Information Visualization and the Challenge
of Universal Usability
Catherine Plaisant,
plaisant@cs.umd.edu
FINAL VERSION WILL APPEAR as Chapter 3 in
J. Dykes,
A.M. MacEachren, M.-J. Kraak (Editors), Exploring
Geovisualization, Elsevier, 2005
Abstract
Information Visualization aims to provide compact
graphical presentations and user interfaces for interactively manipulating
large numbers of items. We present a simple “data by tasks taxonomy” then
discuss the challenges of providing universal usability, with example
applications using geo-referenced data. Information Visualization has been
shown to be a powerful visual thinking or decision tool but it is becoming
important for services to reach and empower every citizen. Technological
advances are needed to
deal with user diversity (age, language, disabilities,
etc.) but also with the variety of technology used (screen size, network speed,
etc.) and the gaps in user’s knowledge (general knowledge, knowledge of the
application domain, of the interface syntax or semantic). We present examples
that illustrate how those challenges can be addressed.
3.1 Introduction
Designers are discovering how to use rapid and
high-resolution color displays to present and manipulate large amounts of information
in compact and user-controlled ways. Information Visualization can be defined
as the use of computer-supported interactive visual representation of abstract
data to amplify cognition (Card et al., 1999). The abstract characteristic of
the data is what distinguishes Information Visualization from scientific
visualization. Information Visualization is more likely to be used to display
database content (for example, recorded stock values, health statistics) than.output
of models or simulations, but this distinction is not always important. The
display of geo-referenced data is often a hybrid visualization that combines
abstract and concrete data. In fact several of the most famous examples of
Information Visualization include maps, from the 1861 representation of the
ill-fated Napoleon’s Russian campaign by Minard (see Tufte (1983) and Kraak
(undated)) to the interactive HomeFinder application shown in Figure 3.1 that
introduced the concept of dynamic queries (Ahlberg et al., 1992). Information
Visualization aims to provide compact graphical presentations and user
interfaces for interactively manipulating large numbers of items (102–106), possibly extracted
from far larger datasets (Card et al., 1999; Spence, 2001; Ware, 2000; Chen, 2002;
Bederson and Shneiderman, 2003). Also sometimes called visual datamining, it uses
the enormous visual bandwidth and the remarkable human visual system to enable users
to make discoveries, take decisions, or propose explanations about patterns,
groups
of items, or individual items. Perceptual
psychologists, statisticians, and graphic designers (Tufte, 1983) offer
valuable advice about presenting static information, but advances in processor
speed, graphic devices and dynamic displays takes user–interface designers well
beyond current wisdom.
This chapter presents a simple “data by tasks
taxonomy” then discusses the challenges of providing “universal usability”,
with example applications using georeferenced data.
Figure 3.1. The
HomeFinder. Houses for sale appear as yellow dots on a stylized map of
feedback (within 10 ms)
is provided on the map showing the houses that match the query, and
allowing users to pose
hundreds of queries in a few seconds and rapidly explore the dataset.
3.2 Data by Task Taxonomy
This data by tasks taxonomy includes seven basic data
types and seven basic tasks (Shneiderman, 1998). The data being explored are
usually multi-dimensional but most designs highlight 1, 2 or 3D that are used
to define the general visual structure of the visualization. The taxonomy is
organized based on those selected dimensions. This simplification is useful to
describe the visualizations that have been developed and to characterize the
types of problems that users encounter when using those visualizations. Examples
were chosen to complement those provided by Keim et al., this volume (Chapter
2) in which a more comprehensive taxonomy for visualization of high dimensional
data is the primary focus.
3.2.1 Data
types
1- 2- or 3D data: Linear data types (1D) include lists, documents, program source code,
and the like that are organized sequentially. Interface-design issues include
what overview, scrolling, or selection methods can be used. User tasks might be
to find the number of items or to see items that exhibit certain attributes
(Eick et al., 1992). Planar data (2D) can be represented by geographic maps,
floor plans, and newspaper layouts. User tasks are to find adjacent items,
containing items and paths between items, and to perform the seven basic tasks
(see below). Real-world 3D objects such as the human body or buildings have
volumetric elements and connections with other elements. Users’ tasks deal with
adjacency plus above–below and inside–outside relationships. In 3D applications,
users must understand and control their position and orientation when viewing
the objects, and must be able to compensate for the serious problems of occlusion.
While many examples of successful 3D computer graphics and scientific visualizations
exist (Nielson et al., 1997) there are still very few Information Visualization
examples in three (abstract) dimensions. Designers have used 3D representations
to present attractive overviews of data that was not intrinsically 3D, such as
sets of documents, as shown in Figure 3.2 (Wise et al., 1995). But controlled experiments
trying to measure the benefits of 3D in such conditions have had mixed results
(Cockburn and McKenzie, 2002). These mixed results complement similar findings
from earlier cartographic experiments and related efforts to assess use of the third
dimension to depict non-spatial attributes on maps (Kraak, 1989; Dorling, 1992)
Temporal data: Time series are very common and merit a data type
that is separate from 1D data. The distinctions are that items have a start and
finish time, and may overlap. Timelines have been widely used, from the line
plots used by Minard see Tufte, 1983) to summaries of heterogeneous data such
as LifeLines, as shown in Figure 3.3 (Plaisant et al., 1996). Frequent tasks
include finding all events before, after,
or during some time period or moment, and in some
cases comparing periodical phenomena (Carlis and Konstan, 1998). Space–time
data have also been a focus of attention in geovisualization for more than a
decade (Szego, 1987; DiBiase et al., 1992; Kraak and MacEachren, 1994; Kwan,
2000) and some recent advances are discussed by Andrienko et al., this volume
(Chapter 10).
Figure 3.2.
ThemesViewTM (formally ThemeScape) shows a 3D map representing the results of a
search in a large
corpus of documents. Proximity indicates similarity of the topics, whilst
height
reflects the number of
documents and frequency of terms. Commercial applications also exist
(OmniViz Inc, 2003)
Reproduced with permission of Pacific Northwest National Laboratory.
Figure 3.3. LifeLines
present a summary of personal records (here a medical record), showing
several facets of the
records and using line thickness and color to map data attributes on the
display.
Multi-dimensional
data: Most relational- and
statistical-database contents are conveniently manipulated as multi-dimensional
data, in which items with n attributes become points in an n-dimensional space.
The interface representation can be dynamic 2D scattergrams (possibly a map, as
is the case in Figure 3.1) with each additional dimension controlled by a
slider or button using dynamic queries (Ahlberg et al., 1992).
A 3D scattergram is possible, but disorientation and
occlusion are severe problems. Parallel coordinates plots (Inselberg, 1985) are
one of the few truly multi-dimensional techniques and have been shown to be a
powerful analysis tool. Familiarity, training and practice in using the
technique will help a user become a “multi-dimensional detective” (Inselberg,
1997). Less powerful but more accessible to novice users is the Table Lens (Rao
and Card, 1994; Inxight Software Inc., 2002), which uses a spreadsheet
metaphor.
Other examples include VisDB for multi-dimensional
database visualization (Keim and Kriegel, 1994), interactive mosaic displays
(Friendly, 1994; Theus, 2002a,b), the Attribute Explorer (Tweedie et al., 1996)
and the scatter plot or prosection matrices of Becker and Cleveland (1987).
Interactive geovisualization software also utilizes multidimensional visualization
techniques (Andrienko and Andrienko, 1999a–f; Gahegan et al., 2002a,b;
MacEachren et al., 2003a,b) as emphasized in section B of this volume
(see Andrienko et al., this volume (Chapter 5) and
subsequent chapters).
Hierarchical
data: Hierarchies or tree structures
are collections of items, in which each item (except the root) has a link to
one parent item. Examples includetaxonomies, file structures, organization
charts and disease classifications. Items and the links between parent and
child can have multiple attributes. Tasks can be topological (for example, a
query asking which branch of the company has more employees?) or attribute based
(such as an attempt to find the largest old files on a hard disk). Interface representations
of trees can use the outline style of indented labels used in tables of contents,
node-and-link diagrams. Examples include the Hyperbolic tree (Lamping et al., 1995)
commercialized by Inxight Software Inc (2002) or SpaceTree (Plaisant et al.,
2002; Grosjean et al., 2002). A third possibility is to use a space filling
representation such as Treemap (Johnson and Shneiderman, 1991; Bederson et al.,
2002) as shown in
Figure 3.4. A
number of commercial applications of the Treemap technique are available including
Shneiderman (1998), the Map of the Market (SmartMoney.com, 2003) or e-business
(The Hive Group Inc., 2003).
Network data: When relationships among items cannot be captured conveniently
with a regular tree structure, items are linked to an arbitrary number of other
items in a network. In addition to performing the basic tasks applied to items
and links, network users often want to know about shortest or least costly
paths connecting two items or traversing the entire network. Common
representations include node-andlink diagrams (but layout algorithms are often
so complex that user interaction remains limited for large networks), and
square matrices of items with the value of a link attribute in the row and
column representing a link. Network visualization is an old but still imperfect
art because of the complexity of relationships and user tasks, for example, (see Rodgers, this volume (Chapter 7)). It is
used in a number of useful geographic applications and is being incorporated
into software for geovisualization, for examples,
(see Mountain, this volume (Chapter 9)) and Fairbairn,
this volume (Chapter 26).
Figure 3.4. An example
of Treemap is the Map of the Market (SmartMoney.com, 2003). Rectangles
each represent a
stock and are organized by industry groups. The rectangle size is proportional
to the market capitalization and the
color indicates the percentage gain or loss for the given time period. Reproduced
with permission of SmartMoney.com.
Figure 3.5. Dynamic
labeling of items is still a challenge. Here Excentric Labels in incMap show
the
labels of all the items
inside the focus circle, revealing hidden items and allowing their selection.
Reproduced with
permission of N Space Labs, Inc. (http://www.incmap.com).
3.2.2
High-level task types
Having considered the range of data types available
along with some methods that have been developed for graphically representing
them, we can consider a number of highlevel tasks that apply to all data types
Overview
task: Gaining an overview of the data
might include gauging the number of items and the range and distribution of the
attribute values, or estimating how much things have changed since last time
the user reviewed the data. Overview strategies include zoomed-out views
adjoining the detail views, for example, (see Ware and Plumlee, this volume
(Chapter 29)). A movable field-of-view box can be used to control the contents
of the detail view. Intermediate views allow larger zoom factors. Another
popular approach is the fisheye strategy originally described by Furnas (1986).
It provides overview and details in a single combined view by using distortion
based on
a degree of interest function. It is effective when
zoom factors are small and deformation is acceptable to users (for example,
when orientation and distance measurement are not important).
Zoom task: Users need to control the zoom focus and the zoom
factor. Smooth zooming helps users to preserve their sense of position and
context. Manual zooming is powerful but users tend to get lost so
application-controlled zooming to preset levels is more likely to be usable,
for example, see Ware and Plumlee, this volume (Chapter 29). Pad++, now called
Piccolo is a popular zooming user interface
toolkit that uses semantic zooming (Bederson, 1994;
Bederson et al., 2000). Semantic zooming (Perlin and Fox, 1993) is commonly
used with maps, where the same area can be displayed with different features
and amount of details at different zoom ratios. There are key parallels with
real time cartographic generalization here (Weibel and Jones, 1998). Constant
density zooming (Woodruff et al., 1998) is an example of
technique to maximize the number and readability of
items on the display. Wood, this volume (Chapter 15) uses mipmapping to display
surface characteristics according to the scale at which any part of a surface
is viewed in a real-time 3D application and Doellner, this volume (Chapter 16)
identifies some associated issues in computer graphics.
Filter task: Dynamic queries allow users to quickly focus on
their interests by eliminating unwanted items. Other techniques include
sorting, grouping or highlighting followed by hiding, or locating items similar
to an item of interest. Theus, this volume (Chapter 6) provides some examples
of “selection” from the perspective of statistical graphics.
Details-on-demand
task: Once a collection has been
trimmed, users need to review the details of single items or groups. The usual
approach is to simply click on an item and review details in a separate or
popup window. Dynamic labeling remains an important challenge. Excentric
labeling (Fekete and Plaisant, 1999) is an approach illustrated in Figure 3.5
through the Geographic Map of the Market in which geovisualization techniques
and those of Information Visualization are integrated (N Space Labs Inc.,
2003).
Relate task: Users need to view relationships between items, as
is the case with the LifeLines shown in Figure 3.3, where users can click on a
medication and see the related visit report, prescriptions, and laboratory test
results. Linking and brushing techniques (
History task: It is rare that a single user action produces the
desired outcome. Keeping the history of actions allows users to retrace their
steps, save useful exploration “recipes” and apply them to updated datasets
later on. Roberts, this volume (Chapter 8) considers these issues at an
operational level and Gahegan, this volume (Chapter 4) addresses the
conceptual, scientific and motivational challenges that underlie support for saving
and sharing entire analysis strategies.
Extract and
Report task: Users often need to save
subsets of the data or particular views of the data into reports. They may also
want to publish “cleansed” data with a simplified subset of the tool’s features
for others to review.
3.3 The Coming of Age of Information Visualization
–
Toward Universal Usability
Although maps have been used for hundreds of years, it
is important to realize that most Information Visualization techniques are very
recent and, if we exclude elementary tools such as pie or bar charts, these
tools have mostly been used by researchers, data analysts and experts. Only
recently have we seen novel designs become widely used by the public. Researchers
recognize that there is no “one size fits all” visualization and that
specialized techniques are needed to tackle special data (for example, genomic
data or spatio-temporal data) as well as special user needs (such as
collaborative analysis or real time monitoring). Two general challenges need to
be faced by Information Visualization before we can anticipate more widespread
uptake of many of the techniques that have been developed: the ability to
handle larger volumes of data and the ability to effectively support more
diverse users. The first challenge relates to the limited number of items most tools
available can manage. Many innovative prototypes can only deal with a hundred
or a thousand items, or have difficulties maintaining real time interactivity when
dealing with larger numbers. Yet examples dealing with millions of items
without aggregation have been achieved as shown in Figure 3.6 (Fekete and
Plaisant, 2002). Keim et al. (2001) demonstrate that Information Visualization
is not yet close to reaching the limits of human visual abilities but that new
techniques are needed to tackle the large quantities of information. Keim et
al., this volume (Chapter 2) provide an overview and some additional solutions.
Dealing with real data also involves data cleansing or dealing with missing and
uncertain values.
Figure
3.6. A Treemap displaying a million files from a large file system, without
aggregation (Fekete and Plaisant, 2002). Careful examination of the high
resolution display reveals patterns and special algorithms preserve the
interactivity of the rich overviews and filtering tools.
The second challenge is focused on more specifically
here: how do we make Information Visualization accessible to a wider group of
diverse users? In fact a growing number of applications are being developed for
what might be the most challenging user group – the general public. Let us take
the example of the enormous amounts of georeferenced data accumulated by
government agencies and to be made available to every citizen. These data are
useful to senior citizens looking for a place to settle after retirement,
business analysts, managers considering relocation, etc. They can also be useful
to drivers on the road and researchers working on complex tasks on their
high-end computer workstations.
To address the problem of universal usability
(Shneiderman, 2000; Shneiderman and Hochheiser, 2001), designers need to
consider larger and more diverse groups of users. Technological advances are
needed not only to deal with user diversity (age, language, disabilities, etc.)
but also with the variety of technology used (screen size, network speed,
platform, etc.) and any specific gaps in a user’s knowledge (e.g., general knowledge,
knowledge of the application domain, of the interface syntax or semantic). Information
Visualization has been shown to be a powerful visual thinking or decision tool
for some average users receiving a minimum of training (Williamson and Shneiderman,
1992; Lindwarm et al., 1998; Chen and Czerwinski, 2000). But it is becoming
important for services to reach and empower every citizen regardless of their background,
technical disadvantages or personal disabilities. Universal usability is an
ambitious long-term goal but many practical steps can be taken toward achieving
it. Focusing on this problem will most likely lead to better technologies for
everyone (simpler interfaces, faster downloads, etc). Several examples are
reviewed below that illustrate how projects have addressed different aspects of
the universal usability challenge.
3.3.1
Improving general usability
Of course the first step is to improve the general
usability of the interface. Many texts are available to guide designers toward
the creation of empowering user interfaces (Shneiderman, 1997; Preece et al.,
2002). Usability testing can then verify that user needs and usability goals
have been met and that users are able to use the system on their own with a
sense of control and satisfaction (Dumas and Redish, 1999; Kuniavsky, 2003). Specific
guidelines for map design are also available (Pickle, 2003) and Tobo´n, this volume
(Chapter 34) draws upon the usability approach to assess geovisualization map use,
for example, (see also Fuhrmann et al., this volume (Chapter 28)). The success
of the Map of the Market (Figure 3.4) illustrates that general techniques
initially described as “difficult to understand” (i.e., Treemap) can become accessible
interfaces. The popularity of this application with the general public might be
attributed in part to the fact that the data is familiar, and important, to
users who visit a financial website. The careful simplification and refinement
of the initial Treemap
interface also plays a part. The names and groupings
of stocks are familiar to users of the SmartMoney Website. The hierarchy is
simple, being shallow and of fixed depth, and the color mapping is natural to
most users (using green for gains or increased values of the stocks, red for
losses, with alternative colors for those with color impairment). An elegant new
algorithm has recently resulted in a better aspect ratio for all the rectangles
making the display more readable and pleasing. Labeling and links to details
were optimized for the particular application. Finally it was carefully written
in lightweight Java so that it could actually run on most users’ machines
without having to download special plugins or worry about Java versioning. This
combination of factors has been effective in making the map usable by the
general public, as indicated by the large number of return users the Website
enjoys.
3.3.2
Helping users get started
Designers need to consider whether their application
is to be used by first-time users or by experts who will have invested time and
effort into learning the application. A major aspect of accessibility is
concerned with enabling users to get started with an application (Andrienko et
al., 2002). Even the average professional analyst or researcher may need help,
but a major challenge is to help ordinary citizens use Information
Visualization applications successfully. Commercial Web sites can decide which
population they target but Digital government applications might well be faced
by the greatest challenge since
they are supposed to be usable by everyone! This
implies that most information consumers will be first time users and also that
they will have very varied backgrounds and levels of education. They may also
have limited time or interest in learning to use the system, but paradoxically
may have very high expectations of the services they seek to use. Users want an
answer to their question, not necessarily to learn all that a tool can do for
them. Let us consider a particular example, that of DataMap (Plaisant, 1993),
which was previously named Dynamap or Ymap. Dang et al. (2001) review three
approaches that were explored to help users get started with the DataMap
interface. DataMap (Figure 3.7) is an interactive visualization tool developed
by our Human–Computer Interaction Laboratory at the
The first step was to revise the interface. This was
done by a team of colleagues at Virginia Tech led by Chris North and is
illustrated in Figure 3.7b.
Figure 3.7. (a) DataMap
allows users to zoom on a state or county map, select areas or filter them
out with dynamic
queries. A tightly coupled scatter plot provides an alternative to compare
areas. (b)
The revised interface
(reproduced with permission of Chris North, Virginia Tech).
Most problems found in the usability study led to
refinements of the interface. This resulted in a number of changes including:
reducing the number of attribute sliders with the possibility of adding more
with a control panel; making slider thumbs easier to recognize and use;
limiting zooming to avoid zooming into empty areas; simplifying window
resizing; using an
appropriate projection for the map; using fonts
consistently and selecting more readable typefaces; using color coding to show
the relationship between the sliders position and the parts of the map
highlighted or hidden. Some aspects of the interfaces still needed
explanations. Since DataMap is meant for public access, it was clear that users
would be unlikely to read manuals or go through long tutorials, so we explored
alternative approaches to providing help (Plaisant et al., 2003.) We considered
three approaches. The first approach is to create a multi-layered design that
provides a simpler interface to get started, while complex features are
accessed progressively as users move through the layers of the interface. The
second approach is called Integrated Initial Guidance (IIG) or “sticky note
help”. It provides help within the working interface, right at the start of the
application. Using the metaphor of sticky notes overlaid on top of the
functional interface it locates the main widgets, demonstrates their manipulation,
and explains the resulting actions by replaying recorded sets of actions. The third
approach uses video demonstrations of the interface. The videos use sound and entirely
overlap the interface to give the illusion of being integrated in the interface[1].
Approach 1:
multi-layered designs Some
applications might be suited for a multi-layer design that allows users to
start with a simple interface with
limited views on information and choices to make and then to move to more complex (and more functional)
levels once the basic functions are understood.
This is the case for DataMap, which can easily be
organized in a three-layer design (Figure 3.8):
- layer 1: map and table
only;
- layer 2: map and table,
plus dynamic query filters;
- layer 3: map and table
and dynamic query, plus scatter plot.
The interface initial view hides level 2 and level 3
functionality. When users go up one level, the appropriate parts of the
interface are added with an animated transition, which help users see what is
changing. Multi-layered interfaces, termed “level-structured interfaces” when
introduced to Information Visualization (Shneiderman, 1998), are commonly
encountered in hardware devices like VCRs that hide advanced function buttons
and controls behind a small door, or in search interfaces that often provide a simple
and advanced search. This approach has been underused in software applications and
could be generalized easily. The benefits are that users can get started more
easily. The risk is that some users will never discover the advanced features
they do not know are there.
Figure 3.8.
Three different levels of the level structured approach. (a) the first level
shows only the
map and the data table;
(b) second level shows slider bar along with map and table; (c) the third level
adds scatter plot. An
introduction panel lists the features of the level and indicates the location
of the
three level buttons.
Approach 2:
integrated initial guidance or “sticky note help”
IIG implements a metaphor of sticky notes inside the
interface itself, thereby allowing users to use the interface or run automated
demonstrations while reading the sticky notes overlaid on the functional
interface (Figure 3.9). Sticky notes highlight the main functions of the interface, show the location
of the main interface widgets whose use can be demonstrated and explained with
a “show me” button, and provide lists of simple to complex example tasks which
lead to demonstrations of advanced interface widget functions. This allows
users to make use of the help in many different ways. Some users
will try out all the example tasks, while others may
never use any. Some users will use the show me feature while others will
execute the steps themselves, guided by the directions on the sticky notes and
using the show me function only when they failed to guess what to do.
Figure
3.9. Using sticky notes. (a) Three IIG sticky notes lead to explanations of how
to use the map, zoom, select multiple
states and move to the next level. Example tasks are listed in the note at the top right. (b) The first example task was
chosen. “Compare the populations of three west coast states”. The next steps are shown in
transparency until the user executes the current one, or asks to see an automated “show me” demonstration.
Approach 3:
autonomous video or animated demonstrations
Video demonstrations are used increasingly to
introduce the main features of complex visual interfaces. They can be launched
from the application but are really run outside the interface itself.
Macromedia Flash can be used to create demonstrations but simple recording
tools (such as Camtasia Studio from TechSmith) are useful to create video explanations
in a matter of hours. Effectiveness is increased by the use of speech, which leads
to more compact explanations and lively demonstrations (but subtitles will be needed
to accommodate users with hearing difficulties). Highlighting the mouse cursor and
making mouse clicks or key presses visible is important. Low-resolution videos
can be effective and fast to download but we found that videos that entirely
cover the interface give users the impression that they are watching the real
interface, therefore reducing the transfer of learning to the interface.
Of these three different approaches, the sticky note
technique was found very effective during informal user testing but it was
fairly difficult to design and build. On the other hand, the video
demonstrations were easier to create and fairly effective when kept short and
mapped in direct ways to users tasks. The multi-layered approach was appreciated
by the majority of our test users and might be the most powerful approach to helping
users get started with complex public access applications, as long as care is
given to guide users to the advanced levels.
3.3.3
Addressing the hardware diversity
Because programmers and development teams usually work
with high-end equipmentand fast network connections it is important to address
the range of devices and network speed available in people’s homes and
businesses when producing visualization software for public access. Issues may
vary from application to application so we only give an example illustrating
how addressing hardware problems does not necessarily result in a “lowest
common denominator” applicationbut can benefit everyone.
Let us consider the example of DataMap once again. The
Java version of DataMap loaded and ran quickly enough on standard PCs and
broadband connections but – as with other interactive map tools – would take
minutes to download with a 56K modem and could not maintain the interactivity
needed for dynamic queries (i.e., 10 ms feedback) on low-end PCs.
Traditionally, interactive maps use vector graphics to draw
the maps which means downloading the vector data and
the software to interpret it. Instead, we created a new version of DataMap that
encoded geographic knowledge into raster images quickly delivered to the client
(Zhao et al., 2003). Algorithms were devised to perform sub-second dynamic
query, panning and zooming, with no or minimum server support. This technique
leads to download times that were often counted in seconds instead of minutes
for modem users, being between 5 and 10 times shorter that those
experienced with Web GIS approaches that are based on
vector geographic data, while keeping the needed interactivity. The client-side
was also implemented as light-weight Java applets to avoid version problems.
This example illustrates that it is possible to find technological advances
that benefit general public users with slow modem network connections and
low-end machines, as well as users with fast T-1 connections and fast machines,
therefore advancing the goals of Universal Usability.
3.3.4
Addressing the needs of users with visual impairments
Color
blindness
Color impairment is a very common condition that
should not be overlooked (Rosenthal and Phillips, 1997; Olson and Brewer, 1997)
This problem can more easily be addressed by limiting the use of color, using
double encoding when appropriate (for example, by using symbols that vary in
both shape and color), providing alternative color palettes to choose from, or
allowing users to customize the colors themselves. For example the Map-of-the-Market
illustrated in Figure 3.4 provides two choices of color schemes: red–green and
blue–yellow. Various tools are available to both simulate color vision
impairments and to optimize graphics for some of the various forms of color
impairment that exist, including Vischeck (Dougherty and Wade, 2002).
ColorBrewer (Brewer and Harrower, 2002) offers guidelines on color schemes that
work for those with color vision impairment.
Low Vision
and blindness
Approximately four million people in the
2000; Muntz et al., 2003). Traditional accommodations
to blind and vision-impaired users include the use of speech synthesizers as
screen reader, and/or Braille to convey the text information on the display.
However, speech-based approaches are very weak at representing 2D spatial
layout in the graphical user interface. This is a challenge for maps as well as
most other Information Visualization techniques.
For navigation in the real world, GPS-based talking
maps have been developed (Golledge et al., 1991a,b). One example product is a
talking nationwide digital map consisting of most addresses and street
intersections (The Sendero Group, 2003). Users can navigate the map using the
arrow keys and listen to speech-synthesized descriptions of the map and
directions. Trekker (VisuAide, 2003) is another GPS-based application that
helps the blind to navigate. Maps are also important to learn an area
beforehand and chose a route. Schneider and Strothotte (2000) have designed a
tangible interface using physical building blocks that users manipulate to promote
constructive exploration of the map.
When using maps to learn Geography or discover spatial
patterns in data, people with limited vision can use screen magnifiers (for
instance, try the “magnifier” available from the Start menu of MS Windows, in
the accessibility accessories), but those with severe vision impairments have
to rely on tactile maps or atlases (Imperatore, 1992) as shown in Figure 3.10
or sonification of the maps.
Figure 3.10. A
traditional tactile atlas showing a map of
Natural Resources
Current assistive technology research is exploring a
number of promising techniques to help blind users benefit from the spatial
awareness provided by maps. The first step is to provide data in both visual
and descriptive form. OptiMaps (Corda Technologies Inc., 2003), employs a small
“d” character below each choropleth map. This is the standard accessibility
mark for image “descriptions” that visually impaired users are able to search
for. These provide hyperlinks to a textual version of the data, generated
automatically with the dynamic map. Examples are available in AtlasPlus (National
Cancer Institute, 2003). New vector graphic file formats, such as SVG, permit embedding
text descriptions with the graphic information and should simplify this process
as a result. Unfortunately reading the data values still does not give an
adequate feeling for the spatial relationships between areas that only spatial
techniques can
provide. Tactile and haptic techniques (and strategies
for signifying data haptically) have
been devised (
Another example developed by TouchGraphics and their
research colleagues (Landau and Gourgey, 2001) augments standard printed
tactile maps. Maps are secured on top of a touch screen that provides the
location of each touch (Figure 3.12). The TouchGraphics Atlas has five
operational modes. Users can simply explore by touching a physical tactile map
and hear names of places touched. They select a destination from an index, and
listen to directions that are updated as a user’s finger gets closer to the
destination. Distance between two points can be
calculated, and descriptions of the areas can be listened to. This work was
inspired by Nomad (Parkes, 1994). 3D maps can benefit from the use of haptic
devices. For example, the Phantom device provides 6 degrees of freedom input
and 3 degrees of freedom output to explore the virtual sound space and augment
it with haptic feedback providing the same sensation
as moving a single finger over a physical 3D map. Tactile
maps can be augmented with abstract audio output (Fisher, 1994; Krygier, 1994).
For example, users can hear a series of graduated pitches proportional to elevations
above sea level as they explore the map. Sonification alone has been demonstrated
to be effective in giving blind users access to graphs (Ramloll et al., 2001) or,
in some limited fashion, entire desktops (Mynatt and Edwards, 1992). In the
case of maps, Jeong and Gluck (2002) compared the effectiveness of and
preferences for using auditory feedback (volume of sound), haptic feedback
(extent of vibration) or both in the tasks of identifying the highest or the
middle valued state on a static choropleth map of the
Figure 3.11. The
VTPlayer is a mouse equipped with two Braille character units that can also be
used to indicate
patterns. For example, as users explore a map of the
different states
(VirTouch Ltd, 2002). Reproduced with permission of VirTouch Ltd.
Figure
3.12. An example of tactile map augmented with audio description when mounted
on a touch screen (Touch Graphics, undated). (a) Sample map plate; (b) the
sample map plate in use with the talking tactile tablet (TTT). Reproduced with
permission of Touch Graphics.
The BATS project at the
Figure 3.13. The BATS
sonic map helps those without sight to explore spatial information (Parente
and Bishop, 2003). Real
world audio icons (car noises, wave crashing, etc.) are played as the user
navigates the map and
appear clearly as coming from your right or your left. Volume increases as
users get closer to the
source of the sound. Reproduced with permission of the authors.
A promising direction for the sonification of spatial
information is the use of spatial audio using a head-related transfer function
(HRTF) (Shinn-Cunningham et al., 1997). Since humans are usually able to
localize sound with amazing precision by using binaural perception, spatial
location can be an important aspect of information perception. It is possible
that the addition of positional cues will greatly improve the
sonification of maps. Stereo effects allow right–left
sound separation only, while spatial audio provides up and down cues, and in a
less reliable manner front and back information.
CAVE-like virtual environments provide such spatial
sound with sets of multiple loud-speakers (Pape, 1998; see Bodum, this volume
(Chapter 19). But synthesized spatial audio allows users to experience 3D audio
with ordinary headsets. Until recently this had been limited to
high-performance computing environments but researchers are now able to
synthesize high-quality 3D sound in real-time on commercial off-the-shelf PCs
(Zotkin et al., 2002). We are currently exploring its use for the sonification of
maps. Nevertheless, the spatial effects – if noticeable – remain fairly weak
and our research at the
Figure 3.14. Spatial
audio allows users to hear the location of virtual sound sources. This schematic
represents what a user might hear as each US state “plays” its statistics, for
example a sound whose pitch is proportional to its African-American population.
Proper linearization of sounds allow users to hear patterns of low to high
values moving from the northern states to the lower
3.4 Conclusions
Information Visualization allows designers to present
a large amount of information using abstract representations. Geographic and
scientific visualization applications usually use representations determined by
the nature of the data being displayed. Location within the graphic is usually
used to represent location in space. For example in 2D maps, a projection of
space structures the representation, whilst in 3D models of the body or of
physical processes such as meteorological predictions graphics are constrained by
a 3D locational framework. On the other hand, Information Visualization allows designers
to choose among a palette of possible representations that fill space in a
variety of ways, such as hierarchies, time lines, networks, tabular displays
and the like, to produce information abundant displays. Choosing the
appropriate representation(s) is challenging and research is needed to evaluate
and compare different approaches. User
studies are critical to judge the relative merits of
different representations. Tightly coupled displays and highly interactive
interfaces using the Zoom, Filter and Detail on Demand principles are needed to
allow users to rapidly explore alternative views of the data in a matter of
seconds to answer instant queries. Advanced interfaces also need to address the
longer term process of analysis that may require annotation, history keeping,
collaboration with peers, and the dissemination of results and procedures used.
Faster rendering algorithms, sophisticated aggregations techniques to deal with
large datasets, and novel labeling techniques are also needed, and along with
careful studies of users and their needs will lead to successful visualization
applications. Many of these, and related issues are addressed in the following
chapters by researchers from a number of related fields.
Information Visualization is becoming increasingly
accessible to the general public and attention should be given to the goal of
universal usability by enabling the widest range of users to benefit from the
applications we develop. Universal usability remains a formidable challenge as
we just begin to address the needs of users with slow modems, small screens, or
wireless devices. Translation to other languages, access for novice, low
education and low motivation users, children and elders all present special difficulties,
and users with visual impairments often remain the “forgotten users” of Information
Visualization. Tactile solutions are promising for blind users but sonification
might provide wider access to map information, as it does not require
specialized hardware.
Acknowledgements
The content of this chapter was inspired in part by
Information Visualization and Universal Usability, and
also by papers co-authored with Haixia Zhao, Hyunmo Kang and other members of
the Human–Computer Interaction Laboratory. Some of the work presented was
funded by the National Science Foundation under Grant No. EIA 0129978 and the
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