
data, is so important, especially when you  

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get a job. You feel left out when you don’t 
have that information while your peers do.”

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Participants also believed tactile charts could  

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empower their learning and 
expand future opportunities.

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As P2 put it:
“It is extremely important  

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for students to be able to have access to that, 
because it just changes the game for you…[tactile  

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charts could enable blind students to be] on 
the same playing field as their sighted peers.”

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In conclusion, we found that 
thoughtfully designed tactile  

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charts with clear exploration instructions 
can be a helpful and preferred educational  

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tool for BLV individuals to 
learn complex visualizations.

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Thank you for listening.