ACM Computing Surveys
28A(4), December 1996,
http://www.acm.org/surveys/1996/CruzTailorable/. Copyright ©
1996 by the Association for Computing Machinery, Inc. See the permissions statement below.
Tailorable Information Visualization
Isabel F. Cruz
Database Visualization Research Group
Tufts University
161 College Av., MA 02155, USA
ifc@cs.brown.edu,
http://www.cs.brown.edu/people/ifc
Abstract:
Information visualization is emerging as one of the most important
topics in human-computer interaction. Existing systems have been
successful at providing automatic ways to display information using
sophisticated rendering techniques (e.g., 3D, animation).
We argue for tools with which users can adapt visualizations to the
application at hand and to their own preferences. Ideally, such tools
should combine user-defined displays with automatically-generated
displays and be integrated with search mechanisms capable of accessing
data in a variety of information bases (e.g., digital libraries, the
WWW, databases). A combined effort of researchers in human-computer
interaction and in information systems is therefore needed.
Introduction
Information visualization focuses on graphical mechanisms designed to
show the structure of information and improve the cost of access to
large information bases. Recently, we have been witnessing an
increased interest in large information bases, first because of the
immense volume of data that can be electronically accessed (e.g., on the
World-Wide Web), and second because of the number and diversity of the
people that are accessing this information on a daily basis. To
access the relevant documents in a large information base, the following
tasks are needed:
- Locating the data
This can be achieved with data mining and knowledge discovery
tools [Etzi96].
- Processing the data
This involves selecting and transforming (e.g., aggregating)
hypermedia/multimedia data using query languages or other
information retrieval mechanisms [CMW95].
- Presenting the retrieved information
The information may consist of text, numerical data,
video clips, and images, which need to be spatially
and temporally put together [WeWi94, CMW95].
We believe that to perform each of these tasks, an integration of
information retrieval/database techniques and visualization techniques
is needed: on one hand, the information to visualize has to be first
extracted from the large information bases; on the other hand, textual
manipulation of the data may be too daunting a task given the amount
of data and the inexperience of many of the users. Therefore, while
historically the HCI and database communities were kept separate, the
interests of both research communities are converging, specifically in
regards to information visualization issues (see for example, the
SIGMOD Record Special Issue on Information Visualization [CaCr96]).
This paper focuses on information visualization from the HCI point of
view, while pointing to relevant issues in information retrieval and
databases. We argue for making tools
available that give the end user the
power to tailor the information displays.
Because of the diversity of users, providing
different levels of customization is another desirable goal: the idea
being that some users will be able to define new visualizations from
scratch, while other users will be happy to change just a few
parameters to the visualization.
Next we discuss several aspects that may lead to better tools for
information visualization in general, and to tailorable information
visualization in particular.
Information Visualization Approaches: the HCI and Database Viewpoints
In printed form, information visualization
has included the display of numerical data (e.g., bar charts, plot
charts, pie charts), combinatorial relations (e.g., drawings of
graphs), and geographic data (e.g., encoded maps) [Bert83, Tuft83, DETT94]. Information visualization systems have
coupled powerful visualization techniques (e.g., constraints [Born81], 3D
[RCM93,CEH96]),
querying capabilities (e.g., dynamic
queries [Shne94]), sophisticated algorithms
(e.g., to draw graphs [GaTa96]) and near
real-time interactivity to produce these displays.
In the database community, the focus on information visualization
started with research in visual query languages, where the
visualization of schema and/or database instances is common (for a
survey, see [CCLB97]).
Recently, a new generation of database systems is emerging, which
tightly combine querying capabilities with visualization techniques
and are information visualization systems in their own right [CCS94, Cruz92, HIL95]. These systems also allow for
tailoring the displays to the users' preferences.
There is a host of research opportunities in HCI associated with
database applications that access large data repositories (e.g.,
data mining and data warehousing), and with information retrieval
(e.g., in digital libraries and the WWW) [FoPi94, FAFL95]. The
research issues include providing both "effective" visualizations of
large amounts of documents and carefully designed user interfaces
capable of addressing the needs of a wide variety of users.
Automatic Visualization
In automatic approaches to
information visualization, the designer or programmer
pre-specifies the information display.
The visualization of graphs in 2D or
3D is one of the most challenging layout problems for two main
reasons: most layout optimization problems are intractable and aesthetic criteria
often conflict. Therefore, finding automatic mechanisms to display
graphs that are also efficient entails the design of algorithms that
take into account the graph characteristics (e.g., trees or general
graphs), the preferred drawing style (e.g., layered trees) and
aesthetic criteria (e.g., minimization of area or volume, maximization
of the display of symmetries) [CrTa94, DETT94].
Other approaches whose main focus is not on the layout of graphs include
systems like APT [Mack86] and
Sage [RKMG94]. These systems have
focused on the automatic generation of visualizations given the
semantics of the data (e.g., functional dependencies in a relational
database in APT).
An comprehensive approach is proposed by [Rao et
al.95], where 3D displays (e.g., the "Document Lens", the
"Butterfly Application", and the "Hyperbolic Tree Browser") and search
mechanisms are integrated in a single environment for accessing
digital libraries.
Declarative Approaches
Declarative approaches to information visualization allow the user
to specify what the displays look like but not how
they are to be produced from the specification. They often combine
constraints with other formalisms, such as grammars [Goli91, WeWi94], visual
languages [Cruz94,Cruz95], and set notation [Mark91]. Declarative approaches to graph drawing
include [Mark91, CrGa94] (for
a survey see [CrTa94]).
An issue of practical importance concerns the efficiency of
rendering a picture. Techniques that rely on optimization techniques
(e.g., simulated annealing or general constraint solvers as in
[Mark91, CrTw96]) are usually
inefficient. For large data sets, such inefficiency can become an
issue especially when the displays are to be generated as the users
browse the data. Therefore, the identification of layouts for which
a constraint solver exists that matches the best known algorithm
would be an important accomplishment. Preliminary results show that
a significant class of graphs can be rendered in linear time [CrGa94].
Incorporating an automatic approach to
data visualization with a user-defined approach is an interesting and
practical problem, for example when the user-defined visualization is
underconstrained. Ideally, an automatic layout facility
could supplement the user-defined visualization.
The users' preferences could also provide invaluable information on
ways to automatically perform the display of the data: how can such
knowledge be gathered to automate the display of information for
users who have previously defined displays of "similar" data? How
can preferences of groups of users be integrated and taken
into account for future displays?
Expressiveness and Readability of Visualizations
Unresolved issues in information visualization include a complete
understanding and characterization of the expressiveness of a
visualization and of its adequacy to represent a data set in the
continuation of the
study started by Bertin [Bert83],
and continued by Mackinlay [Mack86].
The comparison of the expressiveness of the different formal approaches
to information visualization (including grammars, constraints, and visual
languages) is largely an open issue.
A related issue concerns the readability of the displays, and the need
to understand how users interpret information displays.
In graph drawing, the readability is associated with (often conflicting)
aesthetic criteria such as the minimization of edge crossings and of the
area of the graph, and the maximization of symmetries.
A better display and improved readability can
also be achieved by using 3D graph visualization techniques
[RMC91, GaTa96,
CrTw96, CEH96].
Readability studies have been performed for 2D graph drawing
[PCJ96], but more such studies are needed,
including studies for 3D visualizations.
Automatic visualization approaches can benefit in obvious ways
from a better understanding of readability and expressiveness issues.
Incorporating such knowledge in tailorable visualization tools is, however,
a more difficult task: how can "inappropriate" visualization choices
be detected and how can useful feedback be provided to the user?
New Applications: the Challenges
In new applications, such as digital libraries or the WWW, the
presentation of the retrieved information is a challenge. Unlike in
traditional databases, there is no obvious form to display the
information (typically presented in the form of a table in
relational databases). Instead, the user may have to
build "virtual
documents", the assembly and maintenance of which provide motivation
for user-defined visualizations and also suggest the need to
incorporate a query language within the visualization tool to select
the data to be included in the virtual document. In addition, since
the data items that form the document may change over time (e.g.,
from a photo to a video clip), the virtual documents should allow for
dynamic changes. Similarly, such virtual documents may have to be
visualized in different platforms, bandwidths and screen
sizes. Their layout should therefore be adaptable to the different
environments.
The platform issue is particularly relevant for Internet and
Intranet applications. In this regard, consideration should be
given to platform-independent programming languages such as Java,
that can in addition support algorithm animation, e.g., for
education [BCLT86].
In distributed environments, the specification of the visualization
should take into account accessibility conditions to the different
information bases, e.g., to take into account different times to
receive the information from the different locations. Ways to
"dynamically" specify the layout should therefore be supported. A
somewhat similar situation occurs when loading a Web page, where
pictures may fail to appear or first appear incomplete. Other
time-related issues occur when the information itself varies over
time (as with audio or video) [Zell95].
New standards for Web documents should include an object-oriented
approach to the representation of hyperlinks and Web documents. In
this way, it is possible to specify the selective browsing, querying,
and visualization of electronic documents that belong to a class (and
its subclasses) and/or are connected by hyperlinks of a class (and its
subclasses). The current indiscriminate browsing (e.g., of Web
documents) can be supported by allowing for documents of all classes
to be accessed or hyperlinks of all classes to be traversed. Metadata
information can be equally helpful to direct the querying and browsing
of Web documents and to facilitate their visualization.
Acknowledgements
I would like to thank the participants of the HCI working group and
Wendy Lucas for fruitful discussions. This work was partially
supported by the National Science Foundation under CAREER Award
IRI-9625105 and by the Department of Computer Science at Brown
University.
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Last modified: Nov 15 1996
Isabel Cruz
<ifc@cs.brown.edu>