Multi-dimensional information visualizations present
data that is not primarily spatial. The number of
attributes of a given item in the collection is
more than three. Example applications of multi-dimensional
visualization schemes may use stock market statistics,
factory production line data sets, a set
of books in a library, a movie database, and almost any
abstract and statistical information about any phenomenon.
Attributes in multi-dimensional visualizations should
have approximately equal weights. One, two, three dimensional, and
temporal information visualization schemes can be viewed as a subset
of multi-dimensional information visualization. There is an implicit
domination of some of the attributes in these types of
visualizations. For example, time is the inherent attribute in a
temporal visualization scheme. Hence, we believe that one, two, three
dimensional, and temporal visualization schemes should be classified
separately from multi-dimensional visualization. Also, attributes in
multi-dimensional visualizations should have no explicit structure or
relations between them. For example, data sets that lead to an
immediate hierarchy or a network structure should also have their own
categories.
Scientific visualization also deals with multi-dimensional data but
most of the data sets used in this field use the spatial attributes of
the data for visualization purposes. For example, Computer-Aided
Tomography Systems, Computer-Aided Design Systems, and many of the
Geographical Information Systems use either the Cartesian coordinate
system or the geographical coordinates of the data to achieve a
reasonable visualization of the data. Hence, we believe that scientific
visualization should be analyzed in a separate category. On the other hand,
we believe that some of the combinations of multi-dimensional visualization approaches
and scientific visualization schemes can still be considered as
multi-dimensional visualization applications.
Tasks
Understand or get an overview of the whole or a
part of the n-dimensional data. For example, finding patterns,
relationships, clusters, gaps, and outliers of the data.
Find a specific item in the data.
For example, zooming, filtering and selecting a group or a single
item from the data.
Projects
DataSPLASH - University of Berkeley: A project to interactively
visualize the tables of a relational database. Includes dynamic
generation and manipulation of objects within the database.
DEVise
- University of Wisconsin: This project uses the idea of having
various visualizations at the same time. The
visualizations can be applied one after another to obtain different
views of the same data. The approach is very similar to forming a
query on a database using a set of concatenated functions. The result
is a picture of the database which can not be dynamically manipulated
by the user.
DQI - University of Maryland: Main research on Dynamic Querying
continues at the University of Maryland in the Human-Computer
Interaction Lab. The main idea is to help user create scatter plot
views of the data set and manipulate them using direct manipulation
techniques. This research was implemented recently as a commercial
application which is known as Spotfire by IVEE Development Co.
Influence Explorer - Imperial College: This project also uses the
benefits of direct manipulation and Dynamic Querying ideas. This
approach displays histogram information of the attributes
simultaneously.
Magic
Lens - XEROX PARC: The main method used in this project is to
apply various functions to a specified region of the data set that is
being visualized. For example, the simplest function that can be used
for this purpose is the zooming operation on a certain area of
interest of the data set.
Parallel Visual
Explorer - IBM: This project uses the parallel coordinate system
to show different projections of the data. It is highly dynamic. The
approach is capable of showing huge numbers of attributes at the same
time.
SDM -
Carnegie Mellon University: In this project different visualizations
of the same data are linked together. The user can see changes on all
visualizations simultaneously by just manipulating one.
Table Lens -
XEROX PARC: The Table Lens shows spread-sheet data in both symbolic
and graphical representations within a single understandable
view. Users can chose and manipulate regions of the table.
Visage - Carnegie Mellon University: The same group from the SDM
project contributes to this work. The main paradigm is still to
coordinate different visualizations via direct manipulation
techniques. This project uses a new drill-down and roll-up based
navigation method to travel inside the database. The application
automatically selects the best possible visualization for a given data
set.
VisDB - University of Munich: The main paradigm is to show the
similarities between attributes of the data. The definition of the
similarity function is left to the user. Color and distance is used to
give a sense of similarity between attributes.
VizControls - XEROX PARC: Set of applications including Magic
Lens, Table Lens, and others.
A new product, WebWinds, the successor of
LinkWinds -
NASA: The approach uses the tight coupling (linking) of the different
visualizations of the data. It is developed for scientific
visualization purposes (e.g., atmospheric data visualization). But the
output is not just a rendering of the input data. The tool can be used
to dynamically analyze it.
World Within Worlds - Columbia University: Mainly for visualization of functions as different 3D graphs.
XGobi -
AT&T: Allows different visualizations of the same data set
simultaneously and dynamically. The product is capable of taking
various projections of an n-dimensional data set on various attributes
and then animates these projections. Originally developed at Bellcore.
XGobi/ArcView: XGobi Project in combination with a GIS application.
Citations
Feiner, Steven and Beshers, Clifford, Worlds within Worlds: Metaphors for Exploring n-Dimensional Virtual Worlds, in Proceedings of the ACM SIGGRAPH Symposium on User Interface Software and Technology, pp. 76-83, 1990.
Abstract: n-Vision is a testbed for exploring n-dimensional worlds containing functions of an arbitrary number of variables. Although our interaction devices and display hardware are inherently 3D, we demonstrate how they can be used to support int
eraction with these higher-dimensional objects. We introduce a new interaction metaphor developed for the system, which we call "worlds within worlds": nested heterogeneous coordinate systems that allow the user to view and manipulate functions. Objects i
n our world may be explored with a set of tools. We describe an example n-Vision application in "financial visualization", where the functions are models of financial instruments.
Ahlberg, Christopher, Williamson, Christopher, and Shneiderman, Ben, Dynamic Queries for Information Exploration: An Implementation and Evaluation, in P
roceedings of ACM CHI'92 Conference on Human Factors in Computing Systems, Graphical Interfaces for Drawing, Exploring, and Organizing, pp. 619-626, 1992.
Abstract: We designed, implemented and evaluated a new concept for direct manipulation of databases, called dynamic queries, that allows users to formulate queries with graphical widgets, such as sliders. By providing a graphical visualization of t
he database and search results, users can find trends and exceptions easily. Eighteen undergraduate chemistry students performed statistically significantly faster using a dynamic queries interface compared to two interfaces both providing form fill-in as
input method, one with graphical visualization output and one with all-textual output. The interfaces were used to explore the periodic table of elements and search on their properties.
Tweedie, Lisa, Spence, Robert, Dawkes, Huw, and Su, Hua, Externalising abstract mathematical models, in Proceedings of ACM CHI' 96 Conference: Human Factors in Comput
ing Systems, pp. 406-412, 1996.
Abstract: Abstract mathematical models play an important part in
engineering design, economic decision making and other
activities. Such models can be externalised in the form of Interactive
Visualization Artifacts (IVAs). These IVAs display the data generated
by mathematical models in simple graphs which are interactively
linked. Visual examination of these graphs enables users to acquire
insight into the complex relations embodied in the model. In the
engineering context this insight can be exploited to aid design. The
paper describes two IVAs for engineering design: The Influence
Explorer and The Prosection Matrix. Formative evaluation studies are
briefly discussed.
Berkin, A. L. and Orton, M. N., LinkWinds: Interactive Scientific Data
Analysis and Visualization, Communications of the ACM, 37-4,
pp. 42-52, 1994.
Introductory Paragraph: The objectives of the research program are: 1)
To develope a software environment and test bed to support the rapid
prototypeing of visual data analysis; 2) To develope a user interface
that is thouroughly intuitive, allowing quick access to the software
for the novice as well as the advanced user; 3) To provide a suit of
sample applications that are useful across a variety of scientific
disciplines; for to provide tools to support user development of
application for this environment.
Stone, M. C., Fishkin, K, and Bier, E. A., The Movable Filter as a User Interface Tool, in Proceedings of ACM CHI'94 Conference on Human Factors in Computing Systems, In
formation Visualization, 1, pp. 306-312, 1994.
Abstract: Magic Lens filters are a new user interface tool that
combine an arbitrarily-shaped region with an operator that changes the
view of objects viewed through that region. These tools can be
interactively positioned over on-screen applications much as a
magnifying glass is moved over a newspaper. This paper describes their
advantages in more detail and illustrates them with examples of magic
lens filters in use over a variety of applications.
Rao, Ramana and Card, Stuart K., The Table Lens: Merging Graphical and
Symbolic Representations in an Interactive Focus+Context Visualization
for Tabular Information, in Proceedings of ACM CHI'94 Conference on
Human Factors in Computing Systems, Information Visualization, 1,
pp. 318-322, Color plates on pp. 481-482, 1994.
Abstract: We present a new visualization, called the Table Lens, for
visualizing and making sense of large tables. The visualization uses a
focus+context (fisheye) technique that works effectively on tabular
information because it allows display of crucial label information and
multiple distal focus areas. In addition, a graphical mapping scheme
for depicting table contents has been developed for the most
widespread kind of tables, the case-by-variables table. The Table Lens
fuses symbolic and graphical representations into a single coherent
view that can be fluidly adjusted by the user. This fusion and
interactivity enables an extremely rich and natural style of direct
manipulation exploratory data analysis.
Chuah, Mei C., Roth, Steven F., Mattis, Joe, and Kolojejchick, John, SDM:
Selective Dynamic Manipulation of Visualizations , in Proceedings of
the ACM Symposium on User Interface Software and Technology, 3D User
Interfaces, pp. 61-70, 1995.
Abstract: In this paper we present a new set of interactive techniques
for 2D an 3D visualizations. This set of techniques is called SDM
(Selective Dynamic Manipulation). Selective, indicating our goal for
providing a high degree of user control in selecting an object set, in
selecting interactive techniques and the properties they affect, and
in the degree to which a user action affects the
visualization. Dynamic, indicating that the interactions all occur in
real-time and that interactive animation is used to provide better
contextual information to users in response to an action or
operation. Manipulation, indicating the types of interactions we
provide, where users can directly move objects and transform their
appearance to perform different tasks. While many other approaches
only provide interactive techniques in isolation, SDM supports a suite
of techniques which users can combine to solve a wide variety of
problems.
Roth, S. F., Chuah, M. C., Kerpedjiev, S., Kolojejchick, J. A., and
Lucas, P., Towards an Information Visualization Workspace: Combining
Multiple Means of Expression, Human-Computer Interaction Journal, 1997.
Abstract: New user interface challenges are arising because people
need to explore and perform many diverse tasks involving large
quantities of abstract information. Visualizing information is one
approach to these challenges. But visualization must involve much more
than just enabling people to "see" information. People must also
manipulate it to focus on what is relevant and reorganize it to create
new information. They must also communicate and share information in
collaborative settings and act directly to perform their tasks based
on this information. These goals suggest the need for information
visualization workspaces with new interaction approaches. We present
several systems - Visage, SAGE and SDM - that comprise such a
workspace and a suite of user interface techniques for creating and
manipulating integrative visualizations. Our work in this area
revealed the need for interfaces that enable people to communicate
with systems in multiple complementary ways. We discuss four
dimensions for analyzing user interfaces that reveal the combination
of design approaches needed for visualizations to support information
analysis tasks effectively. We discuss the results of our attempts to
provide multiple forms of expression using direct manipulation and
propose areas where multimodal techniques are likely to be more
effective.
Keim, D. A. and Kriegal, H., XGobi: Interactive Dynamic Data
Visualization in the X Window System, 1996.
Abstract: XGobi is a data visualization system with state-of-the-art
interactive and dynamic methods for the manipulation of views of
data. It implements 2-D displays of projections of points and lines in
high-dimensional spaces, as well as parallel coordinate displays and
textual views thereof. Projection tools include dotplots of single
variables, plots of pairs of variables, 3-D data rotations, various
grand tours, and interactive projection pursuit. Views of the data
can be reshaped. points can be labeled and brushed with glyphs and
colors. Lines can be edited and colored. Several XGobi processes can
be run simultaneously and linked for labeling, brushing, and sharing
of projections. Missing data are accommodated and their patterns can
be examined; multiple imputations can be given to XGobi for rapid
visual diagnostics. XGobi includes an extensive on-line help
facility.
Miron Livny, Raghu Ramakrishnan, Kevin Beyer, Guangshun Chen, Donko Donjerkovic, Shilpa Lawande, Jussi Myllymaki, and Kent Wenger.DEVise: Integrated Querying and Visual Exploration of Large
Datasets. Proceedings of ACM SIGMOD, May, 1997.
Abstract: DEVise is a data exploration system that allows users to easily develop, browse, and share visual presentations of large tabular datasets(possibly containing or referencing multimedia objects) from several sources. The DEVise framework,
implemented in a tool that has been already successfully applied to a variety of real applications by a number of user groups.
Our emphasis is on developing an intuitive yet powerful set of querying and visualization primitives that can be easily combined to develop a rich ste of visual presentations that integrate data from a wide range of application domains. While DEVise is
a powerful visualization tool, its greatest strengths are the ability to interactively explore a visual presentation of the data at any level of detail (including retrieving individual data records), and the ability to seamlessly query and combine data fr
om a variety of local and remote sources. In this paper, we present the DEVise framework, describe the current tool, and report on our experience in applying it to several real applications.
Inselberg, A. and Dimsdale, B., Visualizing Multi-Variate
Relations with Parallel Coordinates, in Proceedings of the Third
International Conference on Human-Computer Interaction, Work with
Computers: Organizational, Management, Stress and Health Aspects;
Interface - Displays and Controls, 1, pp. 460-467, 1989.
Abstract: By means of parallel coordinates a non-projective mapping
between N-Dimension (for any N) and 2-Dimensional sets is
obtained. Relations among N variables are then represented by their
planar images, which have certain geometrical properties corresponding
to properties of the relation (hypersurface) that they
represent. Starting from a point {larr} {rarr} line duality when N=2,
the representation of lines in N-dimensions is given and illustrated
by an application to Air Traffic Control (i.e. for N=4). It is
followed by the representation of hyperplanes and more general convex
and some nonconvex in N-dimensional hypersurfaces. Some of these
results can be applied in Exploratory Data Analysis in Statistics. An
algorithm for constructing and exhibiting any interior point of such a
hypersurface is discussed. Such a display shows some local (i.e. near
the point) properties of the hypersurface and information on the
point's proximity to the boundary and is useful in Instrumentation and
Process Control.
Ahlberg, Christopher and Shneiderman, Ben, Visual Information Seeking using the FilmFinder, Department of Computer Science, Human-Computer Interaction Laboratory & Institute for Systems Research, University of Maryland, ACM CHI 94, 1994.
Brier, Eric A., Fishkin, Ken, Pier, Ken, and Stone, Maureen, The Movable Filter as an Interface Tool: The Video, Xerox PARC, ACM CHI 95, 1995.
Brier, Eric A., Fishkin, Ken, Pier, Ken, and Stone, Maureen, A Taxonomy of See-Through Tools: The Video, Xerox PARC, ACM CHI 95, 1995.
Brier, E. A., Fishkin, K., Pier, K., and Stone, M., A Taxonomy of See-Through Tools: The
Video, Xerox PARC, ACM CHI 95, 1995.
Brier, Eric A., Fishkin, Ken, Pier, Ken, Stone, Maureen, Baudel, Thomas, Conway, Matt (Xerox PARC), Buxton, William (University of Toronto), and DeRose, Tony (University of Washington), Toolglass and Magic Lenses: The See-Through Interface, ACM CHI 94, 19
94.
Lucas, P. (MAYA Design Group), Roth, Steven (CMU), Exploring Information With Visage, ACM CHI 96, 1996.
Plaisant, Catherine, Bruns, Tom, Shneiderman, Ben, and Doan, Khoa, Query Previews in Networked Information Systems: the Case of EOSDIS, University of Maryland, ACM CHI 97, 1997.
Plaisant, Catherine and Jain, Vinit, Dynamaps: Dynamic Queries on a Health Statistics
Atlas, University of Maryland at College Park, ACM CHI 94, 1994.
Rao, Ramana and Card, Stuart, Exploring Large Tables with the Table Lens, Xerox PARC, ACM CHI 95, 1995.
Rose, Anne and Vanniamparampil, Ajit, Using Dynamic Queries for Youth Services Information, University of Maryland at College Park, Human Computer Interaction Lab. Video Reports, 1995.
Roth, Steven, Kolojejchick, John, and Chuah, Mei C., SageTools: An Intelligent Environment for Sketching, Browsing, and Customizing Data-Graphics, Carnegie Mellon University, ACM CHI 95, 1995.
Shneiderman, Ben, Visual data mining using Spotfire, University of Maryland at College Park, Human Computer Interaction Lab. Video Reports, 1994.
Shneiderman, Ben, Dynamic queries demos: revised HomeFinder and text version plus health statistics atlas, University of Maryland at College Park, Human Computer Interaction Lab. Video Reports, 1994.
Tweedie, Lisa, Spence, Robert, Dawkes, Huw, and Su, Hua, The Influence Explorer - a Tool for Design Imperial College, England, ACM CHI 96, 1996.
Tweedie, L., Spence, R., Williams, D.,and Bhogal, R., The Attribute Explorer, Department of Electrical and Electronic Engineering, Imperial College, ACM CHI 94, 1994.
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