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Enhancing statistical chart accessibility for people with low vision: insights from a user test

Universal Access in the Information Society

May 2024

DOI:10.1007/s10209-024-01111-4

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Authors:

Rubén Alcaraz-Martínez

University of Barcelona

Mireia Ribera Turró

University of Barcelona

A remote user test was performed with two versions (one accessible and one non-accessible) of three types of web-based charts (horizontal bar chart, vertical stacked bar chart, and line chart). The objectives of the test were: (a) to validate a set of heuristic indicators for the evaluation of the accessibility of statistical charts presented in a previous work (Fariñas Falcón et al. in Mediocentro Electrónica 21(1):65–68, 2017); (b) to identify new barriers and preferences for users with low vision in the access and use of this content not previously contemplated. 12 users were tested, with a variety of conditions associated with low vision: low visual acuity (6 users), reduced central vision (2 users), reduced peripheral vision (2 users), blurry vision (1 user), sensitivity to light (3 users), Nystagmus (2 users) and color vision deficiency (CVD) (4 users). From a quantitative standpoint, accessible versions of charts were more efficient, effective, and satisfactory. From a qualitative point of view, results verify the relevance of heuristics H2, Legend; H3, Axes; H6, Data source (as data table); H10, Safe colors; H11, Contrast; H12, Legibility; H13, Image quality; H14, Resize; H16, Focus visible; H17, Independent navigation; related to the proposed tasks. As new observations, tooltips were highly valued by all users, but their implementation must be improved to avoid covering up significant parts of the charts when displayed. The data table has also been frequently used by all users, especially in the non-accessible versions, allowing them to carry out tasks more efficiently. The position and size of the legend can be a significant barrier if it is too small or appears in an unusual position. Finally, despite the limitations related to color perception, some users prefer color graphics to black and white, so, to target all profiles, it is necessary to redundantly encode categories with colors and patterns as well.

Non-accessible bar chart created with Excel with an additional table in text format

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Accessible bar chart created with Highcharts

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Measure of expectations with accessible and non-accessible charts

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Detail of the low quality of the non-accessible bar chart resized

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Detail of the accessible bar chart showing the absence of some labels

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https://doi.org/10.1007/s10209-024-01111-4

LONG PAPER

Enhancing statistical chart accessibility forpeople withlow vision:

insights fromauser test

RubénAlcaraz‑Martínez1 · MireiaRibera2 · AdriàAdeva‑Fillol3· AfraPascual‑Almenara4

Accepted: 10 April 2024

Abstract

A remote user test was performed with two versions (one accessible and one non-accessible) of three types of web-based

charts (horizontal bar chart, vertical stacked bar chart, and line chart). The objectives of the test were: (a) to validate a set

of heuristic indicators for the evaluation of the accessibility of statistical charts presented in a previous work (Fariñas Fal-

cón etal. in Mediocentro Electrónica 21(1):65–68, 2017); (b) to identify new barriers and preferences for users with low

vision in the access and use of this content not previously contemplated. 12 users were tested, with a variety of conditions

associated with low vision: low visual acuity (6 users), reduced central vision (2 users), reduced peripheral vision (2 users),

blurry vision (1 user), sensitivity to light (3 users), Nystagmus (2 users) and color vision deﬁciency (CVD) (4 users). From

a quantitative standpoint, accessible versions of charts were more eﬃcient, eﬀective, and satisfactory. From a qualitative

point of view, results verify the relevance of heuristics H2, Legend; H3, Axes; H6, Data source (as data table); H10, Safe

colors; H11, Contrast; H12, Legibility; H13, Image quality; H14, Resize; H16, Focus visible; H17, Independent navigation;

related to the proposed tasks. As new observations, tooltips were highly valued by all users, but their implementation must

be improved to avoid covering up signiﬁcant parts of the charts when displayed. The data table has also been frequently used

by all users, especially in the non-accessible versions, allowing them to carry out tasks more eﬃciently. The position and size

of the legend can be a signiﬁcant barrier if it is too small or appears in an unusual position. Finally, despite the limitations

related to color perception, some users prefer color graphics to black and white, so, to target all proﬁles, it is necessary to

redundantly encode categories with colors and patterns as well.

Keywords Low vision· Statistical charts· Data visualization· Web accessibility· User test· Heuristic evaluation

1 Introduction

The number of people with low vision worldwide is signiﬁ-

cant. Globally, in 2020, an estimated 43,3 million people

were blind. On the other hand, it is estimated that 295 mil-

lion people have moderate and severe vision impairment;

258 million have mild vision impairment; and 510 million

have visual impairment from uncorrected presbyopia. Glob-

ally, between 1990 and 2020, the number of people who

were blind increased by 50.6% and the number with moder-

ate and severe vision impairment increased by 91.7% [1].

The same study predicts that by 2050, 61 million people will

be blind, 474 million will have moderate and severe vision

impairment, 360 million will have mild vision impairment,

and 866 million will have uncorrected presbyopia.

Each disability affects visually impaired people dif-

ferently, resulting in a signiﬁcant variety of user proﬁles

[2]. However, in all cases, low vision is a visual condition

* Rubén Alcaraz-Martínez

ralcaraz@ub.edu

Mireia Ribera

ribera@ub.edu

Adrià Adeva-Fillol

aadevaﬁ7@alumnes.ub.edu

Afra Pascual-Almenara

afra.pascual@udl.cat

1 Departament de Biblioteconomia, Documentació i

Comunicació Audiovisual, Universitat de Barcelona,

Barcelona, Spain

2 Departament de Matemàtiques i Informàtica, Institut de

Matemàtiques, Universitat de Barcelona, Barcelona, Spain

3 Universitat de Barcelona, Barcelona, Spain

4 Departament d’Informàtica i Enginyeria Industrial,

Universitat de Lleida, Lleida, Spain

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characterized by a substantial reduction in sight that cannot

be corrected with lenses, medication, or surgery. Low vision

profoundly impacts the daily lives of those who experience it

[2] due to the prevalence of visual information in the acqui-

sition of knowledge and daily activities. Visual information

is often more detailed and richer compared to auditory or

tactile information. As a result, much of our technology has

been designed with a focus on sight.

In this context, the total or partial loss of visual percep-

tion can lead to a dramatic reduction in autonomy, given

its crucial role in fundamental daily tasks such as learning,

mobility, access to information, and social inclusion and

participation.

Low vision is deﬁned by assessing a person’s visual acu-

ity and ﬁeld of vision. Visual acuity measures the ability of

the visual system to distinguish between two closely spaced

points at a speciﬁc angle [3]. Field of vision, or peripheral

vision, refers to the total visual area in degrees while the

central point of focus remains ﬁxed [4]. Generally, an indi-

vidual is considered to have low vision if, even with the best

optical correction, her visual acuity falls below 20/60 [4] or

20/70 [5], or their ﬁeld of vision is less than 20°.

Low vision encompasses individuals with visual impair-

ments other than blindness which cannot be fully corrected

with lenses. This category includes various user proﬁles

resulting from congenital origins or diﬀerent eye conditions

and diseases such as cataracts, glaucoma, macular degen-

eration, or diabetic retinopathy. Each person may exhibit

varying degrees of visual acuity and ﬁeld of vision, along

with speciﬁc challenges related to contrast sensitivity, light

or glare sensitivity, and color perception.

For example, macular degeneration is an eye disease that

can result in blurred or absent vision in the central ﬁeld, in

areas known as scotomas. As a consequence, individuals

with this condition often rely on their peripheral vision [2].

Glaucoma leads to the loss of peripheral vision, accompa-

nied by a blurred central area, making tasks like reading,

and seeing detail exceptionally challenging [6]. Cataracts

can cause vision to become blurred or hazy, especially in

bright light [2], and may also aﬀect color perception [7].

Ocular albinism is characterized by reduced visual acuity

and heightened sensitivity to brightness and light [8]. Nys-

tagmus is associated with involuntary, uncontrollable eye

movements linked to neurological issues [9]. Retinoschisis

impacts both central vision acuity and peripheral vision,

which can be lost if the inner layer of nerve cells detaches

from the outer layer [10]. Multifocal chorioretinitis leads to

vision loss, blurry vision and other symptoms [11]. Star-

gardt’s disease may manifest as gray, black, or hazy spots

in the central vision, light sensitivity, slower adaptation to

changes between light and dark environments and, in some

cases, color blindness [12]. Finally, color vision deﬁciency

(CVD), also known as color blindness, can be acquired but

usually is a genetic condition [13] that aﬀect the expression

of the full complement of normal cone photoreceptors. CVD

presents a wide range of severity: anomalous trichromacy,

dichromacy, and monochromacy (complete inability to per-

ceive any colors) [14].

Another challenge associated with low vision is that

many of the vision problems mentioned tend to manifest as

individuals age, either suddenly or gradually. These visual

impairments often occur later in life, making it more chal-

lenging to acquire new skills and adapt to assistive technolo-

gies that may be unfamiliar.

Furthermore, people with low vision utilize a wide range

of assistive technologies, with screen magniﬁers being a

prominent choice, followed by screen readers, zoom features

integrated into web browsers, and high-contrast settings.

This diversity in proﬁles, barriers, and assistive technologies

presents a signiﬁcant challenge in meeting the speciﬁc needs

of each group through a single, universally eﬀective design.

This research employs a user-centered approach to gain a

deeper understanding of the obstacles faced by individuals

with low vision when accessing data visualizations. In con-

temporary society, data permeates nearly every aspect of our

lives [15], encompassing information dissemination, edu-

cation, research, and leisure activities. As Kim etal. aptly

stated, ‘our society is becoming data-driven’ [16]. Conse-

quently, the ability to comprehend and manipulate data is

crucial for individuals to grasp the world, make informed

choices, access scientiﬁc ﬁndings, grasp abstract scientiﬁc

concepts [17], and retrieve public health and social care

information [18].

In our data-driven era, one of the primary challenges is

to elevate data literacy. Data literacy encompasses the abil-

ity to proﬁciently comprehend, analyze, and communicate

data [19]. In today’s society, data literacy is an indispensable

skill [16, 20, 21]. It involves not only the capacity to read

and interpret charts and data tables but also the ability to

critically assess data quality, recognize biases, and grasp the

implications of ﬁndings [22].

Data visualization, particularly statistical charts and vari-

ous graphical representations, facilitates the eﬃcient pro-

cessing of information. Schepers [23] regards data visualiza-

tion as an inherent assistive technology, a form of cognitive

accessibility that leverages our visual system to ease the

interpretation of tabular data [24]. Charts enable the visuali-

zation of abstract concepts and intricate relationships, which

may be challenging to comprehend through alternative data

formats [25], and facilitate the identiﬁcation of patterns and

trends in data [26].

In the realm of scientiﬁc communication, charts serve

as concise and accessible means to convey the primary

outcomes of extensive research endeavors [27–29]. Conse-

quently, data visualization is recognized by several authors

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as an essential skill, not only for the general populace [16,

20] but also for future researchers [21].

In this context, obstacles to accessing data can exacer-

bate societal inequalities, particularly among individuals

with disabilities, who already contend with various social

and economic disparities. Recent examples have highlighted

challenges in accessing public health information [30–32],

political data [33], preserving professional autonomy [34],

and securing quality education [35, 36].

Conversely, accessibility issues that have traditionally

aﬀected data visualizations, including statistical charts, also

pose challenges for search engines. These engines struggle

to crawl, index, utilize, and display these representations on

their results pages, primarily due to them being static bitmap

images or, at best, vector images with limited accessibility

features despite the potential of this format [37].

In large part, this issue arises from content authors (such

as designers, journalists, data scientists and researchers)

lacking awareness of the accessibility barriers individuals

encounter when trying to access their data visualizations.

Furthermore, they may be unaware of the available tech-

niques and solutions to address these barriers [38].

The primary objective of this article is to elucidate the

needs and perspectives of individuals with low vision,

with the aim of identifying key issues related to inacces-

sible charts. Ultimately, the authors seek to propose spe-

ciﬁc solutions that can enhance the accessibility of data

visualizations.

2 Related research

While the ﬁeld of data visualization has experienced expo-

nential growth in recent years, research on the accessibility

of visual artifacts within this discipline has not kept pace

[39]. Presently, there is a rising interest in enhancing the

accessibility of data visualizations for individuals with

intellectual disabilities and the cognitive barriers caused

by conventional design guidelines related to the chart type

selection, chart embellishment conventions, and the rep-

resentation of data through continuous marks versus dis-

crete marks [40]. However, most of the related research on

accessible data visualization and charts has predominantly

focused on barriers to visual access [16, 39, 41], research

methodologies applicable to accessibility [41, 42], practi-

tioner-implemented solutions [43], and the analysis of the

impact of elements such as image captions or alternative

text [44–47].

Additionally, considerable attention has been given to

the development of speciﬁc solutions and techniques aimed

at facilitating data access. These include, for instance, the

use of 3D printed maps and icons [48], tactile representa-

tions such as organic node-link diagrams, grid node-link

diagrams, adjacency matrices or Braille lists [49], audio-

tactile charts in SVG format optimized for embossers [50];

and the incorporation of natural language descriptions to

provide context and insights [51]. Additionally, data soni-

ﬁcation techniques [52] employ varying tones in terms of

pitch and loudness to guide users through charts, often using

a combination of MIDI sounds, synthesized speech, and pre-

recorded audio ﬁles [53].

Other approaches involve chart image detection and clas-

siﬁcation to identify the chart-types, generate screen reader-

compatible summary descriptions, export data to other for-

mats like data tables, and create new, more accessible data

visualizations based on existing ones [54]. Speciﬁc image

processing algorithms are utilized to extract pertinent infor-

mation from raster images and generate automated textual

descriptions [55, 56], while deep neural network methods

are employed to extract data from charts, including chart

types, labels and relevant data, and convert them into vector

charts format [38].

Some proposals enable users to navigate and interact with

line charts using natural language commands and a Text-

To-Speech (TTS) engine, facilitating speciﬁc queries about

the chart’s content [57, 58]. Hybrid systems are designed to

convey information through diﬀerent senses, such as sight,

touch, sound, or muscular resistance (haptic interfaces) [59].

There are even structured musical stimuli used to convey

simple diagrams [60].

These techniques can be categorized into chart classiﬁca-

tion, text recognition, data extraction or data summarization

[61], all of which aim to create alternative representations or

provide users with access to chart information through their

assistive technology.

Despite the higher prevalence of individuals with low

vision, existing scientiﬁc literature has predominantly cen-

tered on blind individuals [62, 63], further marginalizing a

group that remains relatively unknown to society [64]. Low

vision users exhibit notable distinctions from blind individu-

als, and many within this group use their residual vision in

their daily life as much as possible [65, 66], even if it implies

continual adjustments to various interface aspects [65] or

the adoption of uncomfortable or strained positions in front

of screen.

User studies addressing the accessibility of data visuali-

zations and statistical charts have primarily concentrated on

blind individuals [38, 41, 49, 52, 57, 60, 67–70], with only

a few including individuals with low vision [48, 71, 72] or

color vision deﬁciency (CVD) [73, 74]. The dearth of stud-

ies aimed at identifying the needs and preferences of users

with low vision underscores the need for further research in

this domain. Notably, research speciﬁcally focusing on sta-

tistical charts -a content type integral to various key sectors

such as education, research, communication, and business,

among others- remains largely scarce. To address this gap,

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the authors have developed a set of heuristic principles for

assessing the accessibility of such data visualizations [75]

(see Table1).

Heuristic evaluation (HE) stands as one of the most com-

monly used and eﬀective usability assessment techniques

that do not require direct user involvement. HE is a method

within the ﬁeld of usability engineering, employed to iden-

tify issues related to usability within a user interface design.

It plays a crucial role in identifying and resolving these

issues as part of an ongoing design enhancement process.

In HE, a small group of evaluators inspects the interface and

evaluates its adherence to established usability principles,

often referred to as “heuristics”, “heuristic indicators” or

“heuristic principles” [76].

Compared to an accessibility evaluation conducted using

the WCAG as a reference, HE oﬀers several advantages,

including greater conciseness, memorability, meaningful-

ness, and comprehensibility of its principles [77].

On the other hand, domain-speciﬁc heuristics typically

yield more eﬀective and eﬃcient results compared to general

guidelines like WCAG, which primarily focus on website

analysis [78].

A notable exception to the lack of research in this field

is the set of heuristic indicators put forth by Elavsky and

colleagues [79, 80], published subsequent to the develop-

ment of the authors’ own set of heuristics. Elavsky and

his co-authors’ recommendations are intended to assist

visualization designers, journalists, and other practition-

ers in assessing the accessibility of data-driven visualiza-

tions. Their proposal encompasses a total of 50 heuris-

tics, with 14 of them deemed critical, organized into 7

principles (perceivable, operable, understandable, robust,

compromising, assistive, and flexible). These principles

draw inspiration from the web content accessibility guide-

lines (WCAG) but have been extended and tailored to

address the unique requirements of data visualizations.

While aiming to meet the needs of a broad user spectrum,

it is noteworthy that 31 of the 50 proposed principles

specifically address barriers that may impact users with

low vision. Table2 provides a comparison between the

heuristics proposed by Alcaraz etal. and those suggested

by Elavsky etal. concerning individuals with low vision.

Table 1 Alcaraz etal.’s [75] list of heuristics with their description

ID Short name Heuristic

H1 Title Does the chart have a brief and descriptive title that helps users identify it among others appearing on the

same page, as well as navigate between them?

H2 Legend If the chart uses shapes, color or patterns encodings is there a legend to decodify them?

H3 Axes titles If the chart needs axes, are they visible and have appropriate, concise and clear labels and titles?

H4 Caption Does the chart have a caption to help understand it?

H5 Abbreviations Are all the abbreviations in the chart expanded?

H6 Data source Does the chart include information about its source (institution, date and URL of dataset)?

H7 Print version Is there an optimized version for printing available?

H8 Short text alternative Does the chart provide a text alternative that brieﬂy informs about its contents and helps users decide if

they want more information?

H9 Long description In case the text alternative does not adequately convey the information provided by the chart, does the

chart provide a textual long description

H10 Safe colors If the chart uses colors to provide information, is the color scheme safe for the diﬀerent types of color

vision deﬁciencies, including achromatopsia (total absence of color vision)?

H11 Contrast Does the visual presentation of text and background have a contrast ratio of at least 4.5:1, and the non-text

elements of the chart a contrast ratio of at least 3:1?

H12 Legibility Is the text included in the chart legible (sans-serif font, font size of at least 16px or 12pt, line spacing of at

least 1.5, no abuse of capital letters, bold or italics)?

H13 Image quality If the chart is provided as a bitmap image, does the image have suﬃcient quality for a clear visualization

and does it support a zoom of at least 200% without blurring or pixelation?

H14 Resize Can the chart be zoomed up to 200% without an assistive tool and without loss of content or functional-

ity?

H15 Without disturbing elements Does the chart have any disturbing element like watermarks that hinder the visibility of the chart?

H16 Visible focus When an element of the chart (lines, bars, points...) receives the focus, is there a visual indication of it?

H17 Device independent navigation Is it possible to navigate between the marks and elements of the chart with keyboard, mouse and gestures?

H18 Customization Is it possible to customize the chart (color scheme, contrast, typography...) with assistive technologies or

with a resource-speciﬁc customization system?

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3 Methodology

The development and validation of the heuristics by Alcaraz

etal. followed formal and systematic methodology by

Quiñones etal. [81] for creating usability heuristics, com-

prising eight key steps: (1) exploratory stage (literature

review); (2) experimental stage (data analysis to retrieve

additional information); (3) descriptive stage (select and

prioritize the most important collected information during

stage 1 and 2); (4) correlational stage (reconcile the domain

features and functionalities with existing heuristic indica-

tors); (5) selection stage (review the list of heuristic princi-

ples created); (6) speciﬁcation stage (formal speciﬁcation of

each heuristic principle); (7) validation stage (experiments

to determine the eﬀectiveness and eﬃciency of the heuristic

set); (8) reﬁning stage (reﬁne of the heuristic principles with

the conclusions resulting from the previous stage.

Step seven involves the validation of the heuristics set

through a series of experiments, assessing their eﬀective-

ness and eﬃciency. This validation process employs the

following methods: (a) heuristic evaluation (mandatory):

this method is a crucial part of the validation process;

(b) expert judgment (optional): experts may be consulted

to provide additional feedback, enhancing the validation

process; (c) user testing (when necessary): user testing is

employed to complement the validation process as needed.

The complete list of heuristics and their deﬁnitions is

shown in Table1. These heuristics were validated against

WCAG 2.1 [82] in previous research through the analy-

sis of published charts in several contexts: digital media

[83], public health information, [31] and scholarly articles

[84], with good results. In practical terms, domain-speciﬁc

heuristics enable the detection of a higher proportion of

unique problems, a more even distribution of problems

across principles, the identiﬁcation of a greater number

of severe problems, and a more precise identiﬁcation of

speciﬁc issues.

Table 2 Mapping between the

heuristic principles proposed

in previous works and those

proposed by Elavsky

Alcaraz etal.’s set of heuristics Related chartability heuristics

H1 Title No title, summary, or caption

H2 Legend Data in text is not human-readable

H3 Axes titles Data in text is not human-readable

H4 Caption No title, summary, or caption

Metrics and variables are undeﬁned

Statistical uncertainty isn’t clearly communicated

H5 Abbreviations Axis labels are unclear or missing

H6 Data source No table

Table/data is static

H7 Print version –

H8 Short text alternative Content is only visual

H9 Long description Content is only visual

Visually apparent features and relationships are not described

H10 Safe colors Color is used alone to communicate meaning

Not CVD-friendly

H11 Contrast Low contrast

Low contrast on interactive elements

Keyboard focus indicator missing, obscured, or low contrast

H12 Legibility Small text size

Spacing is inappropriate

H13 Image quality –

H14 Resize Zoom and reﬂow are not supported

H15 Without disturbing elements Meaningful elements can be distinguished from each other

H16 Visible focus Keyboard focus indicator missing, obscured, or low contrast

H17 Device independent navigation Interaction modality only has one input type

Controls override AT controls

Inappropriate tab stops

Complex actions have no alternatives

Information cannot be navigated according to narrative or structure

H18 Customization User style change not respected

User’s text adjustments are not respected

Contrast and textures cannot be adjusted

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3.1 Materials andmethods

In this study, a second validation of the heuristic set with

users is carried out, because users contribute with a new

perspective and identify problems that experts cannot always

detect [85, 86]. Special attention is paid to new possible

barriers [87], and to the characteristics and needs of every

speciﬁc proﬁle [88]. According to Brajnik [87], “a barrier

is any condition that hinders the user’s progress towards

achievement of a goal, when the user is a disabled person”.

For the study, a series of synchronous, moderated, and

remote user tests were carried out. The tests consisted of

solving tasks for which users had to consult a set of web-

based charts that had been created. In total, two diﬀerent ver-

sions of three charts (horizontal bar chart, vertical stacked

bar chart, and line chart) were generated: one accessible, cre-

ated following the abovementioned heuristic guidelines [89],

and another non-accessible version. The speciﬁc types of

charts were chosen based on their popularity and adoption.

Despite the signiﬁcant diversity among the proﬁles that

participated in the user test, it was decided to utilize a single

version for the non-accessible charts. This decision aimed

to prevent a substantial increase in the time required to

conduct the test and to minimize unnecessary and undesir-

able fatigue among the users. In the same sense, the color

scheme selected for the accessible charts is intentionally kept

as “neutral” as possible, utilizing black and white, which is

safe for all colorblind proﬁles. In the case of non-accessi-

ble charts, the color scheme and layouts are based on the

defaults oﬀered by Microsoft Excel. This choice also enables

us to evaluate the accessibility of charts generated automati-

cally by this tool, particularly when they are not customized

by their creator.

The non-accessible charts were generated by Microsoft

Excel (2019 MSO 16.0.10356.20006 Windows) using the

tool’s default options to create a chart of each of the selected

types and generating an automatic export in HTML format

(Fig.1). Automated export of charts to HTML format using

Excel involves converting the original vector image to a low-

quality bitmap image. The export included the chart data

table in text format.

The accessible versions were created using the High-

charts JavaScript library (v. 8.0.0), including many of its

accessibility options with the aid of its accessibility module:

screen reader support, long description, keyboard naviga-

tion, the use of patterns as an alternative to color, a visual

indicator when a mark of the chart receives the focus, and a

table with the chart’s data, as well as a tooltip functionality

that complements the legends, providing information on the

value associated with each mark when the focus points to it

Fig. 1 Non-accessible bar chart created with Excel with an additional table in text format

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(Fig.2). All charts, questions and the results of the test are

available online.1

3.2 Procedure

We designed ﬁve identical tasks for both versions, utilizing

ﬁctitious data and scenarios in a within-subject design (the

same users participated in both conditions). To minimize

learning eﬀects, we modiﬁed the values represented in each

version of the chart.

In deﬁning these tasks, we drew from the categories pro-

posed by Brehmer and Munzner [90], with a focus on tasks

related to information consumption, particularly relevant

in the context of public information. These tasks encom-

passed the following aspects: searching for unknown targets

in known locations (browse), searching for unknown targets

in unknown locations (explore), comparing multiple subsets

of targets (compare), and summarizing targets, including the

entire set of targets (summarize).

Tables3, 4 and 5 show tasks, typology of task [90], objec-

tives and related heuristics.

For each task, the moderator read the explanation before

starting, asked for questions from the participants, and

explained subsequently. We employed the “think-aloud”

method as our approach for this study. This method is com-

monly utilized in user studies to gain insights into the cog-

nitive processes of users as they perform tasks [91]. It has

proven to be a valuable and reliable technique due to its

minimal disruption of participants’ thought processes [92].

In this method, participants are instructed to verbally articu-

late their thoughts while engaging with tasks, essentially

vocalizing their inner dialogues. Moreover, participants

are encouraged to explain what barriers or diﬃculties they

encounter. Another advantage of this method is its avoidance

of interpretation by the subjects and its simple verbalization

process, making it an objective approach [92].

Metrics related to eﬀectiveness (percentage of comple-

tion per task), eﬃciency (time per task), and satisfaction

(measure of expectations, with a simpliﬁed 5-point Likert

scale from 1, not at all complicated, to 5, very compli-

cated) were collected during the test. Qualitative measures

focused on detecting the barriers encountered by users and

on analyzing the strategies and workarounds used by users

to overcome the barriers they faced. After the test, users

were asked for their favorite version of each chart, and

informal comments were promoted. This approach inte-

grated the “think-aloud” method with a follow-up inter-

view, during which the moderator speciﬁcally inquired

Fig. 2 Accessible bar chart created with Highcharts

1 https:// www. ub. edu/ adapt abit/ charts- acces sibil ity/ user- test/.

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about any potential barriers or issues that users may not have verbalized during the tests.

Table 3 Bar chart tasks, objectives and related heuristics

Task Typology of task Objective Heuristics related

Which genre and in what year did cin-

ema get the most box oﬃce takings?

Search > explore Compare bar chart lengths by reviewing

the entire chart

H2, H3, H10, H11, H12, H13, H14, H16

and H17

Which genre and in what year do the

ticket sales approach 3 billion?

Search > explore Understand grid marks, compare bar

chart length versus grid within the

entire chart

H2, H3, H10, H11, H12, H13, H14, H16

and H17

In what year does the Drama genre

generate most sales?

Search > explore Search for a speciﬁc datum by review-

ing a category

H2, H3, H10, H11, H12, H13, H14, H16

and H17

In what year does the Action genre

generate most sales?

Search > explore Search for a speciﬁc datum by review-

ing a category

H2, H3, H10, H11, H12, H13, H14, H16

and H17

Between the Drama and Suspense gen-

res, which of the two grossed the most

ticket sales in 2017?

Query > compare Find and compare two speciﬁc marks

by focusing on a part of the chart

H2, H3, H10, H11, H12, H13, H14, H16

and H17

Table 4 Stacked bar chart tasks, objectives and heuristics related

Tasks Typology of task Objective Heuristics related

How many shoes were sold in Septem-

ber 2019?

Search > browse Search for a speciﬁc bar on the

timeline and look for the speciﬁc

category in the stacked bar

H2, H3, H10, H11, H12, H13, H14, H16

and H17

In which month of 2018 were less

shoes sold?

Search > browse Understand year encoding; compare

bar lengths of one category by

reviewing the entire chart

H2, H3, H10, H11, H12, H13, H14, H16

and H17

Considering the 2-year sale, in what

month were the most shoes sold?

Search > explore Compare total bar lengths by review-

ing the entire chart

H2, H3, H10, H11, H12, H13, H14, H16

and H17

Between the 2years, in what month

did sales closer to 1000 shoes occur?

Query > summarize Understand grid marks, compare bar

length to grid in the chart

H2, H3, H10, H11, H12, H13, H14, H16

and H17

In what month is there the biggest dif-

ference between 2018 and 2019?

Query > compare Understand year encoding; compare

the two categories in the stacked bar

within all bars; do some calculations

H2, H3, H10, H11, H12, H13, H14, H16

and H17

Table 5 Line chart tasks, objectives and heuristics related

Tasks Typology of task Objective Heuristics related

In what month and airport have more

ﬂights been ﬂown?

Query > summarize Locate higher value by reviewing the

entire chart

H2, H3, H10, H11, H12, H13, H14, H16

and H17

In what month has El Prat Airport had

the highest number of ﬂights?

Query > summarize Understand category encoding; locate

higher value of a speciﬁc category by

reviewing the entire chart

H2, H3, H10, H11, H12, H13, H14, H16

and H17

In what month has Barajas Airport had

the lowest number of ﬂights?

Query > summarize Understand category encoding; locate

lower value of a speciﬁc category by

reviewing the entire chart

H2, H3, H10, H11, H12, H13, H14, H16

and H17

Which airport had the highest number

of ﬂights in October?

Query > compare Understand categories, compare two

speciﬁc point values on a section of

the chart

H2, H3, H10, H11, H12, H13, H14, H16

and H17

In which month and airport were the

number of ﬂights nearest to but not

higher than 50.000 ﬂights?

Query > summarize Understand grid marks, compare

points to grid by reviewing the entire

chart

H2, H3, H10, H11, H12, H13, H14, H16

and H17

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3.3 Participants

To recruit participants, the authors distributed a question-

naire to individuals with low vision who are members of the

Asociación Discapacidad Visual de Cataluña: B1 + B2 + B3

(Visual Disability Association of Catalonia, Spain). The

questionnaire collected information on several factors,

including: (a) age; (b) gender; (c) type and degree of visual

impairment; (d) visual ﬁeld aﬀection and degree of aﬀecta-

tion; (e) visual acuity; (f) color blindness; (g) light sensitiv-

ity and contrast sensitivity; (h) other disabilities that may

impede computer use; and (i) level of education.

A total of 12 users were recruited, and with a snow-

ball strategy from the early contacted users. Initially, tests

were planned to be held in B1 + B2 + B3 oﬃces, but due to

access restrictions during the COVID pandemic, they were

repurposed as remote tests with Zoom platform. Because of

COVID and also due to the barriers expected to be encoun-

tered in the use of videoconferencing platforms, many of

the previously contacted users (more than 20) refused to

participate after having initially accepted.

On the other hand, remote tests allowed users to answer

the tests from their own homes, with their personal com-

puter equipment and assistive technology, with the ideal

setup. Consent forms were sent to participants prior to the

session so they could read, print, and sign them.

The sample was composed of 58.33% (7) men and

41.66% (5) women; 83.33% (10) of the users had higher

studies and only two users (16.66%) had middle school

and elementary school studies, respectively. The age of

the participants was between 18 and 79years, the average

being 42,3years. The sample included a variety of con-

ditions associated with low vision: low visual acuity (6

users), reduced central vision (2 users), reduced peripheral

vision (2 users), blurry vision (1 user), sensitivity to light

(3 users), Nystagmus (2 users) and color vision deﬁciency

(CVD) (4 users). Table6 shows a detailed description of

each user.

4 Results

Quantitative (user study results) and qualitative results

(observations) are detailed as complementary views of

the test.

4.1 User study results

As mentioned, eﬀectiveness was measured dividing the

number of completed tasks by the number of attempted tasks

(percentage of completion per task). Eﬃciency was meas-

ured with time per task.

Table 6 Information of participants in the user test

ID Gender Age Education Condition Assistive technology

1 M 18 Middle school Ocular albinism, nystagmus, and low vision with

visual acuity 1/10 with the best correction

Browser’s zoom and Windows high contrast mode

2 M 70 Bachelor’s degree Glaucoma with 30% visual impairment in the left

eye and visual acuity in the right eye, move-

ment of the hand and left eye 0′35 130° − 1′25–

0′45 + 4 R − 0′5

Windows magniﬁer and high contrast mode in

combination with handheld magnifying glass

3 M 30 Bachelor’s degree Ocular albinism with visual acuity of 10% Windows magniﬁer

4 M 58 Bachelor’s degree Glaucoma with visual acuity 0–10 Handheld magnifying glass

5 F 26 Bachelor’s degree Brain injury aﬀecting peripheral vision and

reduced central vision at long distance with 70%

visual ﬁeld involvement

Browser’s zoom

6 M 26 Bachelor’s degree Stargardt’s disease and visual acuity of 5% and

diﬃculty in the perception of all colors

Zoom and inverted colors in MacOS

7 M 79 Bachelor’s degree Wet macular degeneration Windows magniﬁer and high contrast mode in

combination with handheld magnifying glass

8 F 51 Bachelor’s degree Stargardt’s disease with visual acuity of 7%, and

diﬃculty in color perception

Windows magniﬁer

9 F 76 Elementary school Achromatopsia and high myopia with visual acuity

of 15%

Browser’s zoom

10 M 23 Bachelor’s degree Juvenile retinoschisis Windows magniﬁer and browser’s zoom

11 F 28 Bachelor’s degree Multifocal chorioretinitis Browser’s zoom

12 F 49 Bachelor’s degree Bilateral central nystagmus of unknown etiology.

Diﬃculty perceiving certain colors

Windows magniﬁer and high contrast mode in

combination with screen reader

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Table7 shows all users’ average percentage of solved

tasks for the accessible and non-accessible versions of each

chart (eﬀectiveness), all users’ average eﬃciency in seconds

by type of chart and version and, ﬁnally, the median value.

The accessible version of the stacked bar chart and the

line chart present greater eﬀectiveness (88.33% and 93.75%)

than the non-accessible versions (81.67% and 87.50%). On

the other hand, the non-accessible bar chart shows a higher

eﬀectiveness than the accessible one (98.33% vs. 91.67%).

In terms of eﬃciency, the accessible versions of the bar

chart and the stacked bar chart are superior to the non-

accessible versions (21.3 and 23.2s vs. 44.58 and 33.38s).

However, the non-accessible version of the line chart pre-

sented greater eﬃciency compared to the accessible ver-

sion (23.48 vs. 25.56s).

As a relevant observation it must be considered that the

ﬂoating windows of the video conferencing tool sometimes

overlapped with the charts, forcing some users to spend

part of the time moving them, with a negative impact on

the time count.

It must also be taken into consideration that in the line

chart, the time required for one of the users, far above the

average, has increased the overall time count.

Related to satisfaction the metric was “measure of

expectations”, i.e. users were asked to rate their expected

task complexity on a scale from 1 (not at all complicated)

to 5 (very complicated), and after completing the task,

they were also asked to rate the actual complexity they

experienced using the same 1 to 5 scale.

The comparison between expectations and experience

[93] is clearly favorable, being most charts in the quadrant

of “promote-it” (Fig.3), meaning that the users got bet-

ter results than expected and as such, were very satisﬁed,

while in the case of non-accessible charts the comparison

Table 7 Eﬀectiveness and

eﬃciency by chart type and

version

Chart Average percent-

age of solved tasks

Average eﬃciency (time in

seconds) for solving all tasks

Median eﬃciency

(time in seconds)

Accessible bar chart 91.67% (55) 21.30 14.0

Non-accessible bar chart 98.33% (59) 44.58 21.0

Accessible stacked bar chart 88.33% (53) 23.20 19.0

Non-accessible stacked bar chart 81.67% (49) 33.38 29.0

Accessible line chart 93.75% (45) 25.56 15.5

Non-accessible line chart 87.50% (42) 23.48 15.0

Fig. 3 Measure of expectations with accessible and non-accessible charts

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between expectations and experience puts the experience in

the quadrant of “big opportunity” (Fig.3), meaning that the

expectations are so low that small improvements can bring

great results. Tables8 and 9 show the expected and the expe-

rienced satisfaction by chart type, respectively.

When asked which version of each chart users found eas-

ier to use, most users preferred the accessible version over

the non-accessible one (86.11% vs. 13.89%), reinforcing the

satisfaction results, except for user 7 (stacked bar chart),

user 8 (line chart), user 10 (bar and line charts), and user 11

(both bar charts).

“Interacting with the charts (referring to accessible

charts) has allowed me to obtain the data you requested

me more quickly. In the case of those that are not

accessible, I have had to make an additional eﬀort”

(user 5).

4.2 Observations

In this section, we oﬀer a comprehensive explanation of

results, strategies, and diﬃculties experienced by users. This

information is not readily available in existing literature but

proves invaluable for designing more specialized tests or

categorizing users into speciﬁc groups for more relevant

comparisons. Additionally, this in-depth understanding will

greatly inform the design of accessible charts and aid in the

development of eﬀective solutions or approaches.

4.2.1 Observations byuser

Given the signiﬁcant diversity in proﬁles, contexts of use,

preferences, and assistive technologies employed by the

users, Table10 presents the details of the observations of

users’ interactions with the charts throughout the test. Strate-

gies are marked-up with the style subtle-emphasis and dif-

ﬁculties marked-up with emphasis style, to facilitate skim

reading through the table.

4.2.2 Other observations

The use of color (H10) in the non-accessible versions of the

three charts has been a barrier for users 6, 8 and 9. In these

three cases, the accessible version, with greater contrast and

with patterns as an alternative to color, has allowed them to

complete the tasks in a shorter amount of time. However,

some users preferred the use of colors instead of the white,

black, and grey version of the accessible version (1, 2 and

7). In particular, user 11 has highlighted that the absence

of color and the interactivity (H17) implemented had not

beneﬁted him. The same user also highlighted that the use of

patterns confuses him. User 6, aﬀected by CVD, and user 9,

with achromatopsia, hold a completely contrasting viewpoint

on this matter.

“The interactivity of the chart facilitates its use, but

it is better in color than in black and white” (user 1).

“I prefer colors than textures or patterns” (user 3).

“Due to the type of vision loss, I have, the color suits

me very well” (user 11).

“As I have achromatopsia, I ﬁnd it very useful that the

bars have patterns to better distinguish them” (user 9).

“In the case of stacked bar charts, it is essential to have

high contrast colors to be able to diﬀerentiate between

the two sections. Patterns seem a good solution to me.”

(user 6).

Among the magniﬁcation options (H14), we ﬁnd two dif-

ferentiated strategies depending on the user: (a) use of the

operating system’s magnifying glass or screen magniﬁer; (b)

use of the browser zoom. In the ﬁrst case, resizing means

losing certain parts of the chart and, with them, important

information to carry out the proposed tasks. This situation

has been the case for users 1 and 2 (could not locate the

legend) (H2). In those cases, when the task involves making

a comparison between data, they are forced to memorize

the ﬁrst value and look for the second by scrolling through

the screen. In the second case (magnifying with the web

browser), the accessible version adjusts its size to the win-

dow width after applying the zoom, allowing users to see

the entire chart on the screen, but not certain elements that

accompany it, such as the table with the data source (H6)

or the legend (H2). Thus, the accessible versions facilitate

Table 8 Expected satisfaction

by chart type Chart type Expected

satisfaction

(1 to 5, 5

more dif-

ﬁcult)

Bar chart 3.58

Stacked bar chart 3.50

Line chart 3.58

Table 9 Experienced satisfaction by chart type

Chart type Experienced

satisfaction

(1 to 5, 5

more dif-

ﬁcult)

Accessible bar chart 1.75

Non-accessible bar chart 2.67

Accessible stacked bar chart 1.83

Non-accessible stacked bar chart 3.75

Accessible line chart 1.75

Non-accessible line chart 2.83

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Table 10 Qualitative observations per user and chart

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 1

Browser’s zoom and Windows high

contrast mode

Bar chart Eﬀectiveness: the user successfully

answers all the questions posed with

both charts

Eﬃciency: During task 5, here is an

observable increase in the time required

to complete the task. In this instance,

the user takes longer because he reads

the values of the tooltips instead of

comparing the length of the bars

Non-accessible version: when the user

opens the chart, he reviews the entire

contents of the page, including the

chart and data table. It also adjusts the

zoom level to 150% and brings his face

closer to the screen

Upon listening to the ﬁrst task, he asks

the moderator if he can use the data

table

In both the ﬁrst and second tasks, the

user scrolls to the bottom area of the

chart to consult the caption. Through-

out all tasks, the user reviews the chart

by following the bars with the mouse,

as well as examining the axes

Accessible version: in the ﬁrst task, the

user hovers the mouse pointer over the

bars, triggering the tooltip, and zooms

in on the screen to read the data

Similar to the previous case, the user

follows the bars with the mouse, but

in this instance, he constantly uses the

tooltips

The user found it easier to complete tasks

with the accessible chart, primarily due

to the helpful tooltips. However, he

expressed a preference for the use of

color in the bars, in contrast to the black

and white appearance of the accessible

version

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 2

Windows magniﬁer and high contrast

mode. Handheld Magnifying Glass

Bar chart Eﬀectiveness: In the non-accessible

version, tasks 2 to 5 were answered

correctly, but the ﬁrst task was not. In

the accessible version, tasks 1 to 4 were

answered correctly, but not the ﬁfth one

Eﬃciency: In all cases, it took longer to

complete the tasks with the non-acces-

sible version. Notably, for the ﬁrst two

tasks it took signiﬁcantly longer with

the non-accessible versions (267.35%

and 323.53% longer, respectively)

Non-accessible version: After receiving

the task, the user expresses confusion

about the correspondence of each color

(legend) to speciﬁc elements. The mod-

erator advises the user to scroll down

the page to view the legend. The user

approaches the screen and promptly

utilizes a hand-held magnifying glass.

Throughout all tasks, the user reviews

the chart by following the bars and the

x-axis with the mouse. Starting from

task 3, the user maintains the zoom

level at 110%

Accessible version: Upon opening the

chart, the user thoroughly reviews it

and scrolls to view all the bars. Simul-

taneously, they hover the mouse pointer

over the bars and inspect the tooltips.

He sets a zoom level that allows him

to view the entire chart on the screen.

Initially, the user uses the order of

the bars to interpret the years. Later,

he observes the legend as well as the

same information in the tooltips. For all

tasks, the user relies on the chart rather

than the data table

The user mentions that he found it rela-

tively easy to complete the tasks with

both versions of the chart, though it was

slightly easier with the accessible version

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 3

Windows magniﬁer

Bar chart Eﬀectiveness: The user provides correct

answers to all the questions with both

charts

Eﬃciency: In task 3 of the accessible

version, the user needed more time

due to interference from the Windows

magnifying glass’ window. Similarly, in

task 5 of the accessible version, the user

required additional time because certain

values disappeared from the screen

when the browser zoomed in

Non-accessible version: Upon opening

the chart, the user thoroughly examines

the entire page. Upon hearing the ﬁrst

task, he expresses the need to see the

small values and zooms in by 200%

using the Windows magniﬁer glass.

He also approaches the screen closely.

Throughout all tasks, he utilizes the

chart to complete them, consults the

legend, and navigates by following the

bars with the mouse pointer

Accessible version: He zooms in by

200% using the Windows magnify-

ing glass. After hearing the ﬁrst task,

he brieﬂy closes the magnifying glass

to adjust the videoconferencing tool

window. For all tasks, he relies on the

chart to complete them, consults the

legend, and primarily use a compara-

tive approach, comparing the length of

the bars and consulting the tooltips to

solve the tasks

The user mentions that he found it rela-

tively easy to complete the tasks with

both versions of the chart, although the

accessible version was easier due to the

labeled values of bars and the presence

of tooltips. However, he expresses a

preference for color bars over the use of

patterns

User 4

Handheld Magnifying Glass

Bar chart Eﬀectiveness: the user provides correct

answers to all the questions with both

charts

Eﬃciency: in all cases (except for task

3 where the time taken was similar for

both versions) it took longer to com-

plete the tasks with the non-accessible

version. Notably, for the ﬁrst two tasks

the non-accessible versions required

signiﬁcantly more time (964.71% and

350% longer, respectively)

Non-accessible version: The user initially

employs a hand magnifying glass but

struggles to see the Y-axis category

names. He subsequently increases the

browser zoom to 133% and then to

150%. Starting from task 2, the user set

the browser zoom to 200%. Throughout

all tasks, he relies on the chart rather

than the data table

Accessible version: The user initially sets

the browser zoom to 110% and then to

133%. Later, he reduces it to 100%. To

complete all tasks, he primarily uses

the chart and interprets the values based

on the order of the bars, rather than

referring to the legend

The user found the non-accessible version

to be quite complicated, whereas he

found the accessible version much easier

to use

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 5

Browser’s zoom

Bar chart Eﬀectiveness: The user provides correct

answers to all the questions with both

charts

Eﬃciency: In all cases, it took longer to

complete the tasks with the non-acces-

sible version, except in task 4, where

the user’s eﬃciency improved due to

learning eﬀects

Non-accessible version: initially she

examines the chart and the table head-

ings. After hearing the ﬁrst task, she

navigates to the data table and then

reviews the chart again. She answers

the questions using the chart but cross-

checks her answers with the table. She

mentions that the axis titles have poor

contrast, which is why she relies on

the table to verify her responses. In all

tasks, she primarily uses the chart but

references the table for the ﬁrst three

tasks

Accessible version: Upon opening the

chart, the video conferencing tool

window partially obscures it. The

moderator advises her to move the win-

dow for better visibility. She uses the

labeled value of each bar for all tasks.

In cases where the value is not visible,

she resorts to comparing the length of

the bars

She described the non-accessible version

as neither particularly easy nor diﬃcult.

Conversely, she found the accessible ver-

sion notably easier, attributing this ease

to the higher contrast, the presence of

data labels and the availability of tooltips

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 6

Zoom and inverted colors in MacOS

Bar chart Eﬀectiveness: The user provides correct

answers to all questions with both

charts

Eﬃciency: In all cases the user requires

nearly twice as much time to solve the

tasks with the non-accessible chart.

Task 1, in particular, shows a time

increase of 143.75%

Non-accessible version: the user employs

the inverted color mode to read the text.

He zooms in nearly to the maximum

and moves the mouse cursor along the

X-axis while the moderator asks him

the questions. Throughout the test, he

adjusts the window of the videocon-

ferencing tool, which appears above

the legend. However, He does not

locate the legend until task 2. The user

mentions a preference for consulting

the data table. To solve the tasks, he

relies on both the chart and the table.

The user needed to approach the screen

closely to solve the tasks

Accessible version: In this case, the user

does not activate the inverted color

mode. He uses a lower zoom level than

the employed with the non-accessible

chart. The user examines the chart, the

legend, and the data table. Again, he

must adjust the window of the vide-

oconferencing tool. During task 1, he

initially looks for the answer in the data

table and then veriﬁes it with the chart.

After realizing that the bars are labeled

with values and have tooltips, he begins

answering using the chart and cross-

checking some answers with the table

He found the non-accessible version to be

quite complicated, while the accessible

version was straightforward and more

user-friendly

User 7

Windows magniﬁer and high contrast

mode. Handheld Magnifying Glass

Bar chart Eﬀectiveness: The user provides correct

answers to all the questions with both

charts

Eﬃciency: In tasks 1 and 3, the user took

longer to respond with the non-acces-

sible version, while in tasks 2, 4 and 5,

it took longer with the accessible one.

This can be attributed to two reasons:

(a) in task 2, the user directly used the

data table instead of the non-accessible

chart; (b) in tasks 4 and 5, after increas-

ing the zoom level of the browser, some

data labels of the accessible chart disap-

peared

Non-accessible version: After hearing

the ﬁrst task, the user uses a hand-held

magnifying glass to review the Y-axis

labels and the chart title. While search-

ing for the legend, he discovers the data

table and uses it to solve all the tasks

Accessible version: Upon opening the

chart, the user notices the values at the

end of each bar. He continues to utilize

the hand magniﬁer glass to complete

the tasks. In task 5, when one of the

values disappears, he relies on compar-

ing the bars to provide an answer

The user found the accessible version

easier to work with, although he noted

that in some bars, the data labels did not

appear. The user also mentioned that he

might have found it easier after using the

non-accessible version initially

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 8

Windows magniﬁer

Bar chart Eﬀectiveness: the user provides correct

answers to all questions with both

charts

Eﬃciency: in all cases, the user needed

more time to complete the tasks with

the non-accessible chart. In tasks 1 and

2, the increase in time was 52.11% and

339.29%, respectively

Non-accessible version: The user uses

the Windows magniﬁer glass at 500%

and approaches the monitor closely.

Initially, he mentions having diﬃculty

diﬀerentiating colors. He also explains

that reading the Y-axis labels is chal-

lenging. Additionally, he has trouble

ﬁnding the legend. In task 2 he discov-

ers the table and asks the facilitator if it

corresponds to the chart. From then on,

he consistently uses the table

Accessible version: She continues using

the Windows magniﬁer glass at 500%.

She explains that she can see the Y-axis

labels better with this version. In some

tasks, she resorts to using the data table

because the chart is partially obscured

by the video conferencing tool window.

She comments that, in general, she

always ﬁnds it easier to use the table

She found the accessible version easier to

use

User 9

Browser 's zoom

Bar chart Eﬀectiveness: the user provided correct

answers to all the questions with both

charts

Eﬃciency: In all cases the user took more

time to complete the tasks with the

non-accessible chart. In task 2, the time

required was 469.44% longer with the

non-accessible chart

Non-accessible version: Initially, the

user reads the chart’s title and mentions

that she sees three colors per category,

but that she ﬁnds them practically

identical. She identiﬁes the gray color

(central bar) as helping her diﬀerentiate

between the other two. She struggles to

perceive the legend correctly. In task 2,

she discovers the data table and begins

using it to solve the tasks

Accessible version: Right from the start,

she relies on the data table to complete

all tasks

She found the accessible version easier to

consult. Although she needed to use the

table for some tasks, she mentioned that

the colors and textures of the accessible

version were easier to interpret

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 10

Windows magniﬁer and browser’s zoom

Bar chart Eﬀectiveness: The user provides correct

answers to all the questions with both

charts

Eﬃciency: The user took less time to

solve tasks 1, 3 and 4 with the non-

accessible version. Task 2 took the

same amount of time with both charts.

Task 5 took less time with the acces-

sible version. The user mentioned that

the interactive charts confused him,

which inﬂuenced the time required to

solve the tasks

Non-accessible version: the user sets the

zoom level of the Windows magniﬁer

between 200 and 250%. Initially, the

user reviews the chart in general, reads

the title, checks the axes titles and

notices the presence of a data table.

All tasks are solved by comparing the

length of the bars. The user does not

seem to have trouble diﬀerentiating the

colors or interpreting the legend

Accessible version: the user sets the

zoom level of the Windows magniﬁer

between 200 and 250%. In the ﬁrst task,

horizontal scrolling was required, and

the user has to scroll multiple times

from left to right to view the labels on

the Y-axis. Although the user observes

that placing the mouse pointer over

the bars triggers tooltip with all the

information, the user continues to scroll

horizontally to verify the category to

which each bar belongs

The user prefers the non-accessible version

due to the color selection. He also founds

the subtle color change when the mouse

cursor passes over the bar in the acces-

sible version confusing

User 11

Browser’s zoom

Bar chart Eﬀectiveness: the user provides correct

answers to all the questions with both

charts

Eﬃciency: The user required more time

to complete tasks with the non-acces-

sible charts, except in task 4 where he

needed only one second more with the

accessible one

Non-accessible version: The user main-

tains a zoom level of 100% and solves

all tasks by comparing the length of

the bars

Accessible version: the user also keeps

the zoom level at 100% and solves all

tasks by comparing the length of the

bars. However, she mentions feeling

confused by the color scheme used in

the accessible chart (black/gray). On

the other hand, though she understood

the potential beneﬁts of interactivity in

certain situations

The user found both versions of the charts

to be straightforward, but he prefers the

color version (the non-accessible one)

because it made him feel more comfort-

able

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 12

Windows magniﬁer and high contrast

mode. Screen reader

Bar chart Eﬀectiveness: the user provides correct

answers to all the questions with both

charts

Eﬃciency: the user requires more time

to complete all tasks with the non-

accessible charts. The most signiﬁcant

diﬀerences are observed in tasks 1 (43s

vs. 12s) and 2 (19s vs. 4s)

Non-accessible version: the user employs

the Windows magnifying glass and

adjusts the zoom level, ranging from

100 to 150%, depending on the task.

All tasks are solved by comparing the

length of the bars and referring to the

legend

Accessible version: the user utilizes the

Windows magnifying glass and varies

the zoom level, ranging from 100 to

150%, based on the task. All tasks are

completed by comparing the length of

the bars and referencing both the legend

and the tooltips

The user reports that solving the tasks with

the non-accessible chart was quite com-

plicated, while those with the accessible

chart were very easy

User 1

Browser’s zoom and Windows high

contrast mode

Stacked bar chart Eﬀectiveness: The user provides correct

answers to all the questions with both

charts, except for task 1 with the non-

accessible version

Eﬃciency: In tasks 1, 2, and 4, the user

took longer with the non-accessible ver-

sion. However, in tasks 3 and 5, it took

a little longer with the accessible ver-

sion. In the case of task 3, this was due

to the video conferencing tool window

which caused some inconvenience and

required adjustment

Non-accessible version: When the user

opens the chart, he set the browser

zoom to 200% and review the chart

(not the table). To solve the tasks, he

uses the chart and follows the bars with

the mouse pointer. Throughout, he

approaches the computer screen very

closely

Accessible version: To solve tasks 1 and

2, the user uses the tooltips. For tasks 3

and 4, he reviews the data label and the

tooltips. For task 5 he looks at the bars

and positions the mouse pointer on the

bar he selects as the answer. Through-

out, he approaches the computer screen

very closely

He found the accessible version easier to

use because of its interactivity, which

includes data labels, hover eﬀects and

tooltips

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 2

Windows magniﬁer and high contrast

mode. Handheld Magnifying Glass

Stacked bar chart Eﬀectiveness: the user answered task 3

correctly with the non-accessible ver-

sion. With the accessible version, the

user answered tasks 2, 3 and 5 correctly

but answered tasks 1 and 4 incorrectly

Eﬃciency: in all cases, the user took

longer to complete the tasks with the

non-accessible version, except for task

Non-accessible version: Initially, the

user reviews the entire chart without

scrolling to the table. The user sets the

browser zoom to 120%. Tasks are com-

pleted by scrolling the chart, consult-

ing the legend, and guiding the mouse

pointer across the axes

Accessible version: Initially, the user

reviews the chart and reads the caption.

In the ﬁrst task, he maintains a 120%

zoom level, causing some data labels

to be missing, leading to misinterpreta-

tions. The user also mentions diﬃculty

diﬀerentiating bar sections due to the

gray/black combination. In task 2, the

user zooms out to 100% and all missing

values reappear. The user encounters

issues with the video conferencing tool

window, which the moderator helps

resolve. All tasks are completed using

the chart without consulting the table,

and the user frequently approaches the

screen

The user found the accessible version eas-

ier to use overall, although he expressed

a preference for a gray /red combination

User 3

Windows magniﬁer

Stacked bar chart Eﬀectiveness: The user incorrectly

answered tasks 1 and 2 with the

non-accessible version, but correctly

answered all the questions with the

accessible version

Eﬃciency: The user takes more time to

solve all the tasks with the non-accessi-

ble version, with a 266.67% increase in

time compared to the accessible version

for task 1

Non-accessible version: The user sets the

Windows magnifying glass to 200%

and locates the legend. He completes

all tasks using only the chart

Accessible version: After reviewing the

chart, the user sets the zoom to 100%.

To complete all tasks, he looks at the

data labels on the bars of the chart. The

user frequently approaches the screen

He found the accessible version easier

to use. In the non-accessible version of

the stacked bar chart, it was diﬃcult to

distinguish between the two sections of

each bar

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 4

Handheld Magnifying Glass

Stacked bar chart Eﬀectiveness: The user answered tasks 1

and 4 incorrectly in the non-accessible

version. In the accessible version, the

user answered tasks 2 and 3 incorrectly

Eﬃciency: In all cases, the user took

longer to complete the tasks with the

non-accessible version, except for task

2. In task 2 of the accessible version,

the user initially consulted the chart and

then the table, while in the non-acces-

sible version, he looked for the answer

directly in the table

Non-accessible version: Upon opening

the chart, the user adjusts the browser

zoom level to 150% and uses a hand-

held magnifying glass to examine the

values in the table. For the ﬁrst task, he

relies solely on the chart, guided by the

axes and bar sizes. Starting from task 2,

he switches to using the table

Accessible version: After reviewing the

chart, the user sets the browser zoom to

133%. In the ﬁrst task, he inspects the

data labels of the bars. For task 2, he

reduces the browser zoom to 120% and

ﬁnds the answer in the data table. From

task 3 onward, he primarily uses the

chart and occasionally checks the axes

using the hand-held magnifying glass

The user found the accessible version

easier to use and, at times, had to rely on

the table when using the non-accessible

version

User 5

Browser’s zoom

Stacked bar chart Eﬀectiveness: the user correctly answers

all the questions with both charts,

except for task 2 with the non-accessi-

ble version

Eﬃciency: In all cases, the user took

longer to complete the tasks with the

non-accessible version. The diﬀer-

ence in completion times was most

signiﬁcant in task 1 (472.73%), task 3

(89.47%) and task 4 (118.52%)

Non-accessible version: the user consults

the data table when the question

involves the partial interpretation of

each bar, and the chart when it involves

the global interpretation of each stacked

bar. In task 4, she looks at the y-axis

and follows the line to compare the

bars. She needs to get closer to the

screen constantly

Accessible version: Throughout the

tasks, she reviews the chart to complete

them and is guided by the size of each

bar, the colors, and the data labels at

the top of each bar. She needs to get

closer to the screen constantly

She found the accessible version easier to

use, to the extent that she had to resort to

the table on some occasions when using

the non-accessible version

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 6

Zoom and inverted colors in MacOS

Stacked bar chart Eﬀectiveness: The user correctly answers

all the questions with both charts

Eﬃciency: In all cases, the user took

longer to solve the tasks with the

non-accessible version, except for task

3, in which he spent a few seconds

reading the caption. The diﬀerence

between versions is signiﬁcant in terms

of eﬃciency in tasks 1(73.33%); 2:

(112.73%); and 4: (108.33%)

Non-accessible version: After review-

ing the chart, the user turned oﬀ the

inverted color mode and tried diﬀerent

zoom settings. Whenever reading

text, the user approached the screen.

After hearing the ﬁrst task, the user

turned the inverted color mode back

on and read the title of the chart. He

applied the operating system zoom to

read the X-axis labels and browsed the

answers in the data table. For tasks

that required partial interpretation of

the bars, the user used the table. When

tasks required global interpretation of

each bar, the user consulted the chart

and veriﬁed the answer with the table.

For some tasks, the user followed the

axes with his ﬁnger. The inverted color

mode was activated when reading text

and deactivated when checking the bars

Accessible version: After reviewing the

chart, the user looked at the table and

tooltips. With the inverted color mode,

it was almost impossible to diﬀerenti-

ate the two sections of each bar. After

deactivating it, the diﬀerence between

the two sections improved, but the

user still could not distinguish them

correctly. He used the tooltips to solve

the tasks and also read the caption and

checked the table to verify the answers

He found the accessible version easier to

consult, while the non-accessible version

was very complicated

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 7

Windows magniﬁer and high contrast

mode. Handheld Magnifying Glass

Stacked bar chart Eﬀectiveness: the user correctly answered

all the questions with both charts,

except for task 1 with the accessible

version

Eﬃciency: In all cases, the user took

longer to complete the tasks with the

non-accessible version, except for task

2, where he was faster with the non-

accessible version when directly brows-

ing the table, which he did not do with

the accessible version. Additionally, in

the accessible version, he needed to use

the handheld magnifying glass, which

was unnecessary with the table

Non-accessible version: Initially, he reads

the chart title using a hand-held mag-

nifying glass and thoroughly examines

the entire page, paying particular atten-

tion to the colors of each section of the

bars. In task 1, he starts by using the

chart, but quickly switches to the table

to ﬁnd the answer. In task 2, he directly

consults the table, and from task 3

onwards, he reverts to using the chart

as his primary reference. Throughout,

he consistently employs the hand-held

magnifying glass and frequently con-

sults the data table

Accessible version: Initially, the user

looks for the legend to identify the

corresponding colors. Initially, he

ﬁnds it challenging to diﬀerentiate

between colors, although the contrast

eventually proves suﬃcient for him. He

also checks the chart. Throughout, he

primarily uses the chart to answer the

tasks, aided by a hand-held magnifying

glass to read the X-axis labels and the

data labels on the bars. He also com-

pares the lengths of the bars to solve

some tasks

He found both versions equally challenging

but prefers the non-accessible version

because the use of color makes it easier

for him to distinguish between the marks

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 8

Windows magniﬁer

Stacked bar chart Eﬀectiveness: The user correctly

answered all the questions with both

charts

Eﬃciency: In tasks 2, 4 and 5, the user

required more time to answer the ques-

tions with the non-accessible version.

In tasks 1 and 3, she needed more time

with the accessible version. In task 1,

this was because he used the data table

directly with the non-accessible ver-

sion, while with the accessible version,

she consulted the chart using the Win-

dows magnifying glass at 500%, which

required multiple moves to view the

necessary elements. In task 3, the vide-

oconferencing tool’s window interfered

with the chart, causing some delay as

he had to reposition it

Non-accessible version: Initially, she

examines the entire page containing the

chart. Then, she sets the Windows mag-

niﬁer glass to 500% and approaches the

screen. In tasks 1 and 2, she directly

uses the data table. Starting from task

3, she relies on the chart. Task 4 sees

her return to using the table due to

some diﬃculty understanding the ques-

tion, which partly explains the signiﬁ-

cant time diﬀerence between versions

(80s with the non-accessible chart and

30s with the accessible one). In task 5

she consults both the chart and the table

Accessible version: the user maintains

the same zoom level as in the previous

version. Initially, she reviews the entire

chart and mentions that she could see

the axis labels better with the previ-

ous non-accessible version. She also

notes that reading text vertically poses

a signiﬁcant barrier for her. In task 3,

the video conferencing tool window

overlaps some of the bars and interferes

with the task. In task 4, she uses the

Y-axis as a reference and follows a line

with the mouse pointer

She found the accessible version easier to

use

User 9

Browser’s zoom

Stacked bar chart Eﬀectiveness: the user answered all the

questions correctly with both charts

Eﬃciency: in most cases, the user took

longer to complete the tasks with the

non-accessible version, except for task

1, in where she initially misunderstood

the order of the values

Non-accessible version: Initially, the user

examines the entire chart. However, the

user expresses diﬃculty with this type

of bar chart and decides to rely solely

on the data table for all tasks. In task 4,

he brieﬂy refers to the chart to conﬁrm

the answer

Accessible version: Upon opening the

chart, the user reviews its content and

reads the caption. For all tasks, he uses

the data table instead of the chart

She found the non-accessible version to be

quite complicated, while she found the

accessible version easier to consult

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 10

Windows magniﬁer and browser’s zoom

Stacked bar chart Eﬀectiveness: The user correctly answers

all the questions asked with both charts,

except for tasks 2 and 4 with the acces-

sible version

Eﬃciency: In tasks 2, 4 and 5 the user

needed more time with the non-accessi-

ble version. However, in tasks 1 and 3,

he required more time with the acces-

sible version (2 and 5s, respectively).

In these cases, the user positively noted

the size and resolution of the numerical

values, as well as the selected colors

Non-accessible version: The user sets

the Windows magniﬁer zoom level

between 200 and 250%. Initially, the

user reviews the entire chart, reading

the title and axes, and notices the avail-

ability of a data table is available. The

user solves all tasks by comparing the

length of the bars. There don’t appear

to be any issues with diﬀerentiating

colors or interpreting the legend

Accessible version: The user sets

the Windows magniﬁer zoom level

between 200 and 250%. The user solves

all tasks by comparing the length of the

bars. When it is necessary to compare

the entire series, the user reduces the

zoom level to have a panoramic view

The user prefers the non-accessible version

due to the color selection. He also ﬁnds

the subtle color change when the mouse

cursor passes over the bar confusing in

the accessible version

User 11

Browser’s zoom

Stacked bar chart Eﬀectiveness: the user correctly answers

all the questions asked with both charts

Eﬃciency: in all cases, the user took

longer to solve the tasks with the non-

accessible version. The most signiﬁcant

diﬀerences in time spent are observed

in tasks 1 (15s vs. 6s), 2 (13s vs. 8s),

and 4 (14s vs. 6s)

Non-accessible version: the user main-

tains a zoom level of 100%. Task 1

requires consulting the table, while the

remaining tasks are solved by referring

to the chart

Accessible version: the user maintains a

zoom level of 100%. All the tasks are

solved by consulting the chart

She found the non-accessible chart to

be overly complicated. In contrast, she

appreciated the interactive features, such

as tooltips, in the accessible version

User 12

Windows magniﬁer and high contrast

mode. Screen reader

Stacked bar chart Eﬀectiveness: The user correctly answers

all the questions asked with both charts,

except task 1 with the non-accessible

version

Eﬃciency: The user took longer to

solve the tasks with the non-accessible

version in tasks 1 (with a ten-second

diﬀerence) and 2. On the other hand,

the user took longer to solve the tasks

with the accessible version in tasks 3, 4

and 5, but the diﬀerence were only 1s

(tasks 3 and 4) and 2s (task 5)

Non-accessible version: The user uses the

Windows magnifying glass and changes

the zoom level according to the task,

ranging from 100 to 150%. All tasks

are solved by comparing the length of

the bars and checking the legend

Accessible version: with this chart, the

user does not need to magnify the

screen with the Windows magniﬁer.

All tasks are solved by comparing the

length of the bars and checking the

legend and the tooltips

The user states that she found solving the

tasks with the non-accessible chart quite

complicated, while completing them with

the accessible chart was very easy

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 1

Browser’s zoom and Windows high

contrast mode

Line chart Eﬀectiveness: the user correctly answers

all the questions asked with both charts

Eﬃciency: in tasks 1, 4 and 5, the user

needed more time with the non-acces-

sible version. However, in tasks 2 and

3, the user required more time with the

accessible version for two reasons: (a)

the distance between the points of the

lines was smaller necessitating more

time to compare them; (b) he spent

additional time verifying the answer

with the tooltips before verbalizing it

Non-accessible version: the user applies

a 150% zoom with the browser and

approaches the screen. First, he reads

the legend and examines the entire

chart. To solve the tasks, he follows

the lines with the mouse pointer and

constantly consults the legend

Accessible version: ﬁrst, he scrolls

until he ﬁnds the legend. During the

process, he notices that tooltips appear

when hovering over the dots. The user

sets the browser zoom to 125% and

approaches the screen. To solve all the

tasks, he positions the cursor over the

point and reads the tooltips

He found the accessible version easier to

consult

User 2

Windows magniﬁer and high contrast

mode. Handheld Magnifying Glass

Line chart Eﬀectiveness: the user correctly answers

all the questions asked with both charts,

except for task 1 and 2 with the non-

accessible version

Eﬃciency: The user required more time

to complete tasks with the non-accessi-

ble version in all cases except for task

3. Like user 1, this can be attributed to

two reasons: (a) the smaller distance

between the points of the lines, requir-

ing more time for comparison; (b)

spending additional time verifying the

answer with tooltips before verbalizing

Non-accessible version: Initially, he

reviews the entire page and adjusts the

browser zoom to 125%. He examines

the caption and title. For tasks 1 and 2,

he tracks the lines and axes to answer

the questions. Task 4 presents a particu-

lar challenge due to the close proxim-

ity of the two lines, and he frequently

refers to the legend before answering

Accessible version: He begins by hover-

ing the mouse pointer over the chart to

check for tooltips. In task 1, he consults

the legend and, although he can distin-

guish the lines, he appears to use tooltip

information to answer the task. Starting

from task 3, he relies exclusively on

tooltips to address the questions

He found the non-accessible version to be

rather complicated, while the accessible

version was easier to use

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 3

Windows magniﬁer

Line chart Eﬀectiveness: the user correctly answered

all the questions asked with both charts

Eﬃciency: in tasks 1 and 4, the user

required more time to complete the

tasks with the non-accessible chart.

Conversely, in tasks 2, 3 and 5 it took

longer with the accessible version.

Notably, in task 5, the user needed

94.74% more time due to a lack of

understanding of the question

Non-accessible version: Initially, the user

sets the Windows magniﬁer glass to

200% and reads the chart title, explor-

ing the entire content on the screen,

including the X-axis labels and legend.

In task 1, he relies on legend to identify

each airport. However, in task 4, he

encounters diﬃculty distinguishing

between two closely spaced lines. For

all tasks, he tracks the lines using the

mouse pointer to ﬁnd the answers

Accessible version: At ﬁrst, the user

examines the entire chart. In task 1, he

consults the legend to associate each

line with its corresponding airport.

Starting from task 3, he utilizes the

tooltips to complete the tasks

He found the accessible version easier to

work with. In the non-accessible version,

he encountered diﬃculty distinguishing

between the lines

User 4

Handheld Magnifying Glass

Line chart Eﬀectiveness: the user answered task 4

incorrectly with the non-accessible ver-

sion and tasks 1 and 3 incorrectly with

the accessible version

Eﬃciency: In tasks 1 and 2 the user

required more time with the non-acces-

sible version. In tasks 3 and 4, more

time was needed with the accessible

version. Finally, in task 5, the user

required the same amount of time in

both versions. The increase in time for

tasks 3 and 4 with the accessible ver-

sion can be attributed to the user’s ini-

tial hesitation to interact with the chart,

instead preferring to consult the data

table as in the non-accessible version

Non-accessible version: Initially, the user

looks at the chart, and then sets the

browser zoom to 120%. During task 1,

increases the zoom to 150% but strug-

gles to locate the legend. Eventually,

the user solves the task using the table.

For the remaining tasks, the user relies

solely on the table

Accessible version: in this case, the user

maintains the zoom at 150%, although

starting from task 3 the zoom is

reduced to 133%. While reviewing the

chart, the user discovers the tooltips.

For all tasks, except the second one,

the user utilizes the tooltips. In the

second task, there were learning eﬀects

observed. Additionally, in the fourth

task, the user uses the hand magnifying

glass

He found the accessible version easier to

consult. In the case of the non-accessible

version, the user explains that he has had

to consult the table for all tasks

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 5

Browser’s zoom

Line chart Eﬀectiveness: The user correctly answers

all the questions asked with both charts

Eﬃciency: In tasks 1, 4 and 5 she needed

more time with the non-accessible ver-

sion, while in tasks 2 and 3, she needed

more time with the accessible one. The

increase in time in tasks 3 and 4 with

the accessible version is because, in the

non-accessible one she directly consults

the data table, while in the accessible

one, she reviews the entire chart with-

out consulting the table

Non-accessible version: First, she looks

at the chart. During the ﬁrst task, she

informs the moderator that she will use

the data table exclusively

Accessible version: In tasks 1 and 2, she

consults the legend to identify each

line. In all tasks, she uses the chart and

does not seem to have great diﬃculty in

diﬀerentiating the lines

She found the accessible version easier to

consult. The user explains that without

the data table, he would have had a hard

time solving the tasks of the non-accessi-

ble version

User 6

Zoom and inverted colors in MacOS

Line chart Eﬀectiveness: the user correctly answers

all the questions asked with both charts

Eﬃciency: in tasks 1, 2 and 5, the user

needed more time with the non-

accessible version. The most signiﬁcant

increase is in task 5 with a 178.33%

increase in time. In tasks 3 and 4, the

user needed more time with the acces-

sible version (165.22% and 176.47%,

respectively). This is because when the

zoom is applied, the tooltips obscure

practically the entire chart, making it

diﬃcult to see the lines

Non-accessible version: the user activates

the inverted color mode and the macOS

screen magniﬁer. First, he reviews the

chart and reads the title. In task 1, he

ﬁnds the legend and deactivates the

inverted color mode. He then turns it

back on to read the title and X-axis

labels. The user states that he sees the

text better with the inverted color mode,

but that the colors are better diﬀerenti-

ated without it. In task 2, he consults

the chart and veriﬁes the answer with

the table. Task 5 is particularly diﬃcult

for him, and he ends up using the table

Accessible version: with the color mode

inverted, he reviews the chart and table

and also reads the caption. In task 1,

he reviews the legend and the chart.

In task 2, he consults the tooltips and

veriﬁes the answer with the table. In

task 3, he uses the chart and veriﬁes

the answer with the table. In task 4, the

tooltips interfere when he is following

the lines with the mouse pointer, and

he decides to use the table. In task 5,

he starts by consulting the chart, but

ﬁnally uses the table

He found the accessible version easier

to consult and appreciate the abil-

ity to resize the image without losing

deﬁnition. However, he did not like the

inability to deactivate the tooltips

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 7

Windows magniﬁer and high contrast

mode. Handheld Magnifying Glass

Line chart Eﬀectiveness: the user correctly answers

all the questions asked with both charts

Eﬃciency: In tasks 1, 4 and 5, the user

required more time with the non-acces-

sible version. However, in tasks 2 and

3, the user needed more time with the

accessible version. This was because

the distance between the points of the

lines was smaller, requiring more time

for comparison

Non-accessible version: when open-

ing the chart, the user verbalizes the

colors of each line. In the ﬁrst task, the

user consults the legend and reads the

X-axis title using a hand-held magnify-

ing glass. In the second task, there

were observed learning eﬀects. For the

subsequent tasks, the user continues

to use the hand magniﬁer to follow the

lines and axes

Accessible version: After opening the

chart, the user reviews the legend to

diﬀerentiate the lines of the chart. For

most of the tasks, the user uses a hand

magnifying glass to solve them

He found the accessible version somewhat

easier to use

User 8

Windows magniﬁer

Line chart Eﬀectiveness: the user correctly answers

all the questions asked with both charts,

except task 3 with the accessible ver-

sion

Eﬃciency: In tasks 4 and 5, she needs

more time to solve the tasks with the

non-accessible version. However, in

tasks 1, 2 and 3 (with a signiﬁcant

increase of 1120% in task 3), she

requires more time with the accessible

version. This is because with the zoom

at 500%, she can only see a very limited

portion of the screen, which is further

obscured by the tooltips. Additionally,

in task 3, the user appears to be getting

tired

Non-accessible version: Upon viewing

the chart, she notices that the Y-axis

values are very small and pixelated.

Consequently, she looks at the data

table and increases the Windows

magnifying glass to 500%. In task 1,

she successfully locates the legend to

identify each line. However, in tasks 2

and 3, she relies on the data table for

answers. For task 4, she initially con-

sults the chart, but ultimately resorts to

the table. In task 5, she attempts to use

the chart again but struggles due to the

high zoom level, leading her to return

to the table

Accessible version: In this instance, she

maintains the Windows magnifying

glass at 500%. In task 1, she encounters

interference from the video conferenc-

ing tool window, which she must relo-

cate. During task 2, she starts by con-

sulting the chart, but ﬁnds the tooltips

bothersome, prompting her to switch

to the table. In task 3, she expresses

fatigue. Finally, in tasks 4 and 5, she

relies on the table exclusively

She found the non-accessible version

easier to consult

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Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 9

Browser’s zoom

Line chart Eﬀectiveness: the user correctly answers

all the questions asked with both charts,

except for task 1 with the non-accessi-

ble version

Eﬃciency: in tasks 1, 2, and 4, the user

takes longer with the non-accessible

version. In task 3, the user takes longer

with the accessible version initially

due to a mistake and its rectiﬁcation.

Finally, in task 5, the user takes the

same amount of time with both versions

Non-accessible version: the user men-

tions that she can easily see both the

chart and the data table. She consist-

ently uses the data table to respond

while moving closer to the computer

screen

Accessible version: the user reports that

she can easily see both the chart and the

data table. Additionally, she reads the

caption. Like the non-accessible ver-

sion, she relies on the data table for her

responses and adjusts her proximity to

the computer screen as needed

She found the accessible version easier to

work with

User 10

Windows magniﬁer and browser’s zoom

Line chart Eﬀectiveness: the user correctly answered

all the questions asked with both charts,

except for task 4 with the non-accessi-

ble version

Eﬃciency: the user needed more time

with the accessible version in all tasks

except for task 4. The main reason for

this is that the zoom level applied to the

accessible version caused part of the

chart to be oﬀ the screen, leading the

user to scroll constantly to compare and

review values

Non-accessible version: the user sets the

zoom level of the Windows magniﬁer

between 200 and 250%. The user solves

all tasks by comparing the height of the

points on each line. He does not seem

to have trouble diﬀerentiating the colors

or interpreting the legend

Accessible version: The user must reduce

the zoom level to see the entire chart

on the screen. The user mentions that

if both lines were the same (one is

continuous and the other is dotted), it

would be very diﬃcult to diﬀerentiate

between them. He solves all tasks using

the chart only, without consulting the

table

The user prefers the non-accessible version

because, after zooming in, a part of the

chart has been left out of his screen,

requiring more movements to compare

data. Additionally, the user mentioned

that the subtle change of color when

the mouse cursor passes over the bar is

confusing

User 11

Browser’s zoom

Line chart Eﬀectiveness: the user correctly answers

all the questions asked with both charts

Eﬃciency: the user needed more time

with the accessible version in all tasks

except task 3. Task 2 required the same

amount of time in both versions. In task

1, he took twice as long with the non-

accessible version (14s vs. 7s)

Non-accessible version: the user main-

tains a zoom level of 100%. She con-

sults the charts to solve all tasks, except

for tasks 4 and 5, where she needs to

refer to the data table

Accessible version: the user also main-

tains a zoom level at 100%. All tasks

are completed by consulting the chart

In this case, she found it easier to use the

accessible chart because it includes a

complete grid

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comparisons within the chart. In this sense, tasks focused

on comparing data have been performed better (more eﬃ-

ciently) with the accessible versions of the charts.

In the accessible versions of the charts, a tooltip func-

tionality has been implemented to provide the value of the

selected mark (bar or point) as an alternative to legends

(H2). Tooltips have been useful for all users, except for user

9 who preferred to use the data table (H6). This functional-

ity, used by almost all users, has been highly valued by users

1, 3 and 5, while users 6 and 8 in the interaction with the

line chart have highlighted the fact that the tooltips obscured

the chart preventing them from following the lines and see-

ing the marks, especially after magnifying the screen. In

this case, the accessible chart does not meet the dismissible

requirement associated with the success criterion 1.4.13

(Content on hover of focus) of the WCAG 2.1 [82], which

could solve the diﬃculty mentioned by users.

“In the case of interactive charts, you have all the

information at your ﬁngertips. You consult a point and

see all the related information without looking at two

places at the same time.” (user 11).

“Tooltips are nice, but with a zoom applied they cover

too large a part of the chart. It would be interesting if

they were optional, for example, that they only appear

after clicking on them.” (user 6).

“With the second type of charts (referring to the acces-

sible charts) I have not needed to use zoom at any time

because the data is near the bars and points. I simply

needed to approach a little more on the screen.” (user

12).

All users have followed the strategy of following the axes

(H3) and the marks with the cursor pointer.

When bitmap images (Microsoft Excel exports) were

resized, the problem of their low quality was more pro-

nounced, creating legibility problems (H12) for users 2,

3, 4, 5, 6, 7, 8 and 9 (Fig.4). For user 2 there was even a

problem diﬀerentiating the bars of the ﬁrst chart due to the

poor quality of the image. Speciﬁcally, he stated “it seems

to be missing pixels”. Insuﬃcient contrast (H11) between

the text color used by default by Microsoft Excel and the

background has also been a barrier for these users even

Table 10 (continued)

User Chart Eﬀectiveness and eﬃciency Observations Satisfaction

User 12

Windows magniﬁer and high contrast

mode. Screen reader

Line chart Eﬀectiveness: the user correctly answered

all the questions asked with both charts,

except for task 4 with the non-accessi-

ble version

Eﬃciency: The user needed the same

amount of time for both versions in

task 2. For the remaining tasks, she

completed them more quickly with the

non-accessible version, except for task

4 where there was a diﬀerence of 2 to

25s in completion time

Non-accessible version: the user employs

the Windows magnifying glass and

sets the zoom level to 125%. In task 3,

she has diﬃculty seeing the blue line

clearly and increases the zoom level

to 150%. She completes all tasks by

comparing the height of the points on

each line and referencing the legend. It

is possible that the table, which is oﬀ

the screen, went unnoticed by the user

Accessible version: with this chart, the

user does not require screen magniﬁca-

tion through the Windows magniﬁer.

She resolves all tasks by comparing the

height of the points on each line and

referring to the tooltips

The user states that she found solving the

tasks with the non-accessible chart quite

complicated, while those with the acces-

sible chart were very easy. One of the

main factors was the poor deﬁnition of

the non-accessible chart after zooming in

Fig. 4 Detail of the low quality of the non-accessible bar chart resized

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after being resized. In all these cases, the users have solved

the tasks using the data table (H6) available, not the chart.

“In the ﬁrst versions (referring to the non-accessible

charts) I noticed fewer sharp charts and worse con-

trast. The poor sharpness of the text also aﬀected me

a lot.” (user 8).

In all cases, users have initially used the chart to solve

the tasks. Only when they have been unable to ﬁnd the

answer, they have used the data table to ﬁnd it, or they

have used it to conﬁrm their answers before verbalizing

it (users 5, 6 and 7). User 6 was the only one to recog-

nize that he preferred to consult the table rather than the

chart in all cases. Users 7, 8 and 9 (the two last due to

poor color perception) found that their eﬃciency improved

when using the data table after the ﬁrst task and have used

it more frequently since then.

“It is easier to see the data in a chart than in a table”

(user 1).

“In some cases (referring to non-accessible charts) I’d

rather go to the table and deal directly with data than

consult the chart, because the lines and dots are too

thin for me” (user 5).

“When I read a scientiﬁc paper (the user is a researcher

in the ﬁeld of genetics), I never consult the charts

because they are totally inaccessible. At most, they

worry about color blindness, but not about other issues

that aﬀect people with low vision. I always prefer data

tables than charts”. (user 6).

“For all the questions I needed to consult the table. I

always use the tables to solve this kind of situations.”

(user 9).

Every user, except for user 9 (who exclusively relied

on the data table), frequently used legends to interpret the

data (H2). Throughout the test, we observed diﬃculties in

locating the legend when it was not positioned at the bottom

of the chart or when it went oﬀ the screen due to applied

zoom. In this regard, the suggestion put forth by Evergreen

and Metzner [94] to label data directly, in close proximity

to data points (such as on top of or beside bars and next

to lines), can not only reduce cognitive load and facilitate

more eﬃcient information processing but also aid users with

low vision in comprehending data series without the need

for constant scrolling through the interface. We have also

observed diﬃculty in diﬀerentiating the data series if the

color was not suﬃciently distinguishable (H10) or the size

of the legend was not suﬃcient (fonts set to Calibri, 9 pt. In

not-accessible charts).

In accessible versions of the bar chart and the stacked-bar

chart, when a data series receives the focus (H16), the rest

of the bars are displayed with less contrast to highlight the

active element. This has been a barrier for user 10, who has

expressed that it has confused him.

5 Discussion andlimitations

The paper describes the results of an ongoing study that

aims to verify a list of heuristics with users. The relatively

small number of users does not allow to statistically validate

the results nor to generalize them to the whole population,

but the authors consider that the insights collected with this

ﬁrst approach are relevant and give light to barriers and

priorities.

The observations made during the test heightened the

authors’ awareness of the diverse preferences and strate-

gies within the low vision users’ group, emphasizing the

necessity to gain a deeper understanding of these interac-

tions. Consequently, the authors have chosen to incorporate

a thorough description of each user’s results, strategies, and

preferences in the article. This information is deemed invalu-

able for future research in the ﬁeld.

Due to COVID lockdowns, the tests were conducted

remotely, and the interface of the video conferencing plat-

form occasionally disrupted the eﬃciency of users. Some

users had to spend part of their time minimizing the plat-

form’s interface. This is a signiﬁcant consideration for the

authors and may also be a determining factor to address in

future tests.

From the results obtained, we can derive some insights:

a global view of the chart is very informative and users rely

on it for comparative evaluations and trends; they look at it

with a size that ﬁts on screen, with not much zoom; instead

the use of zoom is very important to read text, axes, labels,

legends or tooltips, with many users using levels of zoom

much bigger than the 200% level established by WCAG. A

mechanism speciﬁc for these elements not aﬀecting the chart

should be developed and tested with users. Insight (a): a

zoom option speciﬁc for text elements not aﬀecting the chart

should be devised, and it shall be ﬂexible for zooms over

200%. Tooltips have been an important source of informa-

tion but also created some problems obscuring parts of the

charts. Insight (b): oﬀer zoomable tooltips (see insight a),

but callable on demand. Black and white charts did not sat-

isfy some users, emphasizing the need to redundantly encode

categories with both colors and patterns to cater to diverse

user proﬁles and their preferences. Insight (c): oﬀer color

categories with high contrast, plus patterns, better than black

and white coloring. The data table emerged as a useful alter-

native, particularly in non-accessible versions, enhancing

task eﬃciency for many users who have solved the tasks by

combining both the chart and table. Insight (d): always oﬀer

data in a table as a complement. On the observations many

users follow axes to ﬁnd a speciﬁc value in the chart. Insight

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(e): include axes in the charts as guides for locating speciﬁc

points. Challenges were identiﬁed regarding the legend’s

position and size, and addressing these aspects is essential

to eliminate potential barriers. Insight (f): provide a legend

to understand the data. Ensure that its position, size, colors

and contrast do not impose any barrier to users.

The test is proof that in most cases, users prefer to solve

tasks using the chart, even if it is not accessible, instead of

using the data table. This conﬁrms the results of other stud-

ies in which the use of the residual vision was preferred over

other strategies [65, 66].

The tooltips, which, as we have highlighted previously,

have been highly valued by all users, have been shown to

be useful for: (a) giving direct access to the data associated

with each mark, avoiding forcing users to consult the data

table; and (b) serving as an alternative or complement to the

legend. However, tooltips generated by Highcharts library

do not comply with the accessibility recommendations of

WCAG 2.1 and part of the literature [95, 96], as it is not

possible to hide them in case of overlay with other elements.

The order of the bars was key to interpret the time series

data for users 3, 4 and 6. The recommendation of sorting the

axes chronologically is also cited in the literature [97, 98].

Users 1, 2, 4, 5, 7, 10, 11 and 12 solved the tasks using

the browser zoom set between 110 and 200%. In the acces-

sible version of the charts, this means that content needs to

reﬂow to avoid horizontal scrolling, clipping, or overlapping

of elements. This functionality associated with the respon-

sive web design technique is implemented by the Highcharts

library, but in some cases, it has presented some unexpected

behavior that has involved usability problems that of course

aﬀects accessibility, such as some labels disappearing (see

Fig.5).

Currently, Microsoft Excel does not provide accessible

defaults for creating a new chart. However, it is possible

to create fairly accessible charts. Exporting charts to non-

Microsoft formats like HTML is also very problematic in

terms of accessibility properties. Only an expert author will

be able to create a moderately accessible chart.

The tasks were primarily centered on visual perception

rather than testing data literacy and chart comprehension.

Consequently, we designed the charts to be suﬃciently clear

and comprehensible for all users, regardless of their educa-

tional level. Notably, we found no signiﬁcant diﬀerences in

the results between users with the lowest educational attain-

ment and the rest of the users.

At the outset of this publication, we conducted a theo-

retical comparison between the heuristic indicators pro-

posed by Elavsky etal. [80] and our own set of heuristics.

Although Elavsky and colleagues’ work is highly relevant,

our user tests were conducted prior to its publication, pre-

venting a direct comparison. However, the theoretical analy-

sis revealed that Alcaraz etal.’s set of heuristic indicators

encompasses all the principles proposed by Elavsky etal.

[80]. Notably, Elavsky’s list comprises a larger number of

more speciﬁc heuristics and aims to address a broader range

of disabilities, whereas Alcaraz’s heuristics are tailored to

the speciﬁc needs of users with low vision.

The list of heuristic principles associated with this

research also includes certain principles that provide advan-

tages or help in overcoming accessibility challenges for

individuals with various disabilities, including those who

are blind, have motor or cognitive impairments. These prin-

ciples, considered as a universal set of best practices, oﬀer

beneﬁts to the wider public, irrespective of their disability

status. Table11 provides a summary of these principles.

The results of the user tests underscored the importance

of incorporating tooltips or directly labeling data on the

chart’s marks as an alternative or complement to using leg-

ends (H2). Tooltips and direct data labeling provide users

with immediate access to data associated with each mark,

eliminating the need to consult the data table or scroll

through the interface. Additionally, they reduce cognitive

load and promote more eﬃcient information processing [94].

Data labels can also draw attention to speciﬁc data points,

making them valuable when data values are essential [98].

However, when implementing tooltips, the following con-

siderations should be taken into account: (a) tooltips should

be hidden by default; (b) their use should be restricted to

situations where concise and useful information is provided;

ensure compatibility with both mouse and keyboard interac-

tions; (e) use arrows, akin to comic bubbles, to guide users

to the relevant element; (f) maintain suﬃcient contrast for

readability; (g) avoid obstructing or concealing other related

elements with the tooltip [99].

Furthermore, based on the test results, we will introduce

two new requirements to enhance the H2 heuristic concern-

ing legends: (a) The legend must be of suﬃcient size to

enable users to distinguish the colors or patterns associated

Fig. 5 Detail of the accessible bar chart showing the absence of some

labels

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with each mark eﬀectively; (b) The legend must be posi-

tioned either at the bottom of the chart or in a standardized

and highly visible location.

6 Conclusions andfuture work

The user test aimed at validating heuristic indicators for

assessing the accessibility of statistical charts has provided

valuable insights. The study involved 12 users with diﬀerent

low vision conditions, and the accessible versions of charts

demonstrated superior eﬃciency, eﬀectiveness, and user sat-

isfaction. The evaluation conducted using the think-aloud

method allowed us to visualize, from the users’ perspective,

those elements that constitute barriers to task completion,

as well as the strategies that each user employs to overcome

them. Another crucial aspect of these user tests has been

the opportunity to comprehend speciﬁc preferences that

may not necessarily align with the best practices commonly

acknowledged in the existing literature. A notable example is

the preference for color charts, even among users with CVD.

From a qualitative point of view, the heuristics related to

legends (H2), axes (H3), data source as a data table (H6),

safe colors (H10), contrast (H11), legibility (H12), image

quality (H13), resize options (H14), focus visibility (H16),

avoid disturbing elements (H15), and independent naviga-

tion (H17) proved to be crucial for task performance.

Legend (H2) is essential to understand the data. Its

position and size, as well as the colors (H10) and contrast

(H11) used, can negatively inﬂuence the eﬀectiveness and

eﬃciency if they are not designed following accessibility

guidelines. On the other hand, labelling the values directly

in the chart marks or implementing tooltips are even better

alternatives. For users with CVD, it is essential to use safe

color combinations or patterns to diﬀerentiate the marks.

However, the combinations based on white, black and grey

produce an eﬀect of visual saturation in certain users, espe-

cially in those who preserve the perception of color. Con-

sidering the suitability of color to encode categories [100]

Table 11 Summary of the advantages linked to adhering to the suggested heuristic indicators for diﬀerent user proﬁles

User proﬁle Barriers/rationale Heuristic related

Blind Inability to access visual content H1. Title

H2. Legend

H3. Axes titles

H4. Caption

H5. Abbreviations

H6. Data source

H8. Short text alternative

H9. Long description

H17. Device independent navigation

Motor Diﬃculty in using the mouse or keyboard

Ensuring accessibility for this group relies on making interactive elements, like buttons and

selectors, large enough and ensuring tasks are designed with ample completion time and

minimal required actions

H14. Resize

H17. Device independent navigation

H18. Customization

Cognitive Challenges arising from language comprehension and content complexity

Users who rely on screen readers beneﬁt from heuristic principles designed for individuals

with visual impairments, including concise alternative texts and comprehensive descrip-

tions, which also serve as condensed representations of complex material

H1. Title

H2. Legend

H3. Axes titles

H4. Caption

H5. Abbreviations

H6. Data source

H8. Short text alternative

H9. Long description

H18. Customization

Any user Challenges in comprehending the message conveyed by a statistical chart

Heuristics principles play a valuable role in enhancing the readability of charts for all users,

not just those with disabilities. Principles related to content customization (e.g. H14 or

H18), allow users to tailor the presentation to their preferences or device characteristics,

improving overall user satisfaction during content interaction

H1. Title

H2. Legend

H3. Axes titles

H4. Caption

H5. Abbreviations

H6. Data source

H7. Print version

H12. Legibility

H13. Image quality

H14. Resize

H15. Without disturbing elements

H18. Customization

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and that some users prefer it over monochrome interfaces,

a possible conclusion of the test is the need to redundantly

encode categories with colors and patterns as well, to target

all proﬁles.

Of equal importance to the legend are the titles of the

axes (H3). Both have been used by all users to understand

the data. Using vertical text on the y-axis does not seem

to have been a problem for any user. On the contrary, low-

quality images of text hinder the legibility of the legend and

axes text (H13).

Providing access to the data source as a table (H6) allows

users to have a highly eﬃcient, fully text-based alternative

when the task involves searching for a particular datum.

Also, as observed during the test, it is useful to verify an

answer before delivering the task. For this reason, and

considering the challenges faced by individuals with more

severe low vision in accessing charts, the presence of an

equivalent table becomes indispensable.

Another common barrier has been insuﬃcient image

quality (H13) of non-accessible charts to cope with demand-

ing resizes (up to 500%) (H14). In such cases, legibility

(H12) is compromised and the use of charts in vector for-

mat is the best alternative because they can be enlarged as

much as necessary without losing quality [37]. Another of

vector charts’ advantages is their complete integration with

the Document Object Model (DOM), that grants the ability

to manipulate and customize them as any other HTML ele-

ment and makes them compatible with assistive technology

[101, 102].

Other works highlight the diﬃculties that users with low

vision experience when interacting with screen magniﬁers

[103–105], because they only have a partial view of the page

they are interacting with, and this can cause loss of context

since not all the elements necessary to interpret or interact

with the content are displayed on the screen. This is a com-

mon issue when interacting with a chart whenever the task

requires comparing data. This requirement seems to lead to

designs with reﬂow, to avoid horizontal scrolling, clipping,

or overlapping of elements (H14), but this only worked for

users using browser zoom and not for those using screen

magniﬁers with magniﬁcations much greater than 200%.

The heterogeneity of needs and preferences among par-

ticipants leads to test personalization techniques (H18) as

a key factor to ensure the best accessibility in the greatest

number of possible situations. However, as other works

point out [63] one single method of adapting the presen-

tation of the charts may not be suﬃcient to meet all the

requirements for people with low vision.

With the user test conducted in this research, we have

successfully followed all the steps outlined in the method-

ology by Quiñones etal. [81], aﬃrming the validation and

reliability of our heuristic set.

In these tests, the authors decided to start with simple

charts. With more complex charts it might be possible to

ﬁnd a larger number of barriers (this was even mentioned

by users 2 and 8).

As a future research direction the authors aim to test

how complexity aﬀects the barriers encountered by the

users and also the eﬀect of customization options (H18),

to allow users to change mark colors, font style and font

size, among others.

The main line of future work is trying to recruit new

users, to cover most low vision proﬁles to continue review-

ing the list of heuristic indicators and improve it by reﬁn-

ing the guidelines and doing a new iteration in the deﬁ-

nition and scoring of the heuristic set. Further work is

required to plan other types of tasks that allow validating

some of the heuristics not contemplated in this study (H1,

Title; H4, Caption; H5, Abbreviations; H7, Print version;

H8, Short text alternative; H9, Long description; H18,

Personalization).

Acknowledgements We would like to thank Associació Discapacitat

Visual Catalunya: B1+B2+B3 for having provided us with the contact

for most of the users participating in the study. ChatGPT (GPT-3.5,

OpenAI’s large-scale language-generation model) has been used to

improve the writing style of this Article. The authors reviewed, edited,

and revised the ChatGPT generated texts to his own liking and take

ultimate responsibility for the content of this publication.

Author contributions R.A. and M.R. have overseen the conceptualiza-

tion, administrated of the research, and the bibliographic search. R.A.

and M.R have deﬁned the methodology. A.A and A.P have conducted

and record the user tests. R.A and M.R. wrote the main manuscript

text and prepared all the ﬁgures. All authors have performed an initial

review of the manuscript. Finally, M.R has conducted a formal review

of the entire manuscript.

Funding Open Access funding provided thanks to the CRUE-CSIC

agreement with Springer Nature. This work was partially funded

by Spanish project PID2022-141566NB-I00 (AEI-MICINN).

This work also has been partially supported by the Spanish project

PID2022-136436NB-I00 (AEI-MICINN).

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Color Vision Deficiency Recognition Based on Eye-Tracking Metrics Using Machine Learning Approaches

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Data, Data, Everywhere: Uncovering Everyday Data Experiences for People with Intellectual and Developmental Disabilities

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Mar 2023

Data is everywhere but may not be accessible to everyone. Conventional data visualization tools and guidelines often do not actively consider the specific needs and abilities of people with Intellectual and Developmental Disabilities (IDD), leaving them excluded from data-driven activities and vulnerable to ethical issues. To understand the needs and challenges people with IDD have with data, we conducted 15 semi-structured interviews with individuals with IDD and their caregivers. Our algorithmic interview approach situated data in the lived experiences of people with IDD to uncover otherwise hidden data encounters in their everyday life. Drawing on findings and observations, we characterize how they conceptualize data, when and where they use data, and what barriers exist when they interact with data. We use our results as a lens to reimagine the role of visualization in data accessibility and establish a critical near-term research agenda for cognitively accessible visualization.

Review of chart image detection and classification

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Jan 2023
INT J DOC ANAL RECOG

This paper presents a complete review of different approaches across all components of the chart image detection and classification up to date. A set of 89 scientific papers is collected, analyzed, and enlisted into four categories: chart-type classification, chart text processing, chart data extraction, and chart description generation. Detailed information about problem formulation and a research field is provided, and an overview of used methods in each category. Each paper's contribution is noted, including the essential information for authors in this research field. In the end, a comparison is made between the reported results. The state-of-the-art methods in each category are described, and a research direction is given. We have also analyzed the open challenges that still exist and require the author's attention.

How accessible is my visualization? Evaluating visualization accessibility with Chartability

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Full-text available

Aug 2022
COMPUT GRAPH FORUM

Novices and experts have struggled to evaluate the accessibility of data visualizations because there are no common shared guidelines across environments, platforms, and contexts in which data visualizations are authored. Between non‐specific standards bodies like WCAG, emerging research, and guidelines from specific communities of practice, it is hard to organize knowledge on how to evaluate accessible data visualizations. We present Chartability, a set of heuristics synthesized from these various sources which enables designers, developers, researchers, and auditors to evaluate data‐driven visualizations and interfaces for visual, motor, vestibular, neurological, and cognitive accessibility. In this paper, we outline our process of making a set of heuristics and accessibility principles for Chartability and highlight key features in the auditing process. Working with participants on real projects, we found that data practitioners with a novice level of accessibility skills were more confident and found auditing to be easier after using Chartability. Expert accessibility practitioners were eager to integrate Chartability into their own work. Reflecting on Chartability's development and the preliminary user evaluation, we discuss tradeoffs of open projects, working with high‐risk evaluations like auditing projects in the wild, and challenge future research projects at the intersection of visualization and accessibility to consider the broad intersections of disabilities.

Rich Screen Reader Experiences for Accessible Data Visualization

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Full-text available

Aug 2022
COMPUT GRAPH FORUM

Current web accessibility guidelines ask visualization designers to support screen readers via basic non‐visual alternatives like textual descriptions and access to raw data tables. But charts do more than summarize data or reproduce tables; they afford interactive data exploration at varying levels of granularity—from fine‐grained datum‐by‐datum reading to skimming and surfacing high‐level trends. In response to the lack of comparable non‐visual affordances, we present a set of rich screen reader experiences for accessible data visualization and exploration. Through an iterative co‐design process, we identify three key design dimensions for expressive screen reader accessibility: structure, or how chart entities should be organized for a screen reader to traverse; navigation, or the structural, spatial, and targeted operations a user might perform to step through the structure; and, description, or the semantic content, composition, and verbosity of the screen reader's narration. We operationalize these dimensions to prototype screen‐reader‐accessible visualizations that cover a diverse range of chart types and combinations of our design dimensions. We evaluate a subset of these prototypes in a mixed‐methods study with 13 blind and visually impaired readers. Our findings demonstrate that these designs help users conceptualize data spatially, selectively attend to data of interest at different levels of granularity, and experience control and agency over their data analysis process. An accessible HTML version of this paper is available at: http://vis.csail.mit.edu/pubs/rich-screen-reader-vis-experiences.

Delivering data differently

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Full-text available

Apr 2022

Human-computer interaction relies on mouse/touchpad, keyboard, and screen, but tools have recently been developed that engage sound, smell, touch, muscular resistance, voice dialogue, balance, and multiple senses at once. How might these improvements impact upon the practice of statistics and data science? People with low vision may be better able to grasp and explore data. More generally, methods developed to enable this have the potential to allow sighted people to use more senses and become better analysts. We would like to adapt some of the wide range of available computer and sensory input/output technologies to transform data science workflows. Here is a vision of what this synthesis might accomplish.

The Effect of Cataract on Color Vision Measurement with the Low-Vision Cambridge Colour Test: Providing an Adjustment Factor for Clinical Trials

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Full-text available

Apr 2022

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Towards accessible chart visualizations for the non-visuals: Research, applications and gaps

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Accessible Visualization via Natural Language Descriptions: A Four-Level Model of Semantic Content

Article

Sep 2021

Natural language descriptions sometimes accompany visualizations to better communicate and contextualize their insights, and to improve their accessibility for readers with disabilities. However, it is difficult to evaluate the usefulness of these descriptions, and how effectively they improve access to meaningful information, because we have little understanding of the semantic content they convey, and how different readers receive this content. In response, we introduce a conceptual model for the semantic content conveyed by natural language descriptions of visualizations. Developed through a grounded theory analysis of 2,147 sentences, our model spans four levels of semantic content: enumerating visualization construction properties (e.g., marks and encodings); reporting statistical concepts and relations (e.g., extrema and correlations); identifying perceptual and cognitive phenomena (e.g., complex trends and patterns); and elucidating domain-specific insights (e.g., social and political context). To demonstrate how our model can be applied to evaluate the effectiveness of visualization descriptions, we conduct a mixed-methods evaluation with 30 blind and 90 sighted readers, and find that these reader groups differ significantly on which semantic content they rank as most useful. Together, our model and findings suggest that access to meaningful information is strongly reader-specific, and that research in automatic visualization captioning should orient toward descriptions that more richly communicate overall trends and statistics, sensitive to reader preferences. Our work further opens a space of research on natural language as a data interface coequal with visualization.

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