Gnuplot is a portable command-line driven interactive datafile (text or binary) and function plotting utility for UNIX, IBM OS/2, MS Windows, DOS, Apple Macintosh, VMS, Atari and many other platforms.

Gnuplot supports various kinds of plots. In 2D, it can draw line, point, dot, box, histogram graphs or vector fields. In 3D, it supports line, point and dot surfaces, with or without hidden line removal. It supports color or grayscale surfaces and maps, even for non-equidistant and non-rectangular 3D data, otherwise it offers data gridding.

Tested. Standard part of the scientists’ baggage. But it has an old style command language and unfortunately it is also not interactive.

A free, GPL, non-interactive software package for producing plots, charts, and graphics from data. It was developed in a Unix/C environment and runs on various Unix, Linux, and win32 systems. ploticus is good for automated or just-in-time graph generation, handles date and time data nicely, and has basic statistical capabilities. It allows significant user control over colors, styles, options and details.

Tested. Nice and powerful. Comes with a set of prebuilt templates. Unfortunately it is not interactive.

Grace is a WYSIWYG 2D plotting tool for the X Window System and M*tif. Grace runs on practically any version of Unix-like OS. As well, it has been successfully ported to VMS, OS/2, and Win9*/NT/2000/XP (some minor functionality may be missing, though).

Tested. Hard to get started, but it is a good, simple interactive tool. The hardest part is to understand the data file format. But if you load a chart and save it, the resulting ASCII file is quite simple to understand.

R is a language and environment for statistical computing and graphics. It provides a wide variety of statistical (linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering…) and graphical techniques, and is highly extensible.

One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.

R is available as Free Software under the terms of the Free Software Foundation’s GNU General Public License in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.

Not tested yet.

SciGraphica is a scientific application for data analysis and technical graphics. It pretends to be a clone of the popular commercial (and expensive) application "Microcal Origin". It fully supplies plotting features for 2D, 3D and polar charts. The aim is to obtain a fully-featured, cross-platform, user-friendly, self-growing scientific application. It is free and open-source, released under the GPL license.

Not tested yet. But seems Linux-only for now.

ParaView is an application designed with the need to visualize large data sets in mind.

ParaView runs on distributed and shared memory parallel as well as single processor systems and has been successfully tested on Windows, Linux and various Unix workstations and clusters. Under the hood, ParaView uses the Visualization Toolkit (VTK) as the data processing and rendering engine and has a user interface written using a unique blend of Tcl/Tk and C++.

Tested. Very good end-user tool for 3D scientific visualization. The only drawback is that is quite complex to customize.

The Visualization ToolKit (VTK) is an open source, freely available software system for 3D computer graphics, image processing, and visualization used by thousands of researchers and developers around the world. VTK consists of a C++ class library, and several interpreted interface layers including Tcl/Tk, Java, and Python.

VTK supports a wide variety of visualization algorithms including scalar, vector, tensor, texture, and volumetric methods; and advanced modeling techniques such as implicit modeling, polygon reduction, mesh smoothing, cutting, contouring, and Delaunay triangulation. In addition, dozens of imaging algorithms have been directly integrated to allow the user to mix 2D imaging / 3D graphics algorithms and data.

VTK has been installed and tested on nearly every Unix-based platform, Windows PCs, and Mac.

Tested. Very complete and powerful library for 3D scientific visualization. It is not an end-user tool, it is a development package. But scripting language interface make possible to experiment with it rather quickly.

Vis5D is a system for interactive visualization of large 5-D gridded data sets such as those produced by numerical weather models. One can make isosurfaces, contour line slices, colored slices, volume renderings, etc of data in a 3-D grid, then rotate and animate the images in real time. There’s also a feature for wind trajectory tracing, a way to make text annotations for publications, support for interactive data analysis, etc.

The new developments of Vis5D continue as Vis5d+. Unfortunately this version is still Linux only.

Tested. It is specialized in meteorological data visualization, but it is a good tool to learn visualization techniques. Unfortunately it is Unix only, but a Windows porting that requires an X server (one like Cygwin/X is enough) can be found at the bottom of the Vis5D page.

MayaVi is a free, easy to use scientific data visualizer. It is written in Python and uses the amazing Visualization Toolkit (VTK) for the graphics. It provides a GUI written using Tkinter. MayaVi is free and distributed under the conditions of the BSD license. It is also cross platform and should run on any platform where both Python and VTK are available (which is almost any *nix, Mac OSX or Windows).

Tested. It is quite good and simple to use. Needs only some more example data file to experiment with.

XmdvTool is a public-domain software package for the interactive visual exploration of multivariate data sets. It is available on all major UNIX/LINUX/MAC and Window platforms. It supports four methods for displaying flat form data and hierarchically clustered data: Scatterplots, Star Glyphs, Parallel Coordinates, Dimensional Stacking.

XmdvTool also supports a variety of interaction modes and tools, including brushing in screen, data, and structure spaces, zooming, panning, and distortion techniques, and the masking and reordering of dimensions. Univariate display and graphical summarization, via tree-maps and modified Tukey box plots, are also supported. Finally, color themes and user customizable color assignments permit tailoring of the aesthetics to the users.

Tested. Very complete and powerful to start experimenting with multivariate visualization techniques.

GGobi is a data visualization system for viewing high-dimensional data and is the next edition of XGobi.

Tested. Interesting, but a bit limited compared to XGobi.

XGobi is a data visualization system for viewing high-dimensional data.

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. XGobi features INTERACTIVE DYNAMIC GRAPHICS: realtime zoom and pan, 3-D data rotations, grand tours, correlation tours, projection pursuit, and more. XGobi can be used as a simple HIGH-DIMENSIONAL DRAWING PROGRAM: Data points in p-dimensional space can be moved around manually, and lines can be drawn to connect points.

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

Tested. Not simple to use and understand, but it covers a lot of multidimensional visualization techniques. Unfortunately on Windows it needs an X server running (one like Cygwin/X is sufficient).

parvis is a tool for parallel coordinates visualization of multidimensional data sets. The main goal was to develop a flexible, reusable user-interface component compliant to the Java Swing and Java Beans standards, to perform state of the art PC visualization and provide the user with the necessary means of visual interaction with the data set.

Tested. Simple to use to explore parallel coordinates visualization technique. It is a little buggy, but it works.

Open source data visualization and analysis for novice and experts. Data mining through visual programming or Python scripting. Components for machine learning. Add-ons for bioinformatics and text mining. Packed with features for data analytics.

To be tested.

Works well for classical business charting (line, histogram, pie). But it has also the ability to add a lot of chartjunk to your visualization.

Tested. Well know, but limited to business charts. Beware of gratuitous graphical effects.

MATLAB is a high-level technical computing language and interactive environment for algorithm development, data visualization, data analysis, and numerical computation.

MATLAB 7 introduces a new set of tools to let you interactively create and edit plots without typing any MATLAB code. Now you can create plots from scratch and visualize your data much more quickly. You can also automatically generate the code to create the plot again with new data.

Tested. Good and well known. It has a lot of add-on packages for example for SOM.

The unique Mathcad visual format and scratchpad interface integrate standard mathematical notation, text, and graphs in a single worksheet.

Tested (not recently). The active worksheet metaphor is really user friendly.