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Bug#641399: ITP: visad -- Visualization for Algorithm Development

Package: wnpp
Severity: wishlist
Owner: Mathieu Malaterre <mathieu.malaterre@gmail.com>

* Package name    : visad
  Version         : 2.0
  Upstream Author : Bill Hibbard
* URL             : http://www.ssec.wisc.edu/~billh/visad.html
* License         : GPL, LGPL, BSD
  Programming Lang: Java
  Description     : Visualization for Algorithm Development

 VisAD is a Java component library for interactive and collaborative
 visualization and analysis of numerical data. The name VisAD is an acronym for
 "Visualization for Algorithm Development". The system combines:
 The use of pure Java for platform independence and to support data sharing and
 real-time collaboration among geographically distributed users. Support for
 distributed computing is integrated at the lowest levels of the system using
 Java RMI distributed objects.
 A general mathematical data model that can be adapted to virtually any
 numerical data, that supports data sharing among different users, different
 data sources and different scientific disciplines, and that provides
 transparent access to data independent of storage format and location (i.e.,
 memory, disk or remote). The data model has been adapted to netCDF, HDF-5,
 FITS, HDF-EOS, McIDAS, Vis5D, GIF, JPEG, TIFF, QuickTime, ASCII and many other
 file formats.
 A general display model that supports interactive 3-D, data fusion, multiple
 data views, direct manipulation, collaboration, and virtual reality. The
 display model has been adapted to Java3D and Java2D and used in an ImmersaDesk
 virtual reality display.
 Data analysis and computation integrated with visualization to support
 computational steering and other complex interaction modes.
 Support for two distinct communities: developers who create domain- specific
 systems based on VisAD, and users of those domain-specific systems. VisAD is
 designed to support a wide variety of user interfaces, ranging from simple data
 browser applets to complex applications that allow groups of scientists to
 collaboratively develop data analysis algorithms.
 Developer extensibility in as many ways as possible.

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