Despite the advancement ofvisualization techniques for scientific data over the last several years, there are still
significant problems in bringing thday's technology into the hands ofthe typical scientist. For example, there
are other computer science domains outside of computer graphics like data management that are required to
make visualization effective. One role ofdatamanagement can be expressedby the need for a class ofdata models
that is matched to the structure of scientific data as well as to how such data may be used. Unfortunately, the
critical component of data management is typically missing in most visualization systems.
Traditional methods ofhandling scientific data such as flat sequential files are generally inefficient in storage,
access or ease-of-use for large complex data sets particularly for applications like visualization. Modern,
commercial relational data management systems do not offer an effective solution because they are oriented
towards business applications. The relational model does not accommodate multidimensional or hierarchical
structures often found in scientific data sets nor provide adequate performance for the size, complexity and type
ofaccess dictated by such data sets. In contrast, these data base management systems have been quite viable
for a large class ofnon-spatial metadata management.
There is a need for a data (base) model that possesses elements of a modern data base management system but
is oriented toward scientific data sets and applications. Such a model must be easy to use, support large diskbased
data sets and accommodate scientific data structures. The NSSDC's Common Data Format (CDF) is one
implementation of a scientific data model, which provides abstract support for a class of data that can be described
by a multidimensionalbiock structure. Although alldata do notuit within this framework, alarge variety
of scientific data do.