Correlative visualizaton techniques for multidimensional data
Lloyd A. Treinish, Craig Goettsche · IBM Journal of Research and Development · 1991
Critical to the understanding of data is the ability to provide pictorial or visual representations of those data, particularly in support of correlative data analysis. Despite the many advances in visualization techniques for scientific data over the last several years, there are still significant problems in bringing today's hardware and software technology into the hands of the typical scientist. For example, there are computer science domains other than computer graphics, such as data management, that are required to make visualization effective. Well-defined, flexible mechanisms for data access and management must be combined with rendering algorithms, data transformations, etc. to form a generic visualization pipeline. A generalized approach to data visualization is critical for the correlative analysis of distinct, complex, multidimensional data sets in the space and earth sciences. Different classes of data representation techniques must be used within such a framework, which can range from simple, static two- and three-dimensional line plots to animation, surface rendering, and volumetric imaging. Static examples of actual data analyses will illustrate the importance of an effective pipeline in a data visualization system.