All active development and support have shifted to ggobi. In contrast to xgobi, ggobi has
richer color support, multiple plotting windows, better portability to
Microsoft Windows and MacOSX, support for xml and csv file formats.
ggobi has a multidimensional scaling plugin called ggvis,
which supersedes xgvis, described below.
XGobi
A SYSTEM FOR MULTIVARIATE DATA VISUALIZATION

XGobi is a data visualization system for viewing highdimensional
data.
The authors are
Copyright of most code belongs to
Telcordia (formerly Bellcore),
where much of the work was done.

XGobi is FREELY AVAILABLE from this page, see below.

XGobi's primary views are SCATTERPLOTS and
LINE DRAWINGS whose points and lines can be
brushed and identified across LINKED VIEWS.

XGobi's auxiliary views include a PARALLEL COORDINATE
window and a case list window with text labels,
both linked to the primary scatterplot window.

XGobi has LINKED SCATTERPLOT MATRICES.
See
Di Cook's web page on this topic.

XGobi features INTERACTIVE DYNAMIC GRAPHICS: realtime zoom and pan,
3D data rotations, grand tours, correlation tours, projection
pursuit, and more.

XGobi can be used as a simple HIGHDIMENSIONAL DRAWING PROGRAM:
Data points in pdimensional space can be moved around manually, and lines can be
drawn to connect points.

XGobi can handle MISSING VALUES !

XGobi can be run on a PC running
Windows  with a little effort.

XGobi supports
REMOTE PROCEDURE CALLS
(RPCs) as a means for interprocess communication (IPC).
For more details, see the
man page and
this paper.
XGvis
A SYSTEM FOR MULTIDIMENSIONAL SCALING AND GRAPH LAYOUT IN ANY DIMENSION

XGvis is an interactive visualization system for
proximity data as well as for graphs and networks.
The authors are:
Copyright of much of the code belongs to
Telcordia (formerly Bellcore),
where the work was begun.

XGvis is FREELY AVAILABLE.

XGvis uses XGobi as its VISUALIZATION ENGINE.

XGvis implements MULTIDIMENSIONAL SCALING (MDS) to analyze
 dissimilarity data (to produce spatial configurations/maps of objects),
 multivariate data (for dimension reduction), and
 discrete graphs (for graph layout).
 Some XGvis FEATURES:

classical innerproduct scaling (TorgersonGower),

distance scaling (KruskalShepard),

nonmetric MDS with mixing of isotonic and identity transforms,

metric MDS with power transformations,

animation of MDS optimization,

restarts from random configurations and random perturbations,

configurations in any dimension,

weights as a power function of the dissimilarities,

differential weights between/within groups of objects,

within/between/anchored MDS with regard to groups defined by
colors and glyphs; special cases are multidimensional unfolding and external unfolding,

lower and upper trimming of dissimilarities,

random removal of dissimilarities for stability checks,

missing dissimilarity handling,

moving of configuration points with mouse dragging,

viewing of configurations with 3D rotations and grand tours,

linked views of covariates,

saving and printing of configurations,

XGobi window for Shepard diagram of fit ...
For more details, see the
man page and
this paper.
Downloading and Installing XGobi and XGvis:
[To the members of the DIMACS MDS working group: This is the newest
version of XGobi/XGvis shown at the meeting. Use the extensive
help pages of XGvis to get started.]
XGobi and XGvis (April 2002 version) are bundled in a single shar or tar file:
To install xgobi and xgvis, do the following: unpack
`xgobi.sh' or 'xgobi.tar', creating a subdirectory `xgobi'. Go to
`xgobi/src', create `Makefile' automatically from `Imakefile' by
executing `xmkmf', compile by executing `make', put the executable in
your path, and finally run by typing `xgobi filename' or `xgvis
filename'. For example:
tar zxf xgobi.tar.gz # if you downloaded the gzipped tar file
or
gunzip xgobi.sh.gz # if you downloaded the gzipped shar file
/bin/sh xgobi.sh # unpack the shar file
then
cd xgobi/src # the source directory
xmkmf # create `Makefile' from `Imakefile'
make # compile xgobi and xgvis
# make the xgobi and xgvis executables available,
# eg, by adding this directory to your path:
set path = ($path `pwd`) # csh, tcsh, ... users
export PATH=$PATH:`pwd` # ksh, bash, ... users
# This will work for the current session; for later sessions,
# add the appropriate line to your startup file, replacing
# "`pwd`" with the full pathname of the `src' directory.
# finally run first examples:
xgobi ../data_xgobi/places # the places rated data
xgvis ../data_xgvis/morsecodes # the morsecode data
If something doesn't work, read `xgobi/Readme.install'.
Link between XGobi and ArcView
The link connects the geographic information system ArcView
with XGobi to facilitate exploratory analysis of spatiallyreferenced
data. The link provides connections between the geography and:
 multiple attribute plots
 variogram clouds
 spatial CDFs
 multivariate variogram clouds
 lagged scatterplots
The additional files and some references can be downloaded from
this page.
References:

``XGvis: Interactive Data Visualization with Multidimensional Scaling''
[gzipped PostScript, 254 Kb]
[PDF, 813 Kb]
A. Buja, D. F. Swayne, M. Littman, N. Dean, H. Hofmann (2001).
This is the most up to date work on XGvis and covers its 1998
and 2001 redesigns and extensions.
[Tentatively accepted for publication in the Journal of Computational
and Graphical Statistics.]

``Visualization Methodology for Multidimensional Scaling''
[gzipped PostScript, 197 Kb]
[PDF, 592 Kb]
A. Buja, D. F. Swayne (2001).
A companion paper to the above. It shows what how the XGvis functionality
can be used for specific MDS problems.

``XGobi: Interactive Dynamic Data Visualization in the X Window System,''
[gzipped PostScript, 95 Kb]
[PDF, 253 Kb]
D. F. Swayne, D. Cook, A. Buja (1998).
Journal of Computational and Graphical Statistics 7 (1) (1998).
This is the most up to date overview of XGobi and is the
closest thing to a manual.
It includes the
199698 redesign of the human interface, and new features such as
parallel coordinate displays, jitter plots for categorical variables,
missing data support, dragging points, and more.

``Missing Data in Interactive HighDimensional Data Visualization,''
D. F. Swayne, A. Buja (1998).
Computational Statistics 13 (1) (1998).
A similar paper with a different data example will appear in the
Proceedings of the 1997 American Statistical Association Meetings (1998).
This is about recently implemented methods in XGobi for the exploration
of data with missing values.

``Manual Controls For HighDimensional Data Projections,''
D. Cook, A. Buja,
Journal of Computational and Graphical Statistics 6 (4) (1997).
A paper on methods for manual control of 2D projections from highdimensional
data spaces.

``Interactive HighDimensional Data Visualization,''
[gzipped PostScript, 60 Kb]
[PDF, 206 Kb]
A. Buja, D. Cook, D. F. Swayne,
Journal of Computational and Graphical Statistics 5(1) 7899 (1996).
[The above files have no figures; click here to see the figure gallery.]
This paper contains a taxonomy of interactive data visualization based on the notions of focusing, linking, and arranging views of data.
A few case studies of XGobi applications illustrate the taxonomy.

``Interactive Graphical Methods in the Analysis of Customer Panel Data,'' with discussion,
M. Koschat, D. F. Swayne,
Journal of Business and Economics Statistics 14(1) 113132 (1996).

``Dynamic graphics in a GIS: a link between ARC/INFO and XGobi,''
J. Symanzik, J. Majure, D. Cook, and N. Cressie,
Computing Science and Statistics: Proc. of the 26th Symp. on the Interface, 431535 (1994).

``Higher Dimensional Representations of Graphs,''
A. Buja, N. Dean, M. Littman and D. Swayne,
Technical Report 9547, DIMACS, Piscataway, NJ (1995).
A paper on the Netpad system for graph manipulation,
and XGvis/XGobi for higher dimensional graph layout.

``Visualizing the Embedding of Objects in Euclidean Space,''
M. L. Littman, D. F. Swayne, N. Dean, A. Buja,
Computing Science and Statistics: Proc. of the 24th Symposium on the Interface, 208217 (1992).
A paper about the XGvis system for interactive Multidimensional
Scaling (MDS). XGvis uses XGobi to view embedded configurations.
Kruskal's optimization algorithm can be viewed in progress.
Debby Swayne recently revived this program; it has nothing lost of its
usefulness. We hope to be able to offer it to the public sometime soon.

``XGobi Meets S: Integrating Software for Data Analysis,''
D. F. Swayne, N. Hubbell, A. Buja,
Computing Science and Statistics: Proc. of the 23rd Symposium on the Interface, 430434 (1991).

``XGobi: Interactive Dynamic Graphics in the X Window System with a Link to S,''
D. F. Swayne, D. Cook, A. Buja,
Proceedings of the 1991 American Statistical Association Meetings (1992).
This is the first published document about XGobi.

``Theory and Computational Methods for Dynamic Projections in
HighDimensional Data Visualization,''
A. Buja, D. Cook, D. Asimov, C. B. Hurley.
A monograph on rendering techniques, mathematics, and algorithms for
tours and related methods.

``Prosection Views: Dimensional Inference through Sections and Projections,'' with discussion,
(paper, figures, rejoinder)
G. W. Furnas, A. Buja,
Journal of Computational and Graphical Statistics 3, 323385 (1994).
Explores the question of what can be inferred about highdimensional
objects when looking at their projections and sections. An
interesting duality between projections and sections is described.

``The Grand Tour via Geodesic Interpolation of 2Frames,''
D. Asimov, A. Buja,
Visual Data Exploration and Analysis, Symposium on Electronic Imaging Science and Technology (IS&T/SPIE) (1994).
An early technical paper on grand tour construction. Superseded by
the above monograph on "Theory and Computational Methods ...".

``Grand Tour and Projection Pursuit,''
D. Cook, A. Buja, J. Cabrera,
Journal of Computational and Graphical Statistics 4(3) 155172 (1995).
One of two papers from Di's thesis.

``Projection Pursuit Indices based on Orthogonal Function Expansions,''
D. Cook, A. Buja, J. Cabrera,
Journal of Computational and Graphical Statistics 2 3 225250 (1993).
Di's other thesis paper. Expands on work by J.H. Friedman and P. Hall
on exploratory projection pursuit based on expansions.

``Analyzing HighDimensional Data with Motion Graphics,''
C. B. Hurley, A. Buja,
SIAM Journal on Scientific and Statistical Computing 11, 11931211, (1990).
Describes a marriage of mulitvariate analysis with motion graphics.
Unfortunately the functionality shown here is not currently available
in any software system. It would be desirable to have it in xgobi or
now ggobi.

``Elements of a Viewing Pipeline for a Data Analysis,''
A. Buja, D. Asimov, C. B. Hurley, J. A. McDonald,
in: Dynamic Graphics for Statistics, eds.: W. S. Cleveland, M. E. McGill;
Wadsworth Statistics/Probability Series (1988).
Introduces important pipeline concepts for the construction of complex
data visualization systems. Based on a Lispbased predecessor system
of XGobi.

``Grand Tour Methods: An Outline,''
A. Buja, D. Asimov,
17th Symposium on the Interface of Computer Science and Statistics 6367 (1986)
The earliest paper that describes grand tours as currently implemented
in XGobi, and now in GGobi.

``Interactive Data Visualization using Focusing and Linking,''
A. Buja, J. A. McDonald, J. Michalak, W. Stuetzle,
Visualization '91, 156163 (1991).
Still of interest: an early paper on two important data visualization
concepts.

``Painting multiple views of complex objects,''
J. A. McDonald, W. Stuetzle, A. Buja,
OOPSLA/ECOOP '90 Proceedings, 245257 (1990).
A paper related to the one above. More oriented towards systems aspects.